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SCHOOL OF PUBLIC HEALTH 
COLLEGE OF HEALTH SCIENCES 
UNIVERSITY OF GHANA 
 
 
IDENTIFICATION AND MAPPING OF RISK FACTORS 
ASSOCIATED WITH CHOLERA IN SELECTED COMMUNITIES IN 
THE GREATER ACCRA REGION, GHANA 
 
BY 
 
ANTHONY DONGDEM 
(10256952) 
 
 
 
THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, 
LEGON IN PARTIAL FULFILLMENT OF THE REQUIREMENT 
FOR THE AWARD OF DOCTOR OF PHILOSOPHY IN PUBLIC 
HEALTH DEGREE 
 
 
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DEPARTMENT OF EPIDEMIOLOGY AND DISEASE CONTROL 
 
 
SEPTEMBER, 2021
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DECLARATION 
 
I, ANTHONY DONGDEM hereby declare that apart from the references cited to other 
people’s work which is duly acknowledged, this research work is the result of my own 
research work conducted under the supervision and has never on any previous occasion 
been submitted in part or whole to any Institution or Board for the award of any degree. 
 
  
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DEDICATION 
 
This work is dedicated to my wife Rita, children Maximilian, Krispin, Elsa-Keziah, 
Jaiden, mother Philomena, and late father Mr. Luke Dongdem. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ACKNOWLEDGMENT 
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I wish to express my profound gratitude to my academic supervisors; Prof. Francis Anto 
(Head of Department), Dr. Bismark Sarfo, and Dr. Adolphina Addo-Lartey of the 
department of Epidemiology and Disease Control, School of Public Health who guided me 
through all the stages of the proposal to the thesis writing. I appreciate your invaluable 
guidance, contribution, advice, and patience.  I also want to appreciate the former Dean of 
the School of Public Health, Prof. Julius Fobi, and all the staff of the School of Public 
Health for their inputs and encouragement. 
I am greatly indebted to the Greater Accra Regional Director of Health Services Dr (Mrs.) 
Charity Sarpong and all the Metro, Submetro, and District Directors for permission to 
conduct the study in the region. Am also grateful to their team of staff for the support 
given me during the community entry. I am tremendously grateful also to the hard-
working research assistances for their support during the data collection. 
My special thanks also to Mr. Benjamin Kwasi Offei and Mr. Daniel Larbi Agyarko, Soil 
and Environmental Science Laboratory BNARI, Ghana Atomic Energy for supporting me 
with the water analysis. Also too, Dr. Gifty Boateng, head of the National Public Health 
and Reference Laboratory (NPHRL) for the support in the identification and confirmation 
of all my bacteria isolates.  My utmost thanks also to Dr. Kwabena Duodu, for allowing 
me to use his molecular Laboratory, University of Health and Allied Sciences (UHAS) for 
my molecular analysis. To Dr. David Nana Adjei, senior lecturer, Allied Health Sciences, 
University of Ghana, Mr. Wisdom Takramah, Mr. Maxwel Afetor, Mr. Ernest Akyereku, 
and Mr. Isaac Owusu for helping me with the statistical and spatial analysis. 
I also want to acknowledge the financial support from the Ghana Education Trust Fund 
(GETFund) and the College of Health Sciences, University of Ghana to complete this 
work. 
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ABSTRACT 
Background 
Cholera is an acute diarrhoeal disease caused by the toxigenic Vibrio cholerae O1 or O139 
strains.  Globally, it is estimated to infect over 1.3 million people with over 21, 000 deaths 
annually with the most affected countries being in Africa and Asia. In Ghana, cholera has 
become endemic in some communities in the Greater Accra Region (GAR) with reported 
focal epidemics. The factors contributing to its persistence and spread in these 
communities are not well understood. To prevent future epidemics, it is important to 
identify the specific risks in these communities that may account for its persistence.  This 
study, therefore, identified and mapped risk factors associated with cholera at the 
household and community levels in the GAR. 
Methods 
A community-based cross-sectional comparative study was conducted in 24 (12 each) 
from cholera endemic and non-endemic communities from March 2019 to March 2020. 
The multistage cluster sampling procedure was used in selecting households and a 
structured questionnaire was used to collect data from the head of households. Drinking 
water from selected households was sampled for water quality and the community water 
bodies were assessed for the presence of toxigenic strains of V. cholerae during the wet 
and dry seasons. A sanitation inspection guide was used to assess the sanitation conditions 
of the communities and GPS coordinates of the identified risk taken.  Data were analysed 
using STATA version 14 software. Associations between the history of cholera and the 
independent variables were determined using Chi-square/Fisher exact test and 
multivariable penalized logistic regression. The differences in bacterial counts were 
determined using the Kruskal Wallis rank test. A p-value less than 0.05 was considered 
significant for the associations. Principal Component Analysis was used to categorize the 
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household wealth index and the environmental sanitation conditions. Significantly 
identified risk factors were mapped with the historical cholera cases using Arc GIS.   
Results 
Results of the multivariable penalized logistic regression showed that the presence of 
waste dumpsites (AOR=2.96, 95% CI: 1.11-7.88, p=0.030) and big open drainage 
(AOR=5.78, 95% CI: 1.89-17.72, p=0.002) were predictors of cholera occurrence.  
Whereas cooking in a detached kitchen (AOR=0.22, 95% CI: 0.06-0.82. P=0.024), or in 
yard (AOR=0.42, 95% CI: 0.21-0.86, p=0.017), and the availability of public toilets in the 
neighbourhood (AOR=0.28, 95% CI: 0.08-0.97, p=0.046) were significantly protective 
against cholera. The household drinking water was mostly contaminated with faecal 
coliforms with counts exceeding the zero cfu/100ml standard. Klebsiella penumoniae and 
Escherichia coli were the dominant organisms isolated. The household stored water was 
more contaminated than that obtained from the direct source and the differences were 
significant. The contamination was generally higher in the wet season than in the dry 
season.  No toxigenic Vibrio cholerae O1 or O139 was isolated from the household 
drinking water and the environmental water bodies. However, Vibrio fluvialis and Vibrio 
algionolyticus were isolated from the environmental water bodies. Environmental 
sanitation revealed 66.2% (300/453) of the endemic communities to have poor sanitation 
compared to the 67.5% (306/453) of the non-endemic communities with good sanitation 
conditions. 
Conclusion/Recommendation 
The presence of public toilets, waste dumpsites, and open drainage systems close to each 
other and their combined effect may account for the cholera endemicity in the endemic 
communities. Household drinking water contaminated with faecal coliforms is an indicator 
of high risk for cholera transmission. The absence of toxigenic strains of Vibrio cholerae 
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O1 or O139 in the drinking and environmental water bodies could predict the absence of 
cholera occurrence.  Vibrio fluvialis and Vibrio algionolyticus emerging cholera-like 
diarrhoea pathogens were isolated from the environmental water bodies. Poor 
environmental sanitation is still prevalent in the endemic communities. It is recommended 
that sanitation laws and the treatment of household drinking water at the point-of-used as 
well as siting of public toilets, waste dumpsites, and open drainages beyond 500 m from 
households are enforced.                           
  
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TABLE OF CONTENTS 
 
 
DEDICATION ...................................................................................................................... ii 
ACKNOWLEDGMENT ....................................................................................................... ii 
ABSTRACT ......................................................................................................................... iv 
TABLE OF CONTENTS .................................................................................................... vii 
LIST OF FIGURES .......................................................................................................... xiii 
LIST OF TABLES .............................................................................................................. xv 
LIST OF ABBREVIATIONS ........................................................................................... xvii 
CHAPTER ONE ................................................................................................................... 1 
INTRODUCTION ................................................................................................................ 1 
1.1 Background .................................................................................................................... 1 
1.1.1 Epidemiology .............................................................................................................. 1 
1.1.2 Clinical Presentation, diagnosis, and management ................................................. 2 
1.1.3 Cholera Risk Factors ................................................................................................. 3 
1.1.4 Spatial Distribution .................................................................................................... 4 
1.2 Problem Statement ........................................................................................................ 5 
1.3 Conceptual Framework ................................................................................................ 8 
1.4 General Objectives ........................................................................................................ 9 
1.4.1 Specific Objectives ..................................................................................................... 9 
1.5 Justification ................................................................................................................... 10 
CHAPTER TWO ................................................................................................................ 12 
LITERATURE REVIEW.................................................................................................... 12 
2.1 History of Cholera ......................................................................................................... 12 
2.2 Cholera in Africa ........................................................................................................... 13 
2.3 Cholera in Ghana........................................................................................................... 13 
2.3 The Pathogen ............................................................................................................... 14 
2.4 Infections and Symptoms ........................................................................................... 17 
2.5 Transmission of Cholera ............................................................................................ 19 
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2.6 Diagnosis and Detection of Cholera........................................................................... 20 
2.7 Treatment and Prevention of Cholera ...................................................................... 21 
2.7.1 Treatment.................................................................................................................. 21 
2.7.2 Prevention ................................................................................................................. 22 
2.8 Cholera Risk Factors Influencing Transmission ...................................................... 23 
2.8.1 Host Genetic factors ................................................................................................. 23 
2.8.2 Demographic Factors ............................................................................................... 24 
2.8.3 Socioeconomic factors .............................................................................................. 25 
2.8.4 Water-related risk to cholera .................................................................................. 27 
2.8.4.1 Water Source, Transportation and Handling ........................................................... 27 
2.8.4.2 Water Treatment...................................................................................................... 29 
2.8.4.3 Water Quality Analysis ........................................................................................... 30 
2.8.4.4 Microbial Parameters .............................................................................................. 30 
2.8.5 Food-related risk factors for cholera .......................................................................... 34 
2.8.6 Environmental Sanitation ........................................................................................... 36 
2.8.7 Climatic factors .......................................................................................................... 37 
2.8.8 Hygiene ...................................................................................................................... 39 
2.8.9 Water, Sanitation and Hygiene Interventions related to Cholera ............................... 40 
2.9 Spatial distribution of cholera ....................................................................................... 41 
CHAPTER THREE ............................................................................................................. 43 
METHODS ......................................................................................................................... 43 
3.1 Study Design ................................................................................................................. 43 
3.2 Study Area ................................................................................................................... 43 
3.2.1 Cholera Endemic Communities ................................................................................. 47 
3.2.2 Cholera Non-endemic Communities .......................................................................... 48 
3.3 Study Population ......................................................................................................... 48 
3.4 Study Variables ........................................................................................................... 49 
3.5 Sample Size Determination for households .............................................................. 52 
3.6 Sample size Determination for household drinking water ............................................ 55 
3.7 Sampling Technique ................................................................................................... 56 
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3.8 Inclusion Criteria ........................................................................................................ 57 
3.9 Exclusion Criteria ....................................................................................................... 58 
3.10 Data Collection Method/Technique and Tools ....................................................... 58 
3.11 Environmental Assessment ...................................................................................... 59 
3.12 Water Sample Collection .......................................................................................... 60 
3.13 Laboratory Analysis .................................................................................................... 61 
3.13.1 Bacteriological Quality of water .............................................................................. 61 
3.13.1.1 Membrane Filtration Method ................................................................................ 61 
3.13.1.2 Media Preparation and Selection .......................................................................... 61 
3.13.1.3 Set up of the membrane filtration system ............................................................. 62 
3.13.1.4 Counting of colonies on the Plates ........................................................................ 63 
3.13.1.5 Sub-culturing of colonies ...................................................................................... 63 
3.13.1.6 Confirmation of V. cholerae serotype ................................................................... 63 
3.13.1.7 Biochemical testing of colonies ............................................................................ 64 
3.13.1.8 Processing of the Antigenic Profile Index 20E Biochemical Test ........................ 64 
3.13.2 Genomic DNA Extraction ........................................................................................ 65 
3.13.2.1 Extraction of V. cholerae DNA from Environmental water samples and broth 
Culture ................................................................................................................................. 65 
3.13.2.2 Polymerase Chain Reaction Analysis ................................................................... 66 
3.15.2 Wealth Index ............................................................................................................ 67 
3.15.3 Sanitation Assessment .............................................................................................. 68 
3.14 Spatial Data Collection ............................................................................................... 69 
3.14.1 Cholera data abstraction ........................................................................................... 69 
3.14.2 Other spatial data...................................................................................................... 69 
3.15 Data Analysis ............................................................................................................. 69 
3.15.1 Data processing and analysis ................................................................................ 69 
3.15.4 Spatial data processing and Analysis ....................................................................... 71 
3.15.5 Spatial point pattern analysis ................................................................................ 71 
3.15.6 Proximity analysis .................................................................................................... 72 
3.16 Quality Assurance ....................................................................................................... 73 
3.16.1 Questionnaire Development and Data Collection .................................................... 73 
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3.16.1.1 Training of Research Assistants ............................................................................ 73 
3.16.1.2 Pilot Study ............................................................................................................. 73 
3.16.1.3 Validity .................................................................................................................. 74 
3.16.1.4 Reliability .............................................................................................................. 74 
3.16.1.5 Data Entry ............................................................................................................. 74 
3.16.2 Spatial Data collection ............................................................................................. 74 
3.16.3 Laboratory Analysis ................................................................................................. 75 
3.17 Ethical Consideration .................................................................................................. 75 
3.17.1 Ethical Approval ...................................................................................................... 76 
3.17.2 Study Area Approval................................................................................................ 76 
3.17.3 Informed consent ...................................................................................................... 76 
3.17.4 Risk of the study ...................................................................................................... 76 
3.17.5 Benefits .................................................................................................................... 76 
3.17.6 Right to withdrawal .................................................................................................. 77 
3.17.7 Confidentiality/Anonymity ...................................................................................... 77 
3.18 Safety Precautions ....................................................................................................... 77 
CHAPTER FOUR ............................................................................................................... 78 
RESULTS ........................................................................................................................... 78 
4.1 Socioeconomic characteristics of households in the Greater Accra Region ................. 78 
4.2 Associations between socioeconomic characteristics of household respondents and 
cholera in the Greater Accra Region ................................................................................... 98 
4.3 Associations between behavioural factors and cholera in the Greater Accra Region. 104 
4.3.1 Drinking water sources and handling practices among households and cholera ..... 104 
4.3.2 Food eating habits and cholera ................................................................................. 104 
4.3.3 Solid waste disposal practices and cholera .............................................................. 105 
4.3.4 Liquid waste disposal and cholera ........................................................................... 105 
4.4 Assessment of the bacteriological quality of drinking water and cholera risk in Greater 
Accra Region ..................................................................................................................... 111 
4.5 Environmental assessment for the presence of Vibrio cholerae O1/O139 toxigenic 
strains in the water bodies in the communities ................................................................. 116 
4.6 Environmental assessment of the sanitation and cholera risk in the communities ..... 122 
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4.7 Assessment and identification of environmental risk factors of cholera in the Greater 
Accra Region ..................................................................................................................... 131 
4.7.1 Associations between environmental risk factors and cholera ................................ 131 
4.8 Spatial relationship between significant environmental risk factors and the spread of 
cholera ............................................................................................................................... 134 
CHAPTER FIVE ............................................................................................................... 140 
DISCUSSIONS ................................................................................................................. 140 
5.1 Behavioural Factors Associated with Cholera Outbreaks ........................................... 140 
5.1.1 Water sources and handling factors ......................................................................... 140 
5.1.2 Food eating practices................................................................................................ 142 
5.1.3 Solid waste disposal factors ..................................................................................... 145 
5.1.4 Liquid waste disposal factors ................................................................................... 149 
5.2 Bacteriological quality of household drinking water .................................................. 149 
5.3 Assessment of environmental water bodies for the presence of V. cholerae O1/O139
 ........................................................................................................................................... 153 
5.4 Assessment of Environmental Sanitation Condition of the Communities .................. 155 
5.5 Assessment of Environmental related factors associated with cholera ....................... 157 
5.5.1 Environmental factors and cholera........................................................................... 157 
5.6 Spatial relationship between significant environmental risk factors and the spread of 
cholera ............................................................................................................................... 160 
5.7 Limitations of the Study .............................................................................................. 162 
CHAPTER SIX ................................................................................................................. 164 
CONCLUSION AND RECOMMENDATIONS .............................................................. 164 
6.1 Conclusion .................................................................................................................. 164 
6.2 Recommendations ..................................................................................................... 165 
6.3 Contribution to Knowledge ......................................................................................... 167 
a. This research provides evidence that V. cholerae O1 and O139 is not permanently
 167 
REFERENCES .................................................................................................................. 169 
APPENDICES .................................................................................................................. 186 
Appendix A: Bacteriological Media Preparations ............................................................ 186 
Appendix B: Biochemical Test and Staining Techniques ................................................ 187 
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Appendix C: Antigenic Profile Index 20 Enterobacteriaceae Biochemical Testing ......... 194 
Appendix D: Polymerase Chain Reaction work ............................................................... 196 
Appendix E: Outputs for Multicollinearity, goodness of fit and reliability tests .............. 198 
Appendix F: Household Questionnaire ............................................................................. 201 
Appendix G: Environmental Health Inspection Guide ..................................................... 221 
Appendix H: Consenting Process ..................................................................................... 223 
Appendix I: Ethical Clearance .......................................................................................... 225 
 
  
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LIST OF FIGURES 
Figure 1.1: Annual cholera cases reported in Ghana according to the Disease Surveillance 
department records (1980 to 2019) ....................................................................................... 7 
Figure 1.2: Conceptual framework of the factors influencing cholera recurrence ............... 8 
 
Figure 3.1: A Map showing the endemic and non-endemic areas in the Greater Accra 
Region ................................................................................................................................. 46 
Figure 3.2: Cholera ‘hotspots’ or endemic communities in the Greater Accra Region ...... 47 
Figure 3.3: Cholera non-endemic communities in the Greater Accra Region .................... 48 
Figure 3. 4: Screenshot of spatial pattern analysis .............................................................. 72 
Figure 3. 5: Screenshot of proximity analysis ..................................................................... 73 
 
Figure 4.1: Uniplex PCR products of O1rfb [200bp] amplified from environmental water 
samples and analyzed by 1.5% agarose gel electrophoresis. Lane M, is 50bp molecular 
base marker. Lane 9 is a positive control. Lane 15 is positive and corresponds to S/N 12 in 
table 4.18. Lanes 10 to 14 & 16 to 23 are negative. Lane 23 is the negative control. ...... 121 
Figure 4.2: Uniplex PCR products of ctxA [310bp] amplified from environmental water 
samples analyzed by 1.5% agarose gel electrophoresis. Lane M, is 50bp molecular base 
marker. Lane 1 is a positive control. Lanes 2 to 7 are negatives. Lane 8 is a negative 
control. .............................................................................................................................. 121 
Figure 4.3: Uniplex PCR products of ctxA [310bp] amplified from environmental water 
samples analyzed by 1.5% agarose gel electrophoresis. Lane M, is 50bp molecular base 
marker. Lane 9 is a positive control. Lane 10 to 23 are negatives. Lane 23 is a negative 
control. .............................................................................................................................. 121 
Figure 4.4: Choked gutters at Adabraka, Accra ................................................................ 125 
Figure 4.5: Choked gutters within households in Agbogbloshie, Accra .......................... 126 
Figure 4.6: Waste dump sites near a slum community at Agbogbloshie, Accra .............. 126 
Figure 4.7: Makeshift structures in a slum community along Odorna river in 
Agbogbloshie, Accra ......................................................................................................... 127 
Figure 4.8: Open defecation along the Odorna river near Agblogbloshie, Accra............. 127 
Figure 4.9: Waste dumpsite close to the Chemuna Lagoon at Chorkor, Accra ................ 128 
Figure 4.10: Garbage disposed into open drain with water pipelines in Chorkor, Accra . 128 
Figure 4.11: Waste dumpsite along a big gutter at Maamobi, Accra ................................ 129 
Figure 4.12: Waste overflow at Nungua market dumping site, Accra .............................. 129 
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Figure 4.13: A public toilet located in the compound of a household in Akpeshika in 
Nungua, Accra................................................................................................................... 130 
 
  
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LIST OF TABLES 
Table 3.1a: Operationalization of the Key study variables ................................................. 50 
Table 3.2: Population of households as of 2014 in the endemic communities ................... 54 
Table 3.3: Population of households as at 2018 in the non-endemic communities ............ 54 
Table 3.4: PCR primers used in the study ........................................................................... 66 
 
Table 4.1a: Socioeconomic characteristics of household respondents in cholera endemic 
and non-endemic communities – (N=906) .......................................................................... 80 
Table 4.2a: Water sources and handling factors among households in cholera endemic and 
non-endemic communities – (N=906) ................................................................................ 83 
Table 4.3a: Household food eating practices in the cholera endemic and non-endemic 
communities – (N=906) ...................................................................................................... 86 
Table 4.4a: Solid waste disposal practices among households in cholera endemic and non-
endemic communities – (N=906) ........................................................................................ 90 
Table 4. 5: Liquid waste disposal practices among households in cholera endemic and 
non-endemic communities – (N=906) ................................................................................ 94 
Table 4. 6: Environmental predisposing factors to cholera in endemic and non-endemic 
communities – (N=906) ...................................................................................................... 95 
Table 4. 7: Cholera infection in the households and neighbourhood – (N=906) ................ 97 
Table 4.8a: Associations between socioeconomic characteristics of respondent and cholera 
in the Greater Accra Region .............................................................................................. 100 
Table 4.9: Assessing the association between socioeconomic factors and cholera using a 
penalized multivariable logistic regression model ............................................................ 102 
Table 4.10a: Associations between household behavioural factors and cholera in the 
Greater Accra Region ........................................................................................................ 107 
Table 4.11: Assessing the association between behavioural factors and cholera using 
penalized multivariable logistic regression model ............................................................ 110 
Table 4.12: Mean log of bacterial counts in the dry and wet seasons across some selected 
background characteristics in Endemic communities ....................................................... 108 
Table 4.13: Mean log of bacterial counts in the dry and wet seasons across some selected 
background characteristics in non-endemic communities ................................................ 109 
Table 4.14: Assessing the differences in log bacterial count among household drinking 
water stored in vessels and from direct water sources in endemic communities .............. 111 
Table 4.15: Assessing the differences in log bacterial count among household drinking 
water stored in vessels and from direct water sources in non-endemic communities ...... 112 
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Table 4.16: Microorganisms isolated from the household drinking water samples collected 
in the endemic communities.............................................................................................. 113 
Table 4.17: Microorganisms isolated from the household drinking water samples collected 
in the non-endemic communities ...................................................................................... 115 
Table 4.18: Detection and Isolation of V. cholerae O1, O139, and non-O1/non-O139 from 
environmental water samples in cholera endemic and non-endemic communities during 
the wet season ................................................................................................................... 117 
Table 4.19: Detection and Isolation of V. cholerae O1, O139, and non-O1/non-O139 from 
environmental water samples in cholera endemic and non-endemic communities during 
the dry season .................................................................................................................... 119 
Table 4.20: Environmental assessment of the sanitation conditions in communities using 
Principal Components Analysis ........................................................................................ 124 
Table 4.21: Associations between environmental risk factors and cholera in Greater Accra 
Region ............................................................................................................................... 131 
Table 4.22: Assessment of environmental risk factors of cholera using a penalized 
multivariable logistic regression model ............................................................................ 133 
 
 
 
 
 
 
  
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LIST OF ABBREVIATIONS 
 
 
µl microlitres 
µm micron 
ABC Ablekuma Central 
ABW Ablekuma West 
ACC Accra Metropolitan 
ACP Accuracy Check Point 
ALN Ablekuma North 
AMA Accra Metropolitan Assembly 
ANOVA Analysis of Variance 
AOR Adjusted Odd Ratio 
APHA American Public Health Association 
API 20E Antigenic Profile Index for 20 Enterobacteriaceae 
ASH Ashiaman 
AYW Ayawaso West 
cAMP Cyclic adenosine 5’-monophosphate 
CFR Case Fatality Rate 
cfu Colony-Forming Unit 
CHPs Community-based Health Planning Services 
CLTS Community-Led Total Sanitation 
ctx Cholera toxin complex 
DHS Demographic and Health Survey 
EDTA Ethylenediaminetetraacetic acid 
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EMB Eosin Methylene Blue Agar 
FC Faecal Coliform Bacteria 
FCC Faecal Coliform Count 
GAR Greater Accra Region 
GHS Ghana Health Service 
GHS-ERC Ghana Health Service Ethical Review Committee 
GIS Geographic Information System 
GPS Geographic Positioning System 
GSS Ghana Statistical Service 
GTFCC Global Task Force on Cholera Control 
HIV Human Immunodeficiency Virus 
HlyA Haemolysin 
IHR International Health Regulations 
IND Indole 
KKT Korle Klottey 
KVIP Kumasi Ventilated Improved Pit latrine 
LDK La Dade Kotopon 
LEKMA Ledzokuku Krowor Municipal 
m metres 
MAC MacConkey Agar 
ml millilitre 
oC Degree Celsius 
OCV Oral Cholera Vaccines 
OKN Okaikoi North 
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OR Odds Ratio 
ORS Oral Rehydration Salt 
PBS Phosphate Buffered Saline 
PC Plate Count Agar 
PCA Principal Components Analysis 
PCR Polymerase Chain Reaction 
PI Principal Investigator 
RDTs Rapid Diagnosis Tests 
RDTs Rapid Diagnostic Tests 
RTA Repeat in toxin 
SDG Sustainable Development Goal 
SES Socioeconomic Status 
SSA  Sub Saharan Africa 
stn Heat-stable enterotoxin 
TC Total Coliform Bacteria 
TCBS Thiosulfate-Citrate-Bile-Sucrose Agar 
TCC Total Coliform Count 
tcp Toxin co-regulator 
TDA Tryptophan deaminase 
TSA Tryptone Soy Agar 
TSI Triple Sugar Iron Agar 
TTC Thermotolerant Coliform 
TTSS Type 3 Secretion System 
UNICEF United Nations Children Fund 
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USA United States of America 
USD United States Dollars 
VC Vibrio Count 
VIFs Variance inflation factors 
VP Acetoin 
VRB Violet Red Bile Agar 
WASH Water, Sanitation and Hygiene 
WC Water Closet 
WGB Weija Gbawe 
WHO World Health Organization 
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CHAPTER ONE 
INTRODUCTION 
1.1 Background 
1.1.1 Epidemiology 
Cholera is an acute diarrheal infection caused by the bacterium Vibrio cholerae, which 
causes disease exclusively in humans. The bacterium naturally inhabits aquatic water 
sources such as brackish riverine, estuarine, and coastal waters (Almagro-Moreno & 
Taylor, 2014). The survival and multiplication of the bacterium in the aquatic environment 
are influenced by both biotic and abiotic factors (de Magny et al., 2011; Lutz, Erken, 
Noorian, Sun, & McDougald, 2013).  The abiotic factors include;  pH, temperature, 
salinity, and organic nutrients in the water that helps the zooplankton and phytoplankton to 
bloom with increasing concentration of   V. cholerae O1 (Hug, Small, West, & Colwell, 
1984). This makes it possible to make predictions of a likely cholera outbreak by 
monitoring these abiotic factors in the aquatic environment  (Jutla et al., 2013).  
Nonetheless, cholera is difficult to eradicate because of the presence of the V. cholerae 
within and outside of the aquatic water environment but can be prevented by controlling 
exposure to the bacterium from the environment. 
There are over 200 serogroups of V. cholerae, with only the serogroups O1 and O139 
being responsible for cholera epidemics (Islam et al., 2013). The V. cholerae O1 is 
responsible for most of the cholera cases globally with O139 restricted to India and 
Bangladesh (Mukhopadhyay, Takeda, & Nair, 2014).  The V. cholerae O1 strains are 
classified based on biochemical characteristics into classical and El Tor.  The classical 
biotype was responsible for the sixth cholera pandemic, while the El Tor biotype is the 
causative agent of the current seventh pandemic (Hu et al., 2016).   
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Cholera is an ancient disease that has plagued every continent of the world in the past 
resulting in the deaths of hundreds and thousands of people, and remains a major public 
health problem in developing countries especially in parts of Asia, Africa, and Latin 
America where the basic amenities such as safe water and sanitation are still lacking or 
have been disrupted by war, civil conflicts or natural disasters such as earthquakes and 
floods (WHO, 2010, 2017b).   
Globally it is estimated that 1.3 to 4.0 million cholera cases and 21, 000 – 143, 000 deaths 
occur annually with the majority of these deaths occurring in Africa (Ali, Nelson, Lopez, 
& Sack, 2015). In the African continent, cholera cases are not equally distributed in all the 
regions. The incidences are higher in Sub-Saharan Africa (SSA) and in the Great Lake 
regions where frequent outbreaks continue to occur (Mengel, Delrieu, Heyerdahl, & 
Gessner, 2014). In the West African Coast (i.e stretching from Benin to Mauritania) from 
2009 to 2015, at least 54% of the reported cases were among populations living in three 
urban cities (i.e Accra, Freetown, and Conakry) (Moore et al., 2018). Of the reported 
cases, Ghana alone contributed 52.4% (51,333 out of 97,887 of all the suspected cases) 
within the same period as reported by Moore et al. (2018) in the WHO, Health 
Observatory Data Repository. The annual cholera cases in the country have also been 
estimated to be 41,732 with an average case fatality of 3.8% (Ali et al., 2015). The coastal 
regions (Greater Accra, Volta, Central, and Western) and Eastern region are mostly 
affected (Ghana Health Service, 2015). 
1.1.2 Clinical Presentation, diagnosis, and management 
Cholera is contracted by ingesting food or water contaminated with the toxigenic V. 
cholerae O1 or O139. On ingestion, the bacterium colonizes the small intestine and 
releases the cholera toxin which binds the epithelial cells and induces excessive secretion 
of water and electrolytes into the lumen of the small intestines, resulting in diarrhoea. 
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Although the infection is often mild or asymptomatic in most people, those infected may 
shed the bacteria in their faeces for 1 to 10 days (WHO, 2019).  In severe cases, patients 
present with profuse watery diarrhoea and vomiting. If left untreated, severe cases result in 
massive loss of bodily fluids and lead to dehydration, hypovolemic shock, and death.  The 
incubation period is short from few hours to 5 days after ingestion of  food or water 
contaminated with the bacterium and thus can kill rapidly (Azman, Rudolph, Cummings, 
& Lessler, 2013). Cholera can spread rapidly among children and adults (WHO, 2019).  
 
To diagnose quickly to prevent spread, a rapid diagnostic test (RDTs) is used. However, 
confirmation of the diagnosis is done by the isolation of the bacterium from the stool of 
infected persons (GTFCC, 2017). Treatment of cholera is usually by the replacement of 
the electrolytes loss, through rehydration fluid such as oral rehydration salt, and in severe 
cases by intravenous rehydration with the appropriate antibiotics to reduce the volume of 
diarrhoea and bacterial shedding in their stool (WHO, 2018a). Without prompt and 
appropriate management case-fatality rates can rise to 50% (GTFCC, 2017). 
 
1.1.3 Cholera Risk Factors 
Although cholera is transmitted through ingestion of food or water contaminated with 
toxigenic Vibrio cholerae O1 or O139, several demographics, socioeconomic, 
environmental, and climatic risk factors also promote the spread of the disease (Bwire et 
al., 2017; Leckebusch & Abdussalam, 2015; Stoltzfus et al., 2014). However, the specific 
mechanism and factors involved in its persistence and spread may vary from one area to 
another.   
Accra Metropolitan Assembly, Ledzokuku, and Krowo Municipal Assemblies in the 
Greater Accra Region are highly vulnerable to cholera because they are the most 
urbanized and highly commercialized assemblies in the region with traders and civil 
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workers across the country visiting on daily basis (Ghana Statistical Service, 2013). The 
capital city of the country, Accra which is located in the Accra Metropolis is also an 
important city as it links major cities within West Africa. There is therefore an influx of 
people every day to the city putting pressure on the existing sanitation facilities and thus 
increasing the risk of cholera. Accra is also a coastal town with fisher folks fishing along 
the West African Coast. The long days they spend and the unhygienic conditions they face 
while at sea also pose a risk to cholera (Khonje et al., 2012; Ohene-Adjei et al., 2017). 
There are also rivers passing through the city along with some crowded communities. 
These rivers are contaminated with human excreta and sewage due to a lack of access to 
toilet facilities in the households (Ghana Statistical Service, 2013). However, during times 
of water shortages, such polluted water bodies are used for household activities (Ghana 
Statistical Service, 2013).  
There are slums and squatter settlements within the city. The inhabitants in these 
settlements are less privileged and live in advert poverty including having poor access to 
portable water and sanitation (Accra Metropolitan Assembly and UN Habitat, 2011). Most 
of these slum communities are mostly located in low-lying areas that are prone to 
flooding. There is indiscriminate dumping of waste especially the non-biodegradable 
waste in the urban communities (Yoada, Chirawurah, & Adongo, 2014). This waste is 
washed by rain waters to choke the drains or gutters. Heavy rains may aggravate the 
situation with flood waters that may contaminate broken pipelines conveying water to the 
households and increases the risk of cholera. To control cholera in the Greater Accra 
Region, it is important to identify the cholera ‘hotspots’ and to investigate the specific 
risks to prevent recurrence of cholera.  
1.1.4 Spatial Distribution 
The potential risk factors of cholera have been well demonstrated by spatial epidemiology 
in many studies (Olanrewaju & Adepoju, 2017; Osei, Duker, & Stein, 2012; Osei & Stein, 
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2018).  Spatial epidemiology allows data to be collected to show the spatial distribution of 
disease incidences and their relationship with the risk factors. This was first demonstrated 
by John Snow during the London cholera epidemic in 1855. Snow was able to map the 
location of cholera cases which he traced to the water source (Tulchinsky, 2018). With the 
current advancement in technology, Geographical Information System (GIS) is used not 
only to ensure accurate mapping of locations but also to provide the application in 
studying the correlation between the identified risk (Ngwa et al., 2016; Olanrewaju & 
Adepoju, 2017; Osei & Stein, 2018). By mapping disease in geographical space, local 
authorities will be able to easily identify risk factors, their distribution, and spread in the 
area to plan interventions. 
1.2 Problem Statement 
In Ghana, cholera has become endemic since the first case was reported in 1970 with focal 
epidemics occurring every 4 to 6 years (Dzotsi, Odoom, Opare, & Davies-Teye, 2016; 
Ofori-Adjei & Koram, 2014) (Figure 1.1). From 1970 to 2011, Ghana cumulatively 
reported 128, 525 cholera cases and 6,400 deaths with a case fatality rate (CFR) of 4.98  
(Mengel et al., 2014). Despite the decline in the trend of cases from 1991 to 2010, large 
outbreaks occurred in 2011, 2012, and 2014 (Figure 1.1) (Ghana Disease Surveillance 
Department, 2016).  In 2014, the country recorded the worst outbreak after 30 years with 
over 28,000 cases and 240 deaths (Ghana Health Service, 2015). 
In recent years the epidemics have become more frequent and unpredictable with 
outbreaks occurring from 2010 to 2012 and 2014 to 2016. Also, complete lull periods in 
2013, 2017 to 2020 were experienced with no confirmed case reported despite the ongoing 
surveillance.  Most cholera epidemics in Ghana occur along the four coastal regions (i.e 
Western, Central, Volta, and Greater Accra) (Ghana Health Service, 2015). However, it is 
more prevalent in communities in the Greater Accra Region where there are crowded 
living conditions, poor sanitation, erratic clean water supply, inadequate food safety, and 
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hygiene practices (Mireku-Gyimah, Apanga, & Awoonor-Williams, 2018). Outbreaks 
often start in such communities and quickly spread with heavy rains and flooding to the 
rest of the metropolis, eventually reaching the other parts of the country by population 
movement (Ghana Disease Surveillance Department, 2016; UNICEF, 2013). Twelve (12) 
of these cholera endemic communities described as ‘cholera hotspots’ are located in the 
Accra Metropolis (Adabraka, Agbogbloshie, Agege, Chorkor, Dansoman, James Town, 
Kaneshie, Maamobi, Mamprobi, Nima), Ledzokuku Municipal Assembly (Teshie) and 
Krowor Municipal Assembly (Nungua).  
These communities have persistently reported the highest numbers of cases with high 
attack rates for the past four years (2011 to 2014) (Disease Surveillance Department, 
2015). Despite the persistence of cholera in these communities, the underlying factors 
behind its endemicity and spread remain unclear.  Although cholera transmission is 
through the consumption of food or water contaminated with toxigenic Vibrio cholerae O1 
or O139, several demographics, socioeconomic, environmental, and climatic risk factors 
are known to promote the spread of the disease (Bwire et al., 2017; Leckebusch & 
Abdussalam, 2015; Stoltzfus et al., 2014). 
This study assessed the behavioural, socioeconomic, bacteriological water quality, and 
environmental factors in the cholera endemic communities (Agbogbloshie , James Town, 
Adabraka, Kaneshie, Maamobi, Nima, Chorkor, Mamprobi, Agege, Dansoman, Teshie, 
Nungua) and non-endemic communities (Dawhenya North, Kofikope, Awhiam, Dawa, 
Addokope, Dogobom, Anyaman East, Adjumanikope, Adedetsekope, Angomya-Ada, 
Kophemm Kasseh, Asigbekope) to identify amendable risk factors to give up to date and 
relevant information for policy makers to appropriately plan and allocate resources to 
control the disease.
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35000
30000
25000
20000
15000
10000
5000
0
Year
 
Figure 1.1: Annual cholera cases reported in Ghana according to the Disease Surveillance department records (1980 to 2019) 
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Suspected Cholera Casess 
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1.3 Conceptual Framework 
 
 Behavioural factors 
1. Hygiene and 
 sanitation 
Socioeconomic practice  
factors 2. Food and water 
 
1. Age safety practices Vibrio 
2.  Sex cholerae in Cholera 
the 
3.  Religion environment 
4.  Marital status 
 
Environmental factors 
5. Ethnicity 
 1. Aquatic 
6. Occupation 
reservoir 
 
7. Educational 
2. Toilet facility 
 level 
 
8. Wealth status 3. Waste dumpsite 
 
9.  Income level 4. Market 
 
10. Household 5. Abattoir 
 
occupancy 
 Water sanitation 
  factors 
 
  1. Water source 
 2. Water quality 
 
 3. Water supply 
 network 
Figure 1.2: Conceptual framework of the factors influencing cholera recurrence   
  
 
Narrative: The framework explains the influence of environmental, water sanitation, 
socioeconomic and behavioural factors on cholera. The socioeconomic factors such as sex, 
marital status, ethnicity (beliefs), occupation (e.g traders, fishermen), educational level, 
income level or wealth status, and housing (crowdedness) may influence the individual 
hygiene practices including their food eating and water drinking habits which could lead to 
cholera. The behavioural factors also affect the web of environmental factors that 
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influence how sanitation is maintained and solid or liquid waste is disposed of which 
could lead to outbreaks once the cholera bacterium is exposed to the environment. The 
poor sanitary conditions from the environment may lead to the contamination of the water 
distribution network system and affect the quality of the treated water. This situation may 
be aggravated by heavy rains and flooding due to the poor drainage system, resulting in 
cholera outbreaks. The hygiene practices of households to ensuring safe drinking water 
may be compromised in the household through the type of storage containers, cups dipped 
into the storage water, or length of storage of the water (Agensi, Tibyangye, Tamale, 
Agwu, & Amongi, 2019; Gizachew, Admasie, Wegi, & Assefa, 2020). Behavioural 
factors involving food safety practices could also expose households to cholera. The 
proximity of environmental factors including an aquatic water reservoir which may be 
inhabited with crustaceans and other natural hosts of Vibrio cholerae may pose a risk once 
these water bodies contaminate the household drinking water sources (Almagro-Moreno & 
Taylor, 2014). The closeness of waste dump sites, abattoirs, and markets to the households 
may also expose households to flies and other rodents that could contaminate foods and 
influence cholera recurrence (Osei & Duker, 2008b).  
1.4 General Objectives 
To identify the risk factors associated with cholera outbreaks and map the environmental 
factors in the Greater Accra Region. 
1.4.1 Specific Objectives 
1. To determine the behavioural risk factors associated with cholera in the Greater 
Accra Region 
2. To assess the bacteriological quality of household drinking water and cholera risk 
in the Greater Accra Region 
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3. To determine the risk of toxigenic strains of V. cholerae O1 and O139 in the 
environmental water bodies. 
4. To assess the environmental sanitation risk factors for cholera in the Greater Accra 
Region 
5. To identify and map the significant environmental risk factors using Geographic 
Information System maps 
 
1.5 Justification 
Greater Accra Region has been the epicenter of most of the cholera outbreaks from where 
it spreads to other parts of the country (UNICEF, 2013). Therefore, preventing cholera in 
Greater Accra Region is likely to help control cholera in the country. Few studies have 
attempted to identify the risk factors that contributed to cholera persistence in the endemic 
communities in GAR. Most of the publications have been limited to determining risk 
factors during localized outbreaks with a focus on case management (Dzotsi et al., 2016; 
Ohene-Adjei et al., 2017). To control cholera in GAR, it is important to identify the 
specific risk factors in the cholera endemic communities that aid its persistence, 
transmission, and spread any time cholera occurs. Also, many of the proposed solutions to 
cholera epidemics are generic and poorly adapted to the local needs and specificities.  
Understanding these community risk factors will help target effective interventions to 
control and prevent future epidemics. 
The use of GIS technology to map the risk of cholera will help provide information on 
endemicity and guide the prevention and control of the disease in some communities. It 
will also help to provide information on the location where the intervention is most needed 
to ensure efficient use of resources. The spatial distribution of the cases could provide 
clues to the transmission and spread of the disease in the communities (Guo et al., 2013; 
Lessler, Salje, Grabowski, & Cummings, 2016). 
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This work will support the effort of the Global Task Force on Cholera Control (GTFCC) 
strategy in stopping cholera transmission in cholera ‘hotspots’ communities by 2030 
(Legros, 2018).  This study is important as it will provide current knowledge on the 
potential risks factors aiding cholera persistence and the results will help influence policy 
makers to identify measures to prevent cholera epidemics in GAR. 
 
 
 
 
 
 
 
 
  
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CHAPTER TWO 
LITERATURE REVIEW 
2.1 History of Cholera 
Cholera has existed since the ancient times of Hippocrates and Galen when the disease 
was described as sporadic diarrhoea. Many other hints indicated that cholera had occurred 
since antiquity in the plains of the Ganges River. However, it was not until the 19th 
Century that John Snow demonstrated an association between cholera transmission and 
contaminated water in the Soho district of London cholera outbreak (Tulchinsky, 2018). 
This event disabused the highly upheld ‘miasma theory’ in the early 1880s that suggested 
the disease to be caused by ‘bad air’ or ‘bad smell’. About the same time, an Italian 
anatomist Filippo Pacini isolated the bacterium from the intestinal contents of the corpse 
of cholera patients in Florence, Italy but his work was unnoticed. It was not until 1884, 
that Robert Kock identified the pathogen as Vibrio cholerae O1 from a pure culture during 
an outbreak in Egypt.  
So far, seven pandemics have occurred globally. The first pandemic started in 1817, 
followed by six subsequent pandemics in 1829, 1852, 1863, 1881, 1889, and 1961 (Azizi 
& Azizi, 2010). The first six pandemics originated from Ganges in Bangladesh, thus was 
nicknamed  ‘homeland of cholera’ and the seventh pandemic is suggested to have begun in 
Sulawesi, Indonesia in 1961 (WHO, 2019). It then spread to other continents including 
Africa, Europe and finally reached Latin America in 1991 which has been free from 
cholera for more than a century, resulting in a large number of cases and deaths.  
The seventh cholera pandemic has continued to ravage the world especially in countries 
with poor access to safe water and sanitation or disrupted by war or civil conflicts or 
natural disasters such as earthquakes, tsunamis, volcanic eruptions, landslides, and floods 
(WHO, 2019).  Currently, the disease affects about 3 to 5 million people globally with an 
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annual estimated death of 100,000 to 120,000 with recent large outbreaks in Haiti, Yemen, 
and Sub-Saharan Africa (Ali et al., 2015; Tulchinsky, 2018). 
2.2 Cholera in Africa 
Five cholera pandemics have so far affected Africa in the 19th century. These occurred 
particularly in North Africa where the epidemic killed several thousands of people, 
especially Egypt. The epidemics that occurred at the time were associated with pilgrims 
who returned from Hajj in Mecca. However, it was not until during the seventh pandemic 
that Africa bore the major burden of cholera. The seventh pandemic started in 1970 in 
West Africa, with Guinean students travelling to Conakry where there was an ongoing 
epidemic. The epidemic then spread rapidly from Guinea to most parts of the continent 
where it has become endemic  (Echenberg, 2011).  
Since then, cholera incidence has continued to increase with high Case Fatality Rates 
(CFRs) (Mengel et al., 2014). The majority of the reported cholera cases occur in the 
Central African Great Lakes region and Sub-Saharan African countries (Gaffga, Tauxe, & 
Mintz, 2007; Nkoko et al., 2011). From 1970 to 2011, the African countries alone 
contributed 3,221,000 cases which constituted 46% of the global cases (Mengel et al., 
2014). In 2017, large outbreaks occurred in the Democratic Republic of the Congo (DRC), 
Nigeria, Ethiopia, South Sudan, Sudan, Somalia, and Zambia (Legros, 2018). The true 
burden, however, could be more than reported by WHO because of the inadequate 
laboratory and surveillance reporting systems notwithstanding the countries' fear of 
restriction on travel and trade if known with cholera (Ali et al., 2012; Zuckerman, Rombo, 
& Fisch, 2007). The cholera epidemic in Africa has largely been associated with 
migration, socioeconomic, climatic, environmental factors, and political instability (Ajayi 
& Smith, 2019). 
2.3 Cholera in Ghana 
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The cholera epidemic started in Ghana during the seventh pandemic. The first case was a 
Togolese native who died on arrival at the airport in Accra on the first of September, 1970, 
while in transit to Conakry, Guinea (Pobee, 1970). The case however did not start an 
outbreak. Ghana’s first outbreak was imported by Ghanaian fishermen who have been 
fishing along the Coast of Togo, Liberia, and Guinea (Ofori-Adjei & Koram, 2014). One 
of the fishermen died and the corpse was ‘smuggled’ into the country by the relatives for 
the burial rituals despite the sanitary cordon at the border (Ofori-Adjei & Koram, 2014).  
The disease subsequently spread to other coastal fishing communities. The two worst-hit 
fishing communities were Akplabanya (in the then Ada District) and Nyanyano near 
Kasoa (Ofori-Adjei & Koram, 2014). The disease further spread to start outbreaks in the 
Ashanti region (Ashitey, 1994).  
Since then cholera has become endemic with focal outbreaks occurring every 4 to 6 years 
(Dzotsi et al., 2016; Ofori-Adjei & Koram, 2014).  Between 1970 and 2011, Ghana 
reported cumulatively 128, 525 cases and 6,400 deaths with a CFR of 4.98 to WHO 
(Mengel et al., 2014). Although there was a decline in the trend of cases from 1990 to 
2010, large outbreaks occurred in 2011, 2012, and 2014 (Ghana Disease Surveillance 
Department, 2016).  In 2014, Ghana recorded over 28,000 cases with 240 deaths, the worst 
after 30 years, and affected all the then ten regions, with 72% of the cases occurring in the 
GAR (Ghana Health Service, 2015).  The GAR has thus become cholera-endemic but the 
underlying mechanism behind its endemicity and spread in some communities remains 
unclear. 
2.3 The Pathogen 
Cholera is caused by a bacterium belonging to the genus Vibrio which is described 
typically as small, curved rod-shaped with or without flagella which aid in motility.  
Vibrio species are facultative anaerobes with most species being oxidase-positive. There 
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are many Vibrio species but the pathogenic species that are transmitted via water or 
seafood include; V. cholerae, V. parahaemolyticus, V. vulnificus, V. alginolyticus, V. 
fluvialis, V. tubiashi (Cabral, 2010).  Vibrio species are primarily aquatic organisms and 
the distribution of their species is dependent on the sodium concentration and water 
temperature (Kokashvili et al., 2015). 
Vibrio cholerae can survive in alkaline conditions of up to pH 10 and are inhibited by 
acidic conditions (pH 6 or lower). They are halophilic organisms and require sodium 
chloride for optimum growth thus naturally exist as free living in the estuarine and marine 
environment or coastal waters (Almagro-Moreno & Taylor, 2014). It has also been found 
to be associated with algae, shellfish, chironomid egg masses, fish, waterfowl, amoebae, 
and mostly copepods in its aquatic environment  (Almagro-Moreno & Taylor, 2014; 
Senderovich, Izhaki, & Halpern, 2010). The bacterium can also survive in fresh water 
sources such as lakes, ponds, rivers, and water storage devices at home (Abia, Ubomba-
Jaswa, & Momba, 2017; Yirenya-Tawiah, Darkwa, & Dzodzomenyo, 2018). In a non-
aquatic environment V. cholerae can survive in refuse dumps, fruits, fresh vegetables, 
meat and even in cooked foods that is cold (Mrityunjoy et al., 2013). 
There are over 200 serogroups of V. cholerae that have been classified based on the 
presence of the somatic O antigen. However, the most important serogroups known to 
cause disease and epidemics are serogroups O1 and O139 (Cho, Yi, Lee, Kim, & Chun, 
2010; Islam et al., 2013).  Vibrio cholerae O1 has further been classified based on a 
variety of phenotypic markers such as; susceptibility to polymycin B, Voges-Proskauer 
test, chicken erythrocyte agglutination, and phage IV susceptibility into classical and El 
Tor biotypes (Mandal, Mandal, & Pal, 2011). The El Tor biotype differs by its ability to 
survive better in the human host and environment than the classical biotype. However, the 
classical biotype causes more severe disease than the El Tor biotype (Mohammadi, 
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Bakhshi, & Boustanshenas, 2016). At the genomic level, not much difference is observed 
between the classical and El Tor biotype as a complete sequence of their genome indicates 
that only 29 genes are missing between classical that cause the first six pandemics 
compared to El Tor that is responsible for the ongoing seventh pandemic (Beyhan, 
Tischler, Camilli, & Yildiz, 2006; Hu et al., 2016).  Nonetheless, the presence of a 
particular biotype does not alter the management of a case but present epidemiologist with 
knowledge of the source and spread especially when found in areas where it has not been 
previously reported. 
Vibrio cholerae O1  has been responsible for the epidemics globally until late 1992 when 
V. cholerae O139 was first discovered and found to also cause epidemics in Bangladesh 
and India  (WHO, 2019). This new strain was demonstrated to be genetically different 
from El Tor biotype by the replacement of the biosynthetic genes with O139 biosynthetic 
genes (WHO, 2017d). The V. cholerae O139 has since been confined to causing epidemics 
in Asia (Mukhopadhyay et al., 2014). 
The V. cholerae O1 strains have two serotypes, Ogawa and Inaba which differ by the 
antigens present in the bacteria cell wall.  The Ogawa serotype has been found to possess 
antigens A and B whiles the Inaba contains antigens A and C.  A third serotype Hikojima 
which is rare and unstable has antigens A, B, and C (Gustafsson & Holme, 1985). It is 
detected during the transition when there is a switching of Ogawa serotype to Inaba when 
the human population acquires immunity against the Ogawa serotype (M. T. Alam et al., 
2016; Khan et al., 2010).  However, immunity against Inaba is suggested to offer longer 
protection than Ogawa serotype infection (Longini Jr et al., 2002). Knowledge of these V. 
cholerae O1 serotypes have been used to develop the live oral vaccine candidates to 
protect against cholera (Karlsson et al., 2014; Sit et al., 2019). 
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Vibrio cholerae O1 and O139 serogroups that cause epidemics produce cholera toxin 
complex (ctx) and toxin co-regulated pilus (tcp), coded by ctx A and tcp A genes 
respectively (Danso et al., 2020). The ctx is responsible for the secretory diarrhoea whiles 
the tcp is involved in intestinal colonization.  
The other serogroups are known collectively as V. cholerae non-O1/non-O139 also 
referred to as non-agglutinating Vibrios. These do not agglutinate with antisera specific to 
their O somatic antigen, but may cause sporadic diarrhoea and localized outbreaks. They 
are mostly found in aquatic environmental sources and lack the virulence gene (ctx and 
tcp) (Arteaga et al., 2020). However, they have other virulence factors such as; heat-stable 
enterotoxin (stn), haemolysin (HlyA), repeat in toxin (RTX), type 3 secretion systems 
(TTSS), and type 6 secretion system (T6SS) (Arteaga et al., 2020; Dutta et al., 2013).  
These V. cholerae non-O1/non-O139 are however, thought to constitute genomic islands 
of potential virulence genes that may contribute to the evolution of pathogenic strains 
(Arteaga et al., 2020; Dutta et al., 2013; Li et al., 2014). Further surveillance and 
investigation are required to understand the potential pathogenicity of these environmental 
strains. 
2.4 Infections and Symptoms 
Cholera is contracted by ingesting food or water contaminated with pathogenic V. 
cholerae O1 or O139 (WHO, 2019). Once the bacterium reaches the gastric acid barrier of 
the stomach, the majority are destroyed, but a few make their way into the small intestines 
where they re-establish their population. More than 104 of the bacterium are required to 
develop symptoms of cholera in a susceptible individual (Nelson, Harris, Morris, 
Calderwood, & Camilli, 2009). The incubation period is dependent upon the population of 
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the bacteria that colonize the small intestine and varies from 12 hours to 5 days, typically 
taking two days before causing symptoms (Spagnuolo, DiRita, & Kirschner, 2011; WHO, 
2019). 
In the small intestine, the bacteria adhere to the crypts of the intestine using a tcp to keep 
them from being flushed out (Spagnuolo et al., 2011). The bacterium releases the ctx, 
which is composed of an enzymatic (A) subunit and 5 binding (B) subunits. The B 
subunits bind to the surface of intestinal mucosal cells, allowing the A subunit to enter the 
cell. Once inside the cell, the A subunit stimulates cyclic adenosine 5′-monophosphate 
(cAMP) production.  This causes secretion of water and electrolytes into the lumen of the 
small intestines and causes the severe diarrhoea. The amount of water losses varies 
between individuals, depending on the infecting V. cholerae strain and the amount of 
bacterium that colonizes the small intestine (WHO, 2017d). Within an hour a patient can 
lose up to a litre of fluids.   
The disease is characterized by other symptoms including muscle cramps, sunken eyes, 
and cheeks, a scaphoid abdomen, rapid heart rate, low blood pressure, irritability, and loss 
of skin turgor. If early treatment is not sought, severe volume fluid depletion may result in 
metabolic acidosis which may lead to circulatory collapse and death (WHO, 2017d). In 
children, it may in addition present with drowsiness, fever, convolutions, and even a coma. 
The ‘rice water’ stool produced from a patient carries between 1010 and 1012 Vibrio per 
litre (Nelson et al., 2009).  
About 75% of people infected with the V. cholerae are asymptomatic, although the 
bacterium is present in their faeces for 7 to 14 days after infection and can be shed into the 
environment. Of the 25% of the patients who become symptomatic, 10 to 20% may 
experience severe disease (WHO, 2017d). Such individuals may shed the Vibrio before the 
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onset of the disease and will continue to shed the Vibrio for up to 14 days. A few people 
may habour the bacteria indefinitely with no symptoms (Adagbada, Adesida, Nwaokorie, 
Niemogha, & Coker, 2012). The distribution of symptomatic patients and asymptomatic 
carriers in a community can influence cholera transmission once the bacteria get into the 
environment. 
2.5 Transmission of Cholera 
Cholera transmission is through primary and secondary transmission routes. The primary 
transmission occurs through exposure to an environmental reservoir of V. cholerae or 
contaminated water source with the bacterium regardless of previously infected persons or 
faecal contamination (Ruiz Moreno, 2009). The primary transmission is triggered by 
climatic factors that make the flora and fauna in the aquatic environment bloom enabling 
the growth of the bacterium (Lutz et al., 2013; Mavian et al., 2020). Other studies have 
also suggested that the non-toxigenic strains of V. cholerae may evolve to become 
toxigenic in the aquatic ecosystem (Islam, Zaman, Islam, Ahmed, & Clemens, 2020; 
Mavian et al., 2020). Thus, making the aquatic environment an important source of 
cholera transmission. 
Secondary transmission route on the other hand occurs through exposure to faecally 
contaminated water sources, food, or direct from person-to-person within households or at 
the hospital (Ruiz Moreno, 2009; Sugimoto et al., 2014; You et al., 2013).  This mode of 
transmission plays a major role in cholera spread because it involves multiple factors. The 
faecal-oral transmission is increased by the level of contamination of water or food which 
can be influenced by other local factors such as socioeconomic, demographic as well as 
sanitation (WHO, 2019). To control cholera epidemics both transmission routes need to be 
taken into consideration for effective control of epidemics. 
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2.6 Diagnosis and Detection of Cholera 
A review of clinical features of a suspected case of cholera may help detect cholera 
patients. However, it is important to distinguish between cholera cases and other acute 
watery diarrhoea cases. This is important for quick management of the cases to prevent the 
disease from rapidly spreading. Confirmation of cholera in the laboratory is by the 
isolation and identification of V. cholerae  O1 or O139 from stool specimen of suspected 
patient or by detection with Polymerase Chain Reaction (PCR)   (Dick, Guillerm, Moussy, 
& Chaignat, 2012; WHO, 2015).  
This notwithstanding, many hospital facilities lack laboratories with the capacity to 
perform a culture or PCR diagnostic technique to confirm the clinical diagnosis. As such 
refer specimens of suspected cases to laboratory facilities where cultures or PCR 
identification can be done. However, there are challenges with the timely and safe referral 
of the specimens. This has led to the development of a rapid diagnostic test kit (RDT) to 
quickly test and alert public health authorities for early response to control an outbreak 
(Mwaba et al., 2018).  
The use of RDTs, however, is limited because they cannot grow an isolate to perform 
antimicrobial susceptibility testing and sub-typing of strains. Other RDTs are suboptimal 
in terms of test kit sensitivity and specificity as published by Global Task Force on 
Cholera Control (WHO, 2017a). It is therefore recommended that positive RDT result are 
confirmed with culture or PCR technique before an outbreak is declared (WHO, 2018b). 
Where laboratory diagnostic testing is not available WHO recommends the use of case 
definitions to ascertain that all patients considered as cholera cases have the same disease 
(WHO, 2017a). For instance, the suspected case definition in an area where cholera is not 
known to be present is; ‘any patient aged 2 years or more who develops severe 
dehydration or dies from acute watery diarrhoea’. Also, in an area where there is a cholera 
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epidemic a case is, ‘any patient aged 2 years or more who develops acute watery 
diarrhoea, with or without vomiting’. A confirmed case on the other hand is defined as; ‘a 
case of cholera when V. cholerae O1 or O139 is confirmed by culture or PCR and, in 
countries where cholera is not present or has been eliminated, the V. cholerae O1 or O139 
strain is demonstrated to be toxigenic (GTFCC, 2017). Cholera diagnosis is therefore 
important for ensuring an effective surveillance system and for the control of cholera 
outbreaks. 
2.7 Treatment and Prevention of Cholera 
2.7.1 Treatment 
The first treatment for cholera patients is prompt rehydration through the administration of 
oral rehydration salt (ORS) (Munos, Walker, & Black, 2010). The WHO/UNICEF ORS 
standard sachets have been found to adequately treat more than 80% of patients. In severe 
cases, intravenous rehydration is administered, preferably Ringer lactates instead of 
isotonic sodium chloride. This is because the latter has the effect of correcting metabolic 
acidosis as well (WHO, 2008).  
In addition, an appropriate antibiotic should be given in severe cases. The essence of 
giving antibiotics is to reduce the duration of diarrhoea and minimize bacterial shedding in 
the stool of cases (WHO, 2018b). Various antibiotics have been proposed for cholera 
therapy including; furazolidone, erythromycin, ampicillin, tetracycline, ciprofloxacin, and 
azithromycin (Khan, Saha, Ahmed, Salam, & Bennish, 2015; Leibovici-Weissman et al., 
2014; Pietroni, 2020). However, the choice of antibiotic treatment will vary depending on 
the antibiotic susceptibility pattern of the circulating V. cholerae strain (Kitaoka, Miyata, 
Unterweger, & Pukatzki, 2011; Pietroni, 2020). The continuous monitoring of antibiotic 
resistance patterns of epidemic strains is important for cholera control strategies.  In 
children up to five years, supplementation with zinc is recommended to reduce the 
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duration of diarrhoea as well as the number of diarrhoea episodes. Early reporting of 
cholera cases to the health facility with adequate management can reduce the CFR to less 
than 1%.  Case fatality rates exceeding 1% usually reflect inadequate case management or 
delay in initiating treatment (GTFCC, 2017; Pietroni, 2020). 
2.7.2 Prevention 
Natural protection against cholera is acquired after clinical cholera and the protection can 
be long lasting especially in endemic areas where there is the chance of re-exposures 
(Weil et al., 2012). This infection-derived immunity approach led to the development of 
cholera vaccines to produce immunity with the administration of attenuated strains of V. 
cholerae. Currently, three oral cholera vaccines (OCV) Dukoral, Shanchol, and Euvichol 
have been pre-qualified by WHO and are available. These OCVs have some advantages 
and disadvantages. The Dukoral vaccine requires the administration of a buffer solution 
and is licensed only for patients aged two years and above (WHO, 2017a). Two doses of 
Dukoral are required to confer longer protection (WHO, 2017a). It requires refrigeration at 
2 – 8oC and has a shelf-life of 3 years and one month at 37oC  (WHO, 2017a). From 1997 
to 2014, a review of vaccination campaigns showed that it cost between USD 0.53 to USD 
3.66 per fully immunized person (Martin et al., 2014). Shanchol is administered in two 
liquid doses two weeks apart.  A booster dose is also required after 2 years. In terms of 
cost per fully immunized person, it ranges from USD 1.13 to USD 3.99 from 2011 to 2014 
(Martin et al., 2014). A third vaccine Euvichol which is comparable to Shanchol was 
licensed and prequalified in 2016 by WHO but is not widely used  (Baik et al., 2015). 
Shanchol and Euvichol vaccines can be stored at 2 – 8oC and have a shelf life of 2 years.  
 
Despite the protection, OCV can give, concerns are being raised regarding the vaccines 
because of the cost, the feasibility of organizing large vaccination campaigns, community 
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opinion of oral vaccines, and delay in receiving vaccines (Chaignat, 2008). As such the 
mainstay of cholera prevention remains; improving on the provision of clean water, 
providing sanitation facilities, and improving on personal hygiene practices as well as 
enforcement of standard sanitation laws. These were the measures adapted by most of the 
developed countries such as Europe and the USA that eradicated cholera. World Health 
Organization, recommends OCV to be used during outbreaks to quickly contain the spread 
of the disease. 
2.8 Cholera Risk Factors Influencing Transmission 
2.8.1 Host Genetic factors 
Host immunity plays a role in the susceptibility of an individual to cholera. It determines 
whether an individual will have severe and life-threatening diarrhoea or mild to no 
apparent symptoms. Thus, diseases that cause immune suppression may predispose people 
to cholera. Mushayabasa and Bhunu (2012) used a mathematical model to demonstrate an 
increased association between human immunodeficiency virus (HIV) infection and cholera 
risk in cholera endemic communities. A case-control study conducted in cholera endemic 
communities in Mozambique similarly found an association between HIV infection and 
cholera (Semá Baltazar et al., 2017). Richterman, Cheung, et al. (2018) in their study 
among self-reported HIV patients in rural Haiti also found an association between HIV 
infection and cholera. 
Another host-related factor is the differences in gastric acid level and cholera infection. In 
a low gastric acid condition, a lower infectious dose of V. cholerae is required to cause an 
infection. This was demonstrated in an experimental trial where bicarbonate and live V. 
cholerae were given to volunteers, and the infective dose was lowered from 108 to 104 
organisms (Hornick et al., 1971). A higher risk of cholera is also found among patients 
who have had gastric surgery. This is shown in a study in Italy, where index cases were 
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5.8 times more likely to have had a history of gastric surgery (Baine et al., 1974). 
Helicobacter pylori infection is common in Africa and causes gastric hypoacidity 
(Adagbada et al., 2012). Gastric hypoacidity increases the risk of cholera infection and 
may be the reason cholera is prevalent in Africa (Smith, Fowora, & Pellicano, 2019). 
Blood group is one of the genetic factors that predispose to diseases, including infectious 
diseases. The expression of the ABO and Lewis blood group types has been shown to be 
associated with a cholera risk. Individuals with blood group O for instance have a lower 
risk of initial colonization on exposure to V. cholerae infection, although on colonization 
have a higher risk of more severe disease than the other blood groups (A&B) (Harris et al., 
2005). It is suggested that the cholera toxin exerts a more potent effect on cells expressing 
blood group type O-associated glycan than blood group A, thus making blood group O 
individuals more susceptible (Kuhlmann et al., 2016). Also, individuals expressing the 
Lewis blood group Le (a+b-) are more susceptible to symptomatic cholera than those with 
Le (a-b+) (Arifuzzaman et al., 2011). In Ghana, no epidemiological studies have been 
conducted to relate blood group type to cholera risk although the majority of the populace 
belong to blood group O. 
2.8.2 Demographic Factors 
The host-related risk factors of cholera, such as age and sex have varyingly been reported 
by many researchers.  Concerning age, some studies have reported younger children to 
have a higher risk of cholera than adults (Cummings et al., 2012; Saha et al., 2017), whiles 
others have suggested the risk to be higher among adults (Colombara, Faruque, Cowgill, 
& Mayer, 2014; Rosewell et al., 2012). Although cholera can affect all age groups equally, 
the variation in the risk by age may reflect the natural immunity of the population. For 
instance, infants could be protected through passive immunity from the mother's breast 
milk (Qureshi et al., 2006). Also, previous exposure to cholera by adults living in endemic 
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communities may decrease the risk of illness in the adult population than younger children 
without any episode of exposure as reported in Kenya (Mutonga et al., 2013). Naturally 
acquired immunity also plays a role in cholera endemic areas. A Mozambican study 
showed that cholera infection rarely occurred in the same affected districts for at least 
three years (Gujral et al., 2013). In Ghana, the lull periods observed in 2013, and from 
2017 to 2020 when no cholera outbreaks occurred may be attributed to the immunity 
acquired by the population from the previous outbreaks than an improvement of the 
sanitation situation. 
With regards to sex-related risk of cholera, some studies in Uganda and Bangladesh have 
attributed a high risk to adult women and school-age girls compared to their male 
counterparts (Cummings et al., 2012; Saha et al., 2017). In contrast, many outbreak 
investigations in districts in the Greater Accra and Brong Ahafo observed a higher risk 
among males than females (Dzotsi et al., 2016; Noora et al., 2017; Ohene-Adjei et al., 
2017). This also agrees with the findings of Opare et al. (2012) during an outbreak 
investigation in the East Akim Municipality. Although both sexes were equally at risk of 
cholera, the variation could be attributed to socially ascribed roles in the specific 
environment. For instance, in some jurisdictions, women or young girls may be more 
associated with domestic chores and involved in the care of patients as well as handling 
and preparation of family meals than males. In other situations, adult males may be more 
vulnerable because of their engagement in eating outside foods. 
2.8.3 Socioeconomic factors 
Several studies have explored the relationship between cholera incidence and the 
household income level and socioeconomic status. Rahman et al. (2009) in a multivariate 
analysis among cholera-infected individuals in Matlab, found a lower socioeconomic 
status (SES) to be a significant predictor of hospitalization with cholera. A similar 
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multivariate analysis conducted among children in Bangladesh demonstrated children 
from households with lower incomes have an increased risk of cholera compared to 
households with higher incomes (Colombara, Cowgill, & Faruque, 2013).  Root, Rodd, 
Yunus, and Emch (2013) also explored the impact of SES and observed that higher SES 
reduces cholera risk but could not explain the mechanisms, however, suggested a 
combination of factors including education, hygiene knowledge and practices, better 
housing quality and access to clean water might have accounted for the difference.  Other 
studies, however, did not find any association between SES or income level and cholera 
risk (Dureab et al., 2019; Saha et al., 2017; Stoltzfus et al., 2014). 
In terms of population density and cholera, Saha and colleagues found a significantly 
higher risk for cholera in densely populated areas (Saha et al., 2017). Such areas are often 
located in urban slums where there is usually overcrowding and the people live in poor 
sanitary conditions (Osei & Duker, 2008a; Penrose, de Castro, Werema, & Ryan, 2010). 
The role of education has been explored in many case-control studies where multivariate 
analyses were used to establish the associations between cholera and the educational status 
of victims. The findings of most of the studies suggested that educational level above 
secondary school or nine years of education was protective against cholera (Colombara et 
al., 2013; Nguyen et al., 2017; Nsagha et al., 2015). This may be because people at a 
certain level of education would understand the basic preventive measures to avoid 
contracting cholera. 
In terms of occupation, highly mobile populations such as traders and fishermen who 
travel by water, land, and air from a cholera endemic area may contract the infection and 
transfer to another geographical location (Manga et al., 2008; Mari et al., 2012; Piarroux 
& Faucher, 2012). This is particularly important because there is no trade restriction across 
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countries under the international health regulations (IHRs) for cholera. Such susceptible 
people may become infected whiles travelling and transmit the disease to their home 
communities to start an outbreak. For example, the index case of the Guinean 2012 
cholera epidemic was caused by a fisherman who travelled from Sierra Leone, where an 
epidemic was ongoing at the time (Rebaudet et al., 2014). The cholera epidemics in Ghana 
have been speculated by Sandra and colleagues to occur as a result of the mobile 
population (Moore et al., 2018). This is further emphasized by a recent report of two 
confirmed imported cases of cholera from Nigeria, who were on transit to Kumasi but 
developed symptoms whiles on the journey and were admitted at the Ketu South 
Municipal Hospital (Ghana Health Service, 2018). If not for the timely intervention of the 
Ketu South Municipal Health Directorate this could have started an outbreak once the 
bacterium got into the environment. 
2.8.4 Water-related risk to cholera 
2.8.4.1 Water Source, Transportation and Handling 
Issues surrounding the availability and usage of water have always been a focus of cholera 
epidemics. The use of unimproved water sources (e.g lakes, rivers, estuaries, irrigation 
canals, ponds or dams, shallow wells, street-vended sachet water) are significantly 
associated with cholera, while drinking from improved or treated sources are protective 
(Richterman et al., 2018). In the GAR, the main sources of drinking water are piped-borne 
(in-house, outdoor, public tap) and sachet water (Ghana Statistical Service, Ghana Health 
Service, & ICF International, 2015). However, because of the rapid urbanization of Accra, 
there is an inadequate supply of piped water as demand far exceeds the water production 
and many residents have increasingly relied on sachet water as their source of drinking 
water. Others prefer the sachet or bottled water because they have the belief that piped 
water is contaminated. According to Semey, Dotse-Gborgbortsi, Dzodzomenyo, and 
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Wright (2020) sachet water is usually packaged from boreholes or treated water sources 
and therefore safer. However, their study did not rule out the possibility of contamination 
by factory workers during production. In furtherance to this, Dzodzomenyo et al. (2018) 
observed that a substantial proportion of sachet water sold was not formally registered and 
the microbial quality of such unlicensed water was high.   An indication that the shift to 
drinking sachet water may not necessarily be protective against cholera or diarrhoea 
diseases. Some previous investigations of the water network during the 2012 cholera 
outbreak in the Osu Klottey Sub Metropolis showed that drinking community pipe borne 
water was associated with contracting cholera (Davie-Teye et al., 2014). Another  study 
also revealed unsuitable residual chlorine levels and the regular presence of faecal 
coliform in the Accra network water even during the dry season (Karikari & Ampofo, 
2013). These studies suggest that residents in Accra could be exposed to network water 
contamination either directly via the tap or indirectly via the consumption of sachet water. 
Water contamination may also occur at the point-of-use, as a result of dipping of hands 
into storage vessels (Daniel, Diener, van de Vossenberg, Bhatta, & Marks, 2020; 
Gizachew et al., 2020). Other researchers have implicated distance from water source and 
time spent in water collection to the household as a factor for drinking water 
contamination (Boateng, Tia-Adjei, & Adams, 2013; Colombara et al., 2013; Nygren et 
al., 2016). Thus, testing water source alone is not enough to determine the likely source of 
contamination but testing the quality of the stored water as well. In other cases, the 
contamination may result from vessels used in water storage as reported in a systematic 
review where household risk factors of cholera showed a significant association between 
using water stored in a bucket or open container and cholera (Richterman et al., 2018). In a 
related study V. cholerae O1 strains were isolated from some household drinking water 
storage containers in some communities in the Accra Metropolis before the 2014 major 
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cholera outbreak (Yirenya-Tawiah, Darkwa, & Dzodzomenyo, 2018). This indicates 
household water storage contamination; however, they could not confirm whether the 
contamination was from the source or the household or both and could not also confirm if 
the V. cholerae isolated were of the toxigenic strains. This current study investigated the 
microbial quality of household drinking water from the source and storage containers in 
cholera endemic and non-endemic communities. 
2.8.4.2 Water Treatment 
Water treatment is essential in preventing contamination with waterborne pathogens. Most 
household drinking water is contaminated from source, during transportation, or storage. 
This is evidenced in a study by Clasen and Bastable (2003) who found safe water to be 
faecally contaminated during the collection and storage at home. A similar study by 
Lavanya and Ravichandran (2013) indicated that household water storage was more 
contaminated with E. coli and total coliform than the piped water. The study also revealed 
that there was no evidence of residual chlorine, although the over tanks and wells were 
chlorinated before pumping to households (Lavanya & Ravichandran, 2013). These 
findings raise the importance of water treatment at the point of consumption.  Although 
there has been an improvement with access to portable water (piped water, bottled and 
sachet water) from 37.3% in 2013 to 44.3% in 2017 as reported in the Ghana Living 
Standard Survey data (Government of Ghana, 2019). The quality of household water 
remains in doubt. Thus, for Ghana to achieve the Sustainable Development Goal (SDG) 6, 
the country must ensure that the population who do not yet have access to portable water  
practice effective household water treatment  (WHO, 2012). 
Various methods of household treatment including; sedimentation, filtration, disinfection, 
and safe storage have been recommended by WHO/UNICEF (WHO, 2013).  It has been 
revealed in some systematic reviews that household water treatment interventions reduce 
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the burden of cholera and the risk of transmission by improving household stored water 
(Lantagne & Yates, 2018; Wolfe, 2018). The current study determined the contamination 
levels of household drinking water and established the water treatment attitude at homes. 
2.8.4.3 Water Quality Analysis 
Water is important for life and should be made available in supply, however, its health 
benefits are dependent on the quality (WHO, 2017c). The water quality may be affected 
by the presence of microorganisms such as bacteria, viruses, or parasites (helminths and 
protozoa). These microorganisms may occur naturally in the environment or introduced 
through human activities  (WHO, 2017c). If the drinking water becomes faecally 
contaminated, that will pose a great risk for diarrhoea diseases including cholera (WHO, 
2017c). The drinking water contamination may occur as a result of inadequate treatment 
from the source or in the water distribution network (WHO, 2014). This may lead to health 
hazards resulting in large-scale contamination with the potential of a large waterborne 
outbreak or sporadic outbreaks with low contamination levels (WHO, 2014).   
It is therefore important that regular water surveillance is conducted to detect early 
contamination with waterborne pathogens to allow remedial action to prevent the 
possibility of an outbreak.  In Ghana, water quality monitoring is rarely done and this 
research analyzed the bacteriological quality of household drinking water in both cholera 
endemic and non-endemic communities. 
2.8.4.4 Microbial Parameters 
Microbial parameters are ‘indicator’ organisms used to provide useful information in 
assessing water quality. Usually, the pathogenic pathogens (Salmonella, Shigella, Vibrio, 
or Enteroviruses) themselves are not used as indicator organisms because they are often 
present in small amounts in water and may require unique microbiological techniques 
which might not be cost-effective. Thus, the practical approach is to adopt and use 
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indicator organisms that inhabit the gut in large numbers and excreted in faeces. 
Therefore, the indicator organisms to use must demonstrate the presence of faecal 
contamination as a sign of health hazard (WHO, 1997). As such, WHO (1997) identified 
characteristics of a good indicator organism to include; availability of the organism in 
faeces of humans and other warm-blooded mammals, ease of detection by simple 
methods, must not grow naturally in water or the water distribution network, must be able 
to be treated by disinfection. The essence of the indicator organism is for it to predict the 
presence of pathogens.   
Most of the enteric viruses and protozoa (Cryptosporidium, Giardia) resist disinfection 
and may not be considered as good indicator organisms  (Omarova, Tussupova, 
Berndtsson, Kalishev, & Sharapatova, 2018). However, some countries have started to 
include enteric viruses as indicator organisms because they can afford the cost in their 
investigations  (Wen et al., 2020). This suggests that there is no limit to the inclusion of 
other organisms as an indicator organism. However, the primary indicator organisms still 
involve assessing water quality remains total coliforms, thermotolerant coliforms or faecal 
coliforms, E. coli, and Enterococcus (WHO, 2017c). 
Indicator Bacteria 
Total Coliform Bacteria 
Total coliform bacteria (TC) comprise a large group of organisms which are; Gram-
negative rod-shaped, non-sporing bacteria that can grow in media containing bile salts. 
They are oxidase-negative and ferments lactose at 35-370C with the production of acid, 
gas within 24 to 48 hours (WHO, 1997). The TC belongs to the species within the family 
of Enterobacteriaceae that are capable of growth at 370C and possessed β-galactosidase 
(WHO, 1997). The species belong to the genera Escherichia, Citrobacter, Klebsiella, and 
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Enterobacter. They exist naturally in water and soil. When TC is used in the assessment of 
water quality, care must be taken in the interpretation of the findings since they exist 
naturally and may not necessarily be of human origin (Payment, Waite, & Dufour, 2003). 
This notwithstanding, TC analysis uses cost-effective laboratory techniques and results 
can be obtained within 14 to 24 hours, hence often included in microbial water quality 
assessment (Payment et al., 2003). 
Thermotolerant (faecal) Coliform 
Thermotolerant coliform (TTC) are a group of total coliforms that can ferment lactose at 
44 to 450C with the production of acid and gas (WHO, 1997). The majority of TTC 
belongs to the genus Escherichia, while others are Klebsiella, Enterobacter, and 
Citrobacter species (WHO, 1997). Most TTC exists naturally in the soil and decaying 
water plants and may not necessarily be from faecal origin. Nonetheless, their presence 
nearly always indicates faecal contamination especially in the temperate countries where 
95% of TTC isolated from water are E. coli, a prove of faecal contamination (Bartram & 
Pedley, 1996). In tropical countries, the proportion of E. coli present in TTC may be 
lower.  This implies that caution must be taken in interpreting the results of the analysis, 
and there may be the need to include other additional tests to confirm the presence of E. 
coli.  Thermotolerant coliform analysis can be performed using simple cost-effective 
techniques and results can be obtained within 14 to 24 hours (Payment et al., 2003). 
Escherichia coli 
Escherichia coli is a TTC that possesses the enzymes β-galactosidase and β-glucuronidase 
(Payment et al., 2003). They usually grow at 44 to 450C with acid and gas production and 
also produce indole from tryptophan (Payment et al., 2003). However, some strains of E. 
coli grow at 370C and do not produce gas. Although they are mostly non-pathogenic, the 
Enterohaemorrhagic E. coli serotype (O157:H7) are pathogenic (Payment et al., 2003). 
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Escherichia coli is present in abundance in humans and animal faeces. It is present in 
water and soil that has been recently contaminated with faeces. It has been suggested that 
E. coli can grow and multiply in tropical waters and not only present from human faecal 
contamination (WHO, 1997). This is attributed to other faecal contamination by animals 
other than humans. However, if  E. coli is present in water it should not be ignored 
because the presumption remains that the water has been faecally contaminated with the 
possibility of the presence of pathogens and requires treatment (Payment et al., 2003). As 
such, E. coli is still considered as the most preferred indicator of faecal contamination than 
the faecal coliforms for assessing water quality (Odonkor & Ampofo, 2013). Escherichia 
coli is also easy to detect with simple laboratory techniques and sensitive to disinfection 
(Payment et al., 2003). 
Streptococci and Enterococci 
Faecal streptococci are Gram-positive cocci-shaped, non-sporing bacteria that belong to 
the genus Streptococcus. They are catalase-negative and grow optimally at 35 to 370C in a 
medium containing bile salts and sodium azide. The faecal enterococci (e.g E. faecalis, E. 
faecium, E. avium, and E. gallinarium) can be differentiated from other faecal 
streptococcus by growth in the presence of 6.5% sodium chloride at 450C (Cabral, 2010). 
The faecal enterococci are present in human and animal faeces. Humans' faeces almost 
always have only the two faecal enterococci strains (i.e E. faecalis and E. faecium) 
(Cabral, 2010). The other species of faecal enterococci (e.g E. avium, E. ceocorum, E. 
durans, E. gallinarum, and E. hirae) occur in the faeces of other animals including birds 
(WHO, 1997). However, faecal enterococci species exhibit similar phenotypic 
characteristics and are difficult to differentiate. In terms of the magnitude, faecal 
enterococci are present in lower levels in the gut than E. coli. Faecal enterococci are also 
more resistant to drying and chlorination and survive longer than E. coli and are a useful 
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‘indicator’ organism (Payment et al., 2003). However, caution must be taken in the 
interpretation of water analysis, since faecal enterococci can also be present in food of 
animal origin. Some crops and agricultural soils may also contain faecal enterococci 
resulting from the manure used on the farm. Nonetheless, in drinking water faecal 
enterococci should not be present to demonstrate water treatment efficiency (WHO, 1997). 
Faecal enterococci are easily detectable by simple inexpensive cultural techniques used in 
routine bacteriology laboratories (Payment et al., 2003). 
Vibrio species 
Vibrio are Gram-negative curved-rods that can grow at 35 to 370C in TCBS medium. They 
are mostly found as free-living in an aquatic environment. The distribution of the species 
is dependent on the sodium concentration and water temperature. They are pathogenic in 
humans if ingested in food or water. 
Vibrio is considered a good ‘indicator’ organism because of the high loads of recovery 
from surface water and the ease of isolation using basic bacteriological cultural techniques 
(Okpokwasili & Akujobi, 1996). However, not usually included as an ‘indicator’ organism 
because they are mostly pathogenic and their presence can be predicted by the presence of 
faecal coliform or E. coli. 
2.8.5 Food-related risk factors for cholera 
Exposure to raw or undercooked seafood including shellfish, crabs, oysters, clams, dried 
fish, seafood, and salad can increase the risk of cholera infection (Iwamoto, Ayers, 
Mahon, & Swerdlow, 2010; Kim et al., 2018; Nguyen et al., 2014). This is because Vibrio 
species are found to be naturally present in the gastrointestinal tracts and gills of these 
seafoods, where they are protected from unfavourable conditions (Halpern & Izhaki, 2017; 
Iwamoto et al., 2010). Vibrio cholerae has also been found to survive in a wide variety of 
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foods including rice, tea, coffee, millet gruel, as well as bakery, poultry, and dairy 
products and could pose a risk of cholera when contaminated with the bacterium 
(Hounmanou et al., 2016; Mrityunjoy et al., 2013; Tang et al., 2013). Fruits (except sour 
fruits) and vegetables when eaten raw or unwashed have also been associated with an 
increased risk of cholera (Moradi, Rasouli, Mohammadi, Elahi, & Barati, 2016).  
The contamination of the vegetables or fruits may occur by contact with sewage or manure 
from the human origin on the farm. This has been reported in Lusaka, Zambia between 
November 2003 and February 2004, where an outbreak was linked to the consumption of 
raw vegetables (DuBois, Sinkala, Kalluri, Makasa-Chikoya, & Quick, 2006). A case-
control study conducted by Dinede, Abagero, and Tolosa (2020) in Addis Ababa, Ethiopia 
similarly found the consumption of raw vegetables to be associated with cholera 
outbreaks. In the same study, drinking of ‘holy water’ at an orthodox church was also 
attributed to the outbreak (Dinede et al., 2020). The ‘holy water is water blessed by the 
priest for religious purposes and fetched by the congregants and could have been 
contaminated in the process.  Unhygienic practices of food handlers either at home or 
outside of the home may also result in the contamination of food. These poor hygienic 
practices are particularly common in developing countries where public health measures 
with regard to food are not adhered to. A cholera outbreak in Northwestern Thailand in 
2010 was associated with the Hainanese chicken rice which was contaminated by the food 
handlers during food preparation and handling (Swaddiwudhipong, Hannarong, 
Peanumlom, Pittayawonganon, & Sitthi, 2012). The unhygienic handling of food is 
particularly more pronounced among food vendors on the streets who sell ready-to-eat 
foods.   
Accra is highly urbanized with most of the population relying on food vendors for cheap 
and ready-to-eat foods. It is estimated that about 117 people eat from a vendor in a day in 
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Accra (Donkor, Kayang, Quaye, & Akyeh, 2009). Unfortunately, the majority of the food 
vendors are unlicensed and challenged in the practice of food safety. It is therefore not 
surprising that most residence in Accra contract cholera through the eating of food or 
drinking water from street vendors (Ohene-Adjei et al., 2017). This is further emphasized 
by Feglo and Sakyi (2012) who found higher than acceptable counts of enteric bacteria in 
ready-to-eat foods in Kumasi. Therefore, eating food from outside the home may play a 
major role in contracting cholera. 
On occasions such as funerals, weddings, meetings, or conferences where there is public 
gathering cholera outbreaks can occur if the food served is contaminated. Acquah et al. 
(2016), demonstrated this during an outbreak in Medinya, in the Western region of Ghana 
where most of the people who ate ‘fufu’ and groundnut soup served at the wedding had 
contracted cholera.  In times, where leftover foods are poorly stored and eaten unheated 
may increase the risk of cholera infection (Benjamin, 2018). 
Vibrio cholerae can survive longer under refrigeration (<100C) than in ambient 
temperature. A study by  Waturangi, Amadeus, and Kelvianto (2015) showed that V. 
cholerae survived in foods and beverages for more than two months at room temperature, 
more than three months under refrigeration, and even longer under frozen conditions (-
200C). Therefore, refrigerating or freezing contaminated foods is not a guarantee of 
protection from cholera transmission. This is particularly critical when importing frozen 
foods from cholera endemic countries. In this current study, the food eating habits of 
people living in both cholera endemic and non-endemic communities were studied. 
 
2.8.6 Environmental Sanitation 
Cholera epidemics in Accra have been linked to improper sanitation including the poor 
management of waste (Anaman & Nyadzi, 2015; Ohene-Adjei et al., 2017). In Ghana, 
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large tons of waste are produced daily due to the high population and rapid urbanization of 
our cities (Anaman & Nyadzi, 2015). In most communities in Accra, the waste companies 
are unable to cope with the large quantities of solid waste generated. Hence, oftenwaste 
dumpsites are left to overflow and if waste is not removed regularly,  produces an odour 
that attract flies (Addo, Adei, & Acheampong, 2015).  
Exposure of foods to these flies from the waste dumpsites could aid in the spread of 
diseases including cholera. Osei and Duker (2008b)  used spatial statistical modelling to 
establish a direct relationship between cholera prevalence and proximity to refuse 
dumpsites. They suggested that waste dumpsites should be sited beyond a 500m radius 
from the households. In deprived communities where households cannot afford the high 
charges of waste collection companies, households resort to burying, burning, or 
indiscriminately dumping their waste in the gutters or along the roads (Anaman & Nyadzi, 
2015). The result is that the non-biodegradable wastes are washed into the drains by rains 
to choke the gutters with the consequences of flooding. These floodwaters have the 
potential of contaminating water sources and could result in cholera outbreaks.  
In the deprived communities in Accra, the majority of households lack access to a toilet in 
their homes and rely on public toilets or practice open defecation (Ghana Statistical 
Service, 2013). Yet others, are forced to use pan latrines or defecate into a plastic bag and 
throw (‘flying toilets’) into the environment. These are washed following heavy rains into 
the gutters with the possibility of contaminating the water net connection if the pipelines 
are broken. This study conducted an environmental assessment to understand the reasons 
for cholera persistence in the endemic communities. 
2.8.7 Climatic factors 
There is a strong link between climate change and human infectious diseases (Khan, Thi 
Vu, Lai, & Ahn, 2019; Wu, Lu, Zhou, Chen, & Xu, 2016). The commonly used climatic 
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variables that significantly affect infectious disease transmission include; temperature, 
precipitation, relative humidity, and wind (Parham, Christiansen-Jucht, Pople, & Michael, 
2011). These variables have been used extensively in vector and water-borne infections to 
make predictions and responses to control infectious diseases (Fouque & Reeder, 2019). 
However, their impact is not easily understood because of the other influencing factors 
besides the climatic factors. Nevertheless, mathematical models are developed based on 
climatic data and used to predict early warning signs to prevent outbreaks (Sofaer et al., 
2017). A review of literature from 1974 to 2005 demonstrated the emergence of cholera 
outbreaks with varying seasonal patterns which increases the sea level and sea surface 
temperature (Emch, Feldacker, Islam, & Ali, 2008).  Their findings support an earlier 
study in the Bengal region by Colwell (1996) who found warmer temperatures to increase 
the abundance of phytoplankton and therefore of zooplankton which serves as a reservoir 
for V. cholerae.  de Magny et al. (2011), also found a relationship between increased 
zooplankton population and V. cholerae, hence the incidence of cholera. In that study, they 
associated the detection of V. cholerae with zooplankton such as rotifers, cladocerans, and 
copepods. Numerous studies also identified cholera variability to be related to the inter-
annual climate oscillations (e.g., El Niño) (Constantin de Magny, Guegan, Petit, & 
Cazelles, 2007; De Magny, Cazelles, & Guégan, 2006). The inter-annual climate 
oscillations were explored by studying a 20-year monthly cholera time series data for five 
West Africa coastal countries including Ghana, Togo, Côte d'Ivoire, Benin and Nigeria. 
The researchers further examined the role of climate inter-annual variability on both 
global and local scales. In their study they found a significant association between cholera 
incidence and climate variability (Constantin de Magny et al., 2007). 
Although rainfall periodically appears to be associated with cholera incidence in Ghana, 
this correlation is not spatially and temporally consistent. For example, Moore et al. 
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(2018) observed an extended lull period in cholera incidence from the climatic and cholera 
data analyzed from 2011 to 2014, despite the typically high temperatures and rainfall 
recorded along the coastal belt of the country. This work explored the risk of cholera 
transmission by analyzing the seasonal variation in water contamination levels in the 
drinking water and the determination of V. cholerae O1/O139 toxigenic strains in the 
aquatic environment in the selected communities. 
2.8.8 Hygiene  
Basic hygiene practices including handwashing are an important preventive measure 
against the transmission of infectious diseases. Handwashing with soap before meals and 
after defecation for instance has been found to be protective against cholera (Wolfe, 2018). 
However, there is low access to basic handwashing facilities at homes, schools, or public 
toilet facilities to promote this (Appiah-Brempong, Harris, Newton, & Gulis, 2018; Peprah 
et al., 2015).  A study to assess the hand hygiene habits of 254 youth in Accra,  Oppong, 
Yang, Amponsem-Boateng, and Duan (2019) found that only 22% of the youth practice 
handwashing after outings while 51.6% washed after using the bathroom. 
In the absence of flowing tap water in households or school environments a ‘bowl of water 
is provided for hand washing (Tetteh-Quarcoo et al., 2016).  This practice is common and 
not protective since it creates the opportunity for the transmission of microbes washed into 
the water. 
Among some individuals, the preference is to wash with soap after eating or defecation. 
These were the findings of a study of some communities in Bangladesh where 
handwashing with soap before eating and after defecation was much lower  (Rabbi & Dey, 
2013). It was also observed in a multivariate analysis that handwashing with soap was 
strongly associated with socioeconomic factors such as; education of household heads, 
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availability, and access to water and soap (Rabbi & Dey, 2013). In this study, 
handwashing habits were studied in the communities. 
2.8.9 Water, Sanitation and Hygiene Interventions related to Cholera 
Water, sanitation and hygiene (WASH) is a strategy adopted by WHO to reduce the 
burden of cholera in the endemic or hotspot areas  (WHO, 2018d). While sufficient 
WASH is acknowledged as being essential to avoiding cholera, it is frequently viewed as a 
long-term, expensive intervention that poor countries cannot quickly implement  (WHO, 
2018d). In order to quickly control the disease during an outbreak, some nations have 
relied on temporary treatments like the use of oral cholera vaccine which are costly and 
unsustainable (Chaignat, 2008). 
Adopting long-lasting WASH measures is crucial for the elimination of cholera (Lantagne, 
Bastable, Ensink, & Mintzd, 2015). Accordingly, the World Health Assembly (WHA) 
decided in 2011 to collaborate with the Global Task Force for Cholera Control (GTFCC) 
to eliminate cholera, particularly in cholera hotspot areas (WHO, 2018d). The WHO 
Global Cholera Elimination Plan, which seeks to reduce cholera mortality by 90% by 
2030, has over 50 partners as of October 2017 (WHO, 2018d). Their agenda is to help 
nations accomplish the Sustainable Development Goals (6.1 and 6.2) that call for 
achieving equal and universal access to clean water and sanitation (WHO, 2018d). 
The main WASH programmes involved enhancing access to "improved" water supplies, 
assuring microbiological water safety, lowering inequities, maintaining sustainability in 
households and institutions, and ending open defecation (Lantagne et al., 2015). In the 
meanwhile, a comprehensive plan to stop the spread of cholera must include WASH 
initiatives at the community and household levels (Lantagne et al., 2015). To fully utilize 
the initiative, regular monitoring and evaluation of the WASH interventions is required. 
The current study investigated the risk factors for cholera in endemic and non-endemic 
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communities and offered recommendations in conjunction with WASH to prevent cholera 
and other diarrhoeal disease epidemics. 
2.9 Spatial distribution of cholera 
Geographic Information System technology is a tool that is used to process, analyze and 
visualize spatial data in environmental health, disease ecology, and public health 
(Kistemann, Dangendorf, & Schweikart, 2002). This concept of spatial distribution was 
first demonstrated by John Snow during the London cholera outbreak in 1855 (Brody, Rip, 
Vinten-Johansen, Paneth, & Rachman, 2000). In his study, Snow was able to use spatial 
patterns of cholera cases which he represented with dots to illustrate how the cases 
clustered around the contaminated water sources. Thus, was able to determine the cause of 
the outbreak. This happened before the discovery of the cholera bacterium by Robert Kock 
in 1884. After the discovery of V. cholerae, most studies on cholera were related to the 
biological and pathogenic characteristics of the bacterium and could not accurately detect 
the individual exposures and the high-risk geographical areas. However, with the advent 
of the GIS technology disease incidence of cases can accurately be identified by location 
for immediate public health action. Geographic Information System has also been used to 
integrate multiple layers of spatial data in different disciplines such as health, 
environmental, genetic, socio-demographic risks and can establish relationships using 
different spatial analysis including; proximity calculation, assessment of clustering, spatial 
smoothing, interpolation and spatial regression (Auchincloss, Gebreab, Mair, & Diez 
Roux, 2012). Many studies have employed proximity measures and spatial statistical 
methods to establish the relationships between cholera and environmental risk. Osei and 
Duker (2008b) explored the proximity and density of open refuse dumps. In the study, 
they used spatial statistical modelling to demonstrate that proximity and density of open 
refuse dumps played a role in cholera transmission in Kumasi. They indicated that open 
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refuse dumps serve as niches for cholera infection and individual households living within 
a 500 m radius were more at risk of cholera infection. Their findings are similar to that of 
Olanrewaju and Adepoju (2017), who also found cholera to occur close to waste dump 
sites near markets, rivers/streams, and abattoirs. In another related research, Osei and 
Duker (2008a) used spatial and statistical analysis to show that high cholera cases were 
clustered around Kumasi Metropolis and further indicated high urbanization and 
overcrowding to be important predictors of cholera in the Ashanti Region. Spatial analyses 
have also been used to predict cholera occurrence and drinking contaminated water. 
Olanrewaju and Adepoju (2017) demonstrated this in a composite risk cholera map where 
cholera ‘hotspot’ areas recorded high coliform counts in their drinking water source.  
Thus, suggesting that faecal contamination of drinking water sources predisposes 
communities to cholera infection. 
Although GIS technology has been used to identify risks factors for cholera, this has often 
been done during outbreaks to show how cases clustered. This study used spatial analysis 
to produce composite risk maps for cholera in both endemic and non-endemic coastal 
communities in the GAR. By mapping the cholera risk factors in geographical space, local 
authorities will be able to easily identify, make a prediction of potential future outbreaks 
and appropriately plan with the necessary resources. 
In summary, there is evidence that cholera outbreaks are linked to drinking water quality, 
environmental-related factors, socioeconomic and behavioral factors. Geographical 
Information System is a useful tool that could be used to spatially map the distribution of 
these factors in relationship to cholera cases for future control of outbreaks. 
 
  
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CHAPTER THREE 
METHODS 
3.1 Study Design 
A community-based cross-sectional comparative design was used for this study. The study 
area was classified into two communities; cholera endemic and cholera non-endemic. The 
cholera endemic communities were cholera ‘hotspots in the Accra Metropolitan Area, 
Ledzokuku, and Krowor Municipal Areas which over four years (2011 to 2014) have 
recorded high cholera cases with high attack rates.  The cholera non-endemic communities 
were the Ningo Prampram, Ada West, and East districts that have rarely recorded any case 
of cholera over the same period. Households were randomly selected and data on 
socioeconomic, water supply, solid and liquid waste disposal and behavioural factors 
about food safety were collected from the household heads or their adult representatives 
using a questionnaire. Drinking water from selected households was sampled for 
bacteriological water quality assessment. An environmental assessment was also done 
using an environmental health inspection guide and risk factors including; water bodies, 
markets, public toilets, and refuse disposal sites mapped using GIS. The water bodies were 
sampled for the presence of Vibrio cholerae O1 and O139 toxigenic strains.  The study 
was conducted in the wet (April to August 2019) and dry seasons (January to March 
2020). 
3.2 Study Area 
The study was carried out in the Greater Accra Region (GAR), one of the 16 
administrative regions of Ghana. It is located in the south-central part of the country and 
bordered by the Central Region to the west, Volta Region to the east, Eastern Region to 
the north, and the Gulf of Guinea to the south (Figure 3.1). It is the smallest of the 16 
regions, occupying a total land surface of 3,245 square kilometres or 1.4 percent of the 
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total land area of Ghana  with estimated  population to be 5,055,805 (Ghana Statistical 
Service, 2014). The capital city of Ghana, Accra is also located in the region with a daily 
influx of people from within and outside the country.  
The region is the most urbanized and has the highest population density in the country 
(Ghana Statistical Service, 2013). There are highly populated slums, squatter, and informal 
settlements in parts of the region due to the rapid urbanization being experienced (Accra 
Metropolitan Assembly and UN Habitat, 2011; Amoako, 2016). The region has 29 
districts of which two are metropolitans; namely Accra and Tema and 23 municipalities 
including; Ablekuma Central, West and North, Adenta, Ashiaman, Ayawaso East, Central, 
North and West, Ga Central, East, North, South, and West, Korle Klottey, Kpone 
Katamanso, Krowor, La Dade Kotopon, La Nkwantanang, Ledzokuku, Okaikoi North, 
Tema West, Weija Gbawe and four ordinary districts; Ada East and West, Ningo 
Prampram, and Shai Osudoku as shown in Figure 3.1.  
The region is endowed with many tourist attractions including forts, Kwame Nkrumah 
Mausoleum, outstanding beaches, estuaries that attract tourists to the region. There are 
diverse ethnic groups with the predominant group being the Akans followed by the 
indigenous Ga-Dangmes (Ghana Statistical Service, 2013).  
With regards to occupation, the majority of the people living in the urban areas are 
engaged in trading, transport business with a larger concentration of professional and 
technical workers whereas, farming, animal husbandry, and fishing are the predominant 
occupation of the people in the rural communities (Ghana Statistical Service, 2013). Salt 
mining is common among inhabitants living along with the tributaries of the Volta River 
where the soil is waterlogged and salty (Ghana Statistical Service, 2013). 
 
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The region has a coastline stretching the entire southern end of the region from Kokrobite 
in the west to Ada in the east. The region is located in the dry equatorial belt with coastal 
savannah vegetation. The average temperatures of the region range between 24.7°C and 
33.0° C (Ghana Statistical Service, 2014). The highest temperatures are recorded in April 
and the lowest in August. The region is the driest in the country with annual rainfall 
ranging between 635 millimetres along the coast to 1,140 millimetres in the northern parts 
(Ghana Statistical Service, 2014). There are two rainfall seasons, the major occurring from 
April to July and the minor from September to November, however peaking respectively 
in June and October (Ghana Statistical Service, 2014).  The driest months of the year are 
between November and April.  
The region has low-lying areas which are usually subjected to severe perennial flooding 
following heavy rains due to the poor drainage system and choked gutters (Ghana 
Statistical Service, 2013). This has the potential of contaminating water pipelines and 
spreading diseases. The river Densu and Volta are the two main rivers flowing through the 
region but have tributaries flowing into the sea through Lagoons. The most important of 
these are the Odorna river and Korle Lagoon which is highly polluted and located in the 
Accra Metropolis (Aglanu & Appiah, 2014).   
The majority of the households do not have toilet facilities at their homes and use public 
toilets (Ghana Statistical Service, 2013). Others living along the beaches drains, refuse 
dumps, and open spaces engaged in open defecation (Ghana Statistical Service, 2013). 
Solid waste disposal is generally poor and usually dependent on the availability of vehicles 
to convey the waste to the field sites (Ghana Statistical Service, 2013). This usually results 
in solid waste overflowing and posing a health risk to the public. Clean water supply is not 
regular in some communities and they rely on vendor supply for their domestic chores 
(Ghana Statistical Service, 2013).  
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The GAR has been the epicenter for most cholera epidemics in the country since the first 
case of cholera was reported in 1970. Since 2004 the Accra Metropolitan Assembly 
(AMA) and Ledzokuku Krowor Municipal Assembly (LEKMA) have persistently 
reported cholera cases almost every year (Ghana Disease Surveillance Department, 2015). 
The Disease Surveillance Department of the Ghana Health Service identified communities 
where the outbreaks usually begin with the highest recorded cholera cases and attack rates 
as cholera ‘hotspot’ communities. These communities are in AMA and LEKMA were 
selected as the cholera endemic sites for the study while communities from Ningo 
Prampram, Ada West, and East districts which rarely recorded a case of cholera and also 
located along the coastal belt selected as non-endemic communities.   
 
Figure 3.1: A Map showing the endemic and non-endemic areas in the Greater Accra 
Region 
ALN-Ablekuma North, ABC-Ablekuma Central, ABW-Ablekuma West, ACC-Accra 
Metropolis, KKT-Korle Klottey, WGB-Weija Gbawe, OKN-Okaikoi North, AYW-
Ayawaso West, LDK-La Dade Kotopon, ASH-Ashaiman 
 
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3.2.1 Cholera Endemic Communities 
Twelve (12) communities were identified from the AMA and LEKMA based on the 
regular high burden of cholera with evidence of  local transmission over the past four 
years (2011 to 2014) (Ghana Disease Surveillance Department, 2015; WHO, 2018c). 
These communities are; Agbogbloshie and James Town in the Ashiedu Keteke Sub 
Metropolis; Adabraka in the Korle Klottey Sub Metropolis; Kaneshie in the Okaikoi 
South; Maamobi and Nima in the Ayawaso Sub metropolis; Chorkor and Mamprobi in the 
Ablekuma South Metropolis; Agege and Dansoman in the Ablekuma West Sub 
Metropolis; Teshie in the Ledzokuku Municipality and Nungua in the Krowor 
Municipality (Figure 3.2). 
 
Figure 3.2: Cholera ‘hotspots’ or endemic communities in the Greater Accra Region 
 
  
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3.2.2 Cholera Non-endemic Communities 
The non-endemic communities were communities selected from Ningo Prampram, Ada 
West, and East districts which rarely recorded a case of cholera with no evidence of local 
transmission for the past four years (2011 to 2014)(WHO, 2018c). These communities 
were 12 in number, viz. Dawhenya North, Kofikope, Awhiam, and Dawa in the Ningo 
Prampram district; Addokope, Dogobom, Anyaman East, Adjumanikope in the Ada West 
district; Adedetsekope, Angomya-Ada, Kophemm Kasseh and Asigbekope in the Ada East 
district. 
 
Figure 3.3: Cholera non-endemic communities in the Greater Accra Region  
 
3.3 Study Population 
The study population was the population of households living in the Greater Accra Region 
at the time of the study.  
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3.4 Study Variables 
The dependent or outcome variable was ‘cholera’ defined based on the surveillance 
suspected or confirmed case definition as in table 3.1(a) and reported by household 
members past experience. ‘Cholera’ which is binary was recorded as ‘Yes’ if household 
member ever had cholera and ‘No’ if household member never had cholera. The 
independent variables were categorized into three main areas and described as: 
socioeconomic factors (age, sex, ethnicity, religion, occupation, educational level, income 
level, wealth index and house occupancy, residential unit); behavioural factors (solid and 
liquid waste disposal practices, food and water safety habits); environmental factors 
(availability of aquatic reservoir, toilet facilities, waste dumpsites, markets, and abattoir) 
and water sanitation factors (water source, water quality, water distribution network).  All 
the variables are summarized in Table 3.1(a,b,c). 
  
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Table 3.1a: Operationalization of the Key study variables 
Variables Operational Definition Level of Categories 
Measurement 
Dependent    
variable 
 Cholera    A patient 2 years and above Dichotomous Yes 
with acute watery diarrhoea  No  
with or without vomiting and 
severe dehydration or dies of 
acute diarrhoea or a patient of 
any age with acute watery 
diarrhoea from whom V. 
cholerae (O1 or O139) was 
isolated from faeces during 
illness by culture or PCR. 
Independent    
variables 
Age Age of respondent in Discrete but 18-27, 28-37, 38-47, 48-57, 
 completed years at the time of was categorized 58-67, >68 
the study 
Sex Respondent being identified Dichotomous Male, Female 
 as male or female 
Marital status Respondent relationship with Nominal Single,  
 a significant other Married, 
 Cohabit, Separated, Divorced, 
Widowed 
Religion Religious affiliation of the Nominal No religion, Christianity, 
 respondent Islam, Traditionalist, others 
Ethnicity Identified group with Nominal Akan, Ewe, Ga Dangme, 
 similarities such as culture, Guan, Mole-Dagbon, Others 
language or history that the 
respondent belongs 
Employment Refers to the current work Nominal Unemployed, Retired worker, 
 position of a respondent  Formal employment, Informal 
employment 
Level of The highest level of formal Nominal No formal Education, Primary 
Education school that a respondent ever Education, JSS/Middle School 
 attended or was attending Education, Senior High 
 Education, Tertiary Education 
Income level All money received from Ranked or Low income (≤ Gh₵300), 
(ranked) salary, wages or own business ordinal Medium income (> Gh₵300 - 
as well as money from ≤ Gh₵1000), High income (> 
additional work activities, Gh₵1000 - ≤ Gh₵2000), 
remittances from family Highest income > Gh₵2000 
elsewhere, pensions or grants 
 
 
 
  
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Table 3.1b: Operationalization of the Key study variables  
Variables Operational Definitions Level of Categories 
Measurement 
Residential Refers to the various types of Nominal Separate house, Semi-
unit dwelling  detached, Flat/apartment, 
 Compound house (rooms), 
Tent, Improvised house 
(Kiosk/container) Living 
quarters attached to 
office/shop, Uncompleted 
building, others 
Household Number of people living in Discrete and 1-3, 4-6, ≥7 
occupancy the household categorized 
 
Drinking Source of water for drinking Nominal Private pipe, public pipe, 
water source and domestic chores borehole, protected well, 
 unprotected well, water-
 carrier/tanker/vendor, surface 
water 
(dam/river/stream/spring), 
Other water sources 
Drinking Drinking water that is free Nominal Private pipe, public pipe, 
water quality from harmful borehole, protected well, 
microorganisms unprotected well, water-
carrier/tanker/vendor, surface 
water 
(dam/river/stream/spring), 
Other water sources 
Water safety Water handling and storage Nominal water treatment at the point 
habit of used, water storage in 
clean containers, storage 
vessels covered 
Food safety Food handling, storage and Nominal Treatment of leftover food 
eating habit  before eating, handwashing 
 before meals, washing of 
fruits before eating, storage 
of cooked food, eating home 
prepared food 
Household Measures taken for the safe Nominal Waste collected once a week, 
waste disposal transportation and disposal of Waste collected irregularly, 
household waste burned by households, public 
dump (container), public 
dump (open space), dumped 
indiscriminately, Buried by 
household, Others 
Human waste Measures taken for the safe Nominal No toilet facilities, Water 
disposal collection of by-products of closets, Pit latrine, KVIP, 
digestion such as faeces and Bucket/Pan, Public toilet 
urine (WC, KVIP, Pit pan/etc), 
others 
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Table 3.1c: Operationalization of the Key study variables (cont’d) 
Variables Operational Definitions Level of Categories 
Measurement 
Liquid waste Measures taken for the safe Nominal Through the sewage system, 
disposal  disposal of liquid waste Through the drainage system 
 into the gutter, through 
drainage into a pit (soak 
away), Thrown onto the 
street/outside 
Aquatic water The availability and Dichotomous Proximity to cholera cases,  
reservoir closeness of water bodies  
(river, stream, sea, others) to No proximity to cholera 
the community  cases 
Public refuse The availability and Dichotomous Proximity to cholera cases,  
dumpsite closeness of refuse disposal  
 site to the community No proximity to cholera 
cases 
Markets The availability and Dichotomous Proximity to cholera cases,  
closeness of markets to the  
community No proximity to cholera 
cases 
Abattoirs The availability and Dichotomous Proximity to cholera cases,  
closeness of an abattoir to the  
community No proximity to cholera 
cases 
  
3.5 Sample Size Determination for households 
The sample size was calculated using Cochran’s formula given (Cochran, 1963). 
N= z2 p(1-p)               
           e2 
where,  
N = desired sample size of the households to be interviewed 
p = proportion of households that reported a case of cholera in a pilot study conducted at 
Ashongman community in the Ga East Municipality =23.0% 
1-p = the proportion of households that did not report a case of cholera 
z = the standard normal deviation (set at 1.96 corresponding to the 95% CI)  
e = Precision or degree of accuracy desired (set at 0.05) 
    N= (1.96)2 X 0.23(1-0.23)   
                 (0.05)2 
 
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     N= 272.02 
A design effect of 1.5 was assumed because there is no information in the study area. It is 
meant to produce a larger sample size than what will be expected with a simple random 
sampling method.  
272.02 X 1.5 = 408.03 
However, adjusting for a non-response rate of 10% (Awalime, Davies-Teye, Vanotoo, 
Owoo, & Nketiah-Amponsah, 2017) 
The total sample size was therefore estimated as follows; 
N= 408.03/ (1-0.10) = 453.37 = 453.37. This was rounded up to 453 as the minimum 
sample size of households selected for the endemic communities.    
The sample size for each community was then calculated based on proportional 
representation as indicated in Table (3.2 & 3.3)  
where, 
 ‘n’ represents the sample size of the households for the study area  
‘Nh’ represent the household population of each community population 
‘N’ the total household population in the study area 
‘n1’ represents the sample size of the households to be selected 
i.e n1= Nh x n 
               N 
 
 
  
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Table 3.2: Population of households as of 2014 in the endemic communities 
Community Household Population Sample size (proportionate to size) 
Agbogbloshie 43, 121 32 
James Town 17, 936 13 
Adabraka 40, 369 30 
Kaneshie 34, 433 25 
Maamobi 68, 248 50 
Nima 89,388 66 
Chorkor 29, 694 22 
Dansoman 62,593 46 
Agege 10, 162 7 
Mamprobi 28,585 21 
Teshie 111, 785 82 
Nungua 80, 796 59 
Total 617,110 453 
Source Ghana Statistical Service, 27th June, 2018 
The sample size for the non-endemic communities were similarly calculated as shown in 
table 3.3.  
Table 3.3: Population of households as at 2018 in the non-endemic communities  
Community Household Population Sample size (proportionate to 
size) 
Ningo-Prampram District   
(151) 
Kofikope 5173 42 
Awhiam 4155 34 
Dawhenya-North 5440 44 
Dawa 3876 31 
 18,644  
 
Ada West District (151)   
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Addokope 123 35 
Dogobom 89 25 
Adjumanikope 164 47 
Anyamam East 156 44 
 532  
Ada East District (151)   
Angomya-Ada 535 28 
Kopehem Kasseh 785 41 
Asigbeykope 868 46 
Adedetsekope 691 36 
 2879  
 Total 453 
Source District Health Directorate Populations, 2018 
3.6 Sample size Determination for household drinking water 
To determine how many drinking water samples of the selected household to sample the 
Cochran’s formula was used; 
N= z2 p(1-p)               
           e2 
Where, 
 N = desired number of water samples to collect from the communities,  
p = proportion of households drinking water contaminated with V. cholerae as 83.8% 
reported in Accra Metropolis (Yirenya-Tawiah et al., 2018), 
e = Precision or degree of accuracy desired (set at 5%)   
z = Standard normal deviation (set at 1.96 corresponding to the 95% CI)   
    N= (1.96)2 X 0.838(1-0.838)   
                 (0.05)2 
 
     N= 208.608 
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The minimum sample size was 209 for each of the communities. Therefore, for both dry 
and wet seasons in the endemic and non-endemic communities, total sample size was 
estimated to be 420. 
 
3.7 Sampling Technique 
This study employed a multistage cluster sampling approach. A cluster represented 
cholera ‘endemic’ or ‘non-endemic community. A three-stage sampling technique was 
used in the endemic community. The first stage represented the selection of all twelve (12) 
clusters from the endemic communities which included; Agbogbloshie, James Town, 
Adabraka, Dansoman, Agege, Mamprobi, Chorkor, Kaneshie, Nima, Maamobi, Teshie, 
and Nungua were purposively selected based on their identification as cholera ‘hotspots’ 
(Ghana Disease Surveillance Department, 2015).  
 
The second stage involved the listing of all the Ghana Health Service Community-based 
Health Planning and Services (CHPs) zones in each of the endemic communities and 
random selection of one CHPs zone by ballot. This was necessary because of the large size 
of the communities. 
A systematic sampling procedure was used in the third stage to select the households. A 
household was defined as a person or group of people who lived in the same dwelling and 
shared meals during the survey period. Each of the selected clusters were mapped by 
drawing to show the various important landmarks such as health Centre, church, mosques, 
school, market, major roads or public toilet.   
The centre of each cluster was located and a random direction was obtained by spinning an 
empty bottle. The households along the direction indicated by the bottle top were followed 
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in a straight line, numbering the houses on both sides until the boundary of the sector was 
reached. A sampling interval was first determined for each community by dividing the 
total number of households in the CHPs zone by the number of households to sample.  
From the listed number of houses obtained, a random household number was selected as 
the starting point for inclusion in the study and then the sample interval to locate the next 
household to sample. This continued until the calculated minimum sample size for each 
cluster was obtained.  In situations where there was more than one household in a house as 
in a compound house or flats only one household was selected by a ballot. If there was no 
qualified respondent the interviewer went to the next house that has the closest door and 
checked for a qualified respondent. This continued until an eligible respondent was found. 
In cholera ‘non-endemic communities, a two-stage approach was employed.  The first 
stage was the selection of four communities each from the three cholera non-endemic 
districts (Ningo Prampram, Ada west, Ada East) in the GAR. All 12 clusters were 
randomly selected by a ballot using the list of all the communities from each of the three 
cholera non-endemic districts that rarely reported a case of cholera over the same period 
(2011 to 2014)  (Ghana Disease Surveillance Department, 2015). The selected 
communities were; Addokope, Dogobom, Adjumanikope, Anyaman, Adedetsekope, 
Agomya-Ada, Kopehem-Kasseh, Asigbeykope, Awhiam, Dawa, Kofikope, and Dawhenya 
North.  
A systematic sampling procedure was similarly used in the second stage to select the 
households as described in the endemic communities. The sampling and recruitment were 
done by the researcher and the research assistants.  
3.8 Inclusion Criteria 
Participants who were eligible for inclusion in this study were; 
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1. The head of households or a senior member of the family (above 18 years) 
2. Members of the household living in the community before 2015 to the time of the 
study. 
3.9 Exclusion Criteria 
1. Visiting adults were not allowed to act in the absence of the head of household 
3.10 Data Collection Method/Technique and Tools 
The research was conducted from March 2019 to March 2020. All stakeholders including 
the Disease Surveillance Department, Accra Regional Health Directorate, Accra 
Metropolitan and Sub-metropolitan health Directorates, Accra Environmental Health, and 
the respective District Health Directorates that were sites for this study were engaged to 
solicit their inputs during the proposal development phase of this work. Site visits were 
also conducted to meet with some community leaders including chiefs and 
assemblymen/women to inform them of the objective of the study. The Public Health 
Nurses, Community Health Nurses and Disease Control Officers serving in the study sites 
served as liaisons between the researchers and the community to facilitate easy entry into 
the communities. 
A questionnaire designed specifically for this study was used to collect data from the 
household members about their sociodemographic factors, water sanitation factors, solid 
waste, and sewage disposal factors, and behavioural factors. The socioeconomic 
characteristics section of the questionnaire was adopted from the Demographic and Health 
Survey (DHS) questionnaire and modified.  
The other sections of the questionnaire were designed by the researcher with expert 
guidance from public health and environmental health specialist. The questionnaire 
comprised a series of questions to be filled in by the research assistants during the 
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interview with the participant. The questionnaire included both open-ended and closed-
ended questions. The open-ended questions allowed the participants to respond to 
questions in their own words while the closed-ended questions gave alternative responses 
for the participants to select. The questionnaire was written in English and interpreted by 
the researcher or research assistant in Twi, Ga, or Ewe if the respondents did not 
understand or write English.  
During the administration of the questionnaire, the research assistants first introduced 
themselves to the participants and explained the purpose of the study. The participants 
were then assured of their confidentiality and anonymity. Consent was sought and 
participants signed or thump printed an informed consent form and another community 
member or the research assistant witnessing.  
3.11 Environmental Assessment 
An onsite sanitation inspection guide adopted from Cheesbrough (2006), modified and 
pretested at Ashongman community in the Ga East Municipality by the researcher was 
used for the assessment of the water supply pipelines (availability of exposed pipelines, 
accumulation of water around the pipelines, pipelines laid in open drains/gutters, broken 
pipelines); refuse disposal (availability of waste dumpsite/landfill site, refuse dump 
container overflowing, flies around refuse dumpsite, refuse dumpsite near a water source); 
Sewage disposal (choked gutters with waste, indiscriminate disposal of sewage, evidence 
of sewage disposed into water body); Excreta disposal (availability of public toilets, flies 
hovering around toilet facility, evidence of open defecation) in the environment of the 
households in the endemic and non-endemic communities. 
In addition, water from surface water bodies including rivers/streams, dams, lagoons, and 
estuaries located in the selected communities was also collected for microbial analysis. 
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The GIS coordinates and photographs of potential environmental cholera risk factors were 
taken.  
3.12 Water Sample Collection 
Households’ drinking water samples were collected for bacteriological quality analysis. 
The households from which samples of water were collected were randomly selected by 
listing all the households in each of the communities and balloting to select nine 
households for each of the 24 sites in the endemic and non-endemic communities. One 
additional sample was purposively collected from the main drinking water source point 
(e.g public tap, pipe, or dam) as a control sample in each community.  The water samples 
were collected in the wet season (April to August 2019) and repeated in the dry seasons 
(January to March 2020) to determine the temporal variation in water quality.  
About 500 ml of the stored household drinking water was sampled using the container 
usually used to scoop water from the storage container into a sterile plastic bottle. In case 
the household drank sachet water they were collected and a selected edge of the sachet 
water decontaminated by cleaning with 70% ethanol, then cut aseptically with sterile 
scissors and the water poured into the sterile plastic bottle. On the other hand, if the 
household drank bottled water, they were only collected and labelled. The water samples 
from the source point were directly collected from the pipe, standpipe, dam, or well. 
The collection of water from the tap or pipe water was done by cleaning the outside of the 
tap with 70% ethanol and allowing flow at maximum for about a minute before directly 
collecting into the sterile plastic bottle (Cheesbrough, 2006). A drop of sodium 
thiosulphate (0.5 ml of 10% solution) was added to the pipe-borne water to neutralize 
residual chlorine before transporting it to the laboratory (Cheesbrough, 2006). 
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Environmental water samples were collected from the water bodies (lagoons, estuaries, 
rivers or streams, and dams) located in the selected communities. These environmental 
water samples were collected manually by attaching a string to a 500 ml Wheaton sterile 
glass bottle and directly lowering it to a depth of about 30 centimetres in the water body 
and allowed to fill before redrawing as described by Cheesbrough (2006). The river or 
streams water samples were collected in the up and down streams. The dams and lagoons 
water samples were collected at multiple points, whiles the estuarine water was sampled 
from where the lagoon or river meets the seawater. Coordinates of these sampling points 
were recorded by GPS to ensure the water samples were collected at the same point in 
both the dry and wet seasons.  
The water samples collected from the field were transported in insulated boxes at 40C to 
the laboratory within six hours. In case of a delay, the water samples were stored in the 
refrigerator (20C to 80C) and processed the next day (within 24 hours).  
3.13 Laboratory Analysis 
3.13.1 Bacteriological Quality of water 
3.13.1.1 Membrane Filtration Method 
The water samples were analyzed in accordance with the American Public Health 
Association (APHA) standard methods for examining drinking and wastewater using the 
membrane filtration method  as described by Eaton et al. (2005). 
3.13.1.2 Media Preparation and Selection 
The appropriate media including; Eosin Methylene Blue (EMB) agar, Violet Red Bile 
(VRB) agar, Plate Count Agar (PC), Thiosulfate-Citrate-Bile-Sucrose (TCBS) agar, 
Tryptone Soy Agar (TSA), MacConkey Agar (MAC), were prepared following the 
manufacturer’s instructions. The prepared media was dispensed into 25 ml sterile plastic 
disposable petri dishes and allowed to set. They were dried in a hot air oven set at 55 to 
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600C for about 30 minutes to sufficiently dry before being used. Buffered peptone water 
was also prepared and sterilized in bottles for use in the dilution of the water samples 
where the growth was uncountable.  
3.13.1.3 Set up of the membrane filtration system 
The membrane filtration system consists of a funnel or filtration apparatus connected to a 
vacuum source/pump and a suction flask. The apparatus was sterilized with 70% ethanol 
and to ensure sterility, placed or mounted in the laminar flow hood.  A membrane filter of 
0.45µm was aseptically removed from the sterile package and place over the porous plate 
of the filtration receptacle with the grid side up. The funnel unit was carefully placed over 
the receptacle and locked with a clamp. About 100 ml of water was poured directly into 
the filtration funnel. In instances that the growth was heavy and uncountable (i.e greater 
200 colony count), 10 ml, 1 ml, 0.1 ml, or 0.01 ml of the water was used and diluted with 
buffered peptone water to make up the 100 ml before filtration. The pump was turned on 
to filter the sample under partial vacuum with the filter still in place and sample allowed to 
be drawn completely but retaining any bacteria on its surface. Forceps were flamed and 
aseptically used to transfer the filter unto a well labelled sterile petri dish with the 
appropriate media (PC agar, VRB agar, EMB agar, and TCBS). The filtration funnel was 
decontaminated with 70% ethanol and the vacuum turned on to allow the liquid to be 
drawn completely out before repeating with another sample. 
The inoculated PC and VRB agar were incubated at 360C±1, while the EMB and TCBS 
were incubated at 440C±1. The plates were observed after 24 hours and 48 hours. The 
plates for PC and VRB were counted and estimated respectively for the total viable count 
and total coliform. The EMB was estimated for faecal coliforms (thermotolerant 
coliforms) and TCBS for suspected Vibrio species. 
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3.13.1.4 Counting of colonies on the Plates 
After the incubation period, the grid pattern of the sterile membrane filter was used as a 
guide for rapid counting of the colonies with the aid of a hand lens. The colony density 
was estimated using the formula; 
Colonies/100 ml =    Number of colonies counted    X 100 ml 
                                     mL of sample filtered 
 The ‘mL of sample filtered’ refers to the actual sample volume and not the diluted. 
3.13.1.5 Sub-culturing of colonies 
The morphological characteristics of the colonies on the filter membrane were described. 
Colonies that appeared as; large, smooth, yellow, slightly flattened, and translucent 
peripheries on the TCBS medium were presumptively identified as Vibrio cholerae. These 
colonies were sub-cultured onto another TCBS plate for purification. The suspected Vibrio 
colonies were further sub-cultured on TSA (a non-selective media) for biochemical testing 
and serotyping. Other suspected coliform bacteria growing on the PC agar, VRB, EMB 
were sub-cultured on MAC plate for purification. Distinct colonies were sub cultured on 
TSA for presumptive identification and biochemical testing. 
3.13.1.6 Confirmation of V. cholerae serotype 
To confirm the V. cholerae, the suspected isolate was first serotyped with polyvalent 
antisera type-specific O1 and O139 (Denka Seiken Co., Ltd, Tokyo, Japan). The 
agglutination test was done by picking the suspected V. cholerae colonies and emulsified 
them in a drop of sterile distilled water on clean glass slides. The slide was then 
thoroughly mixed by tilting back and forth for 30 seconds. The suspension was then 
examined to ensure the suspension is smooth and without any agglutinins. A drop of 
polyvalent O1 antisera was added to the suspension and mixed on the slide by tilting back 
and forth and observed for the presence or absence of agglutination. For a positive 
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reaction, strong clumps appeared within 30 seconds to 1 minute. This process was 
repeated with polyvalent antisera for O139. If polyvalent O1 antiserum was positive, the 
specific serotype was confirmed using monovalent Inaba and Ogawa antisera.  
3.13.1.7 Biochemical testing of colonies 
In addition to a Gram stain test that was performed on the pure culture isolates, the 
conventional method of bacteria identification was carried out by testing isolates for 
catalase, oxidase, motility, Indole, and ornithine decarboxylase activity as well as 
carbohydrate fermentation on Triple Sugar Iron (TSI) agar. The Gram-Negative bacteria 
which could not be identified by the conventional biochemical test were subsequently 
identified using Mini Antigenic Profile Index for Enterobacteriaceae (API 20E). 
3.13.1.8 Processing of the Antigenic Profile Index 20E Biochemical Test 
The Antigenic Profile Index (API) 20E is a standardized identification system for 
Enterobacteriaceae and other non-fastidious, Gram-Negative rods which uses 21 
miniaturized biochemical tests and a database (bioMérieux, France) was used. It consists 
of 20 microtubes containing dehydrated substrates. A single test isolate was emulsified in 
an ampule of 5 ml of API sodium chloride (0.85%) medium to achieve a homogeneous 
bacterial suspension. The bacterial suspension was distributed with a sterile pipette into 
the 20 microtubes on the API strip and incubated at 36 ± 20C for 18 to 24 hours. The strip 
was read with the reading table. All the microtubes that showed spontaneous reactions 
were recorded and those microtubes that required the addition of reagents to determine; 
tryptophan deaminase (TDA), indole (IND), and acetoin (VP) production were added and 
also read.  
The tests were separated into three groups and a value of 1, 2, or 4 was indicated for each. 
By adding together, the values corresponding to positive reactions within each group, a 7-
digit profile number was obtained for the 20 tests on the API strip. The oxidase test which 
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was performed first constitutes the 21st test and had a value of 4 if it was positive. The 
identification was performed by keying in the 7-digit numerical profile in the API 20 E 
database (bioMérieux, France) and bacteria identified. 
3.13.2 Genomic DNA Extraction 
All strains of V. cholerae isolated from the culture and directly from the environmental 
water samples collected from rivers, dams, lagoons, and estuaries were identified and 
confirmed for the presence of ompW, O1rfb, O139rfb, and ctxA genes. 
3.13.2.1 Extraction of V. cholerae DNA from Environmental water samples and broth Culture  
The environmental water samples were concentrated by filtering 250 ml of the samples 
aseptically through a 0.22 µm pore size bacteriological membrane filter (Millex GP 
Syringe filter Unit). The retained contents of the membrane were placed in a 2 ml sterile 
microcentrifuge tube and 200 µl of phosphate-buffered saline (pH 8.0) was added. It was 
vortexed for 5 minutes at full speed to wash the filter paper and the DNA extraction was 
carried out using the Zymo Research DNA extraction kit (D3024, USA). The filter paper 
was removed and 800 ml genomic lysis buffer was added to the tube (4:1, i.e 800 µl 
genomic lysis buffer to 200 µl of phosphate-buffered saline (PBS)). It was vortexed again 
at full speed for 10 minutes and incubated for 10 minutes at room temperature. The 
contents were carefully transferred into the Zymo-Spin Columns in a collection tube 
without wetting the rim. The tubes were centrifuged at 10,000 x g for a minute (Thermo 
Scientific, max. 14,800 rpm or 24 x 4g, UK). The collection tube was discarded and the 
Zymo-Spin Column was transferred into a new 2 ml collection tube. The mini spin 
columns were carefully opened and 200 µl of DNA Pre-wash buffer was added. The mini 
spin columns were centrifuged at 10,000 x g for a minute.  The mini spin columns were 
transferred into new 2 ml collection tubes.   About 500 µl of DNA wash buffer was 
carefully added to the mini spin columns and centrifuged at 10,000 x g for a minute. The 
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spin columns were transferred into sterile 1.5 ml microcentrifuge tubes and 50 µl DNA 
elution buffer was added. It was then incubated at room temperature for 5 minutes and 
centrifuged at top speed (10,000 x g) for 30 seconds to elute the DNA. The DNA quantity 
and quality were determined using NanoDrop One (Thermo Fisher Scientific Inc, USA). 
The DNA extract was divided into 25 aliquots, labelled, and stored at -20 0C until tested. 
Overnight cultures (18 to 24 hours) of V. cholerae isolates were made in Luria broth and 
incubated at 37 0C. The extraction of the broth cultures was also carried out using Zymo 
kit (D3024, USA) for DNA purification.  About 1 ml of broth culture was centrifuge at 
10,000 x g for 2 minutes. The supernatant was discarded and cells resuspended in 200 ml 
of PBS and the procedure continued as described by protocol from the Zymo kit for 
extraction of DNA from cell cultures.  
3.13.2.2 Polymerase Chain Reaction Analysis 
Polymerase Chain Reaction detection (PCR) of V. cholerae was based on the protocol 
described previously by Alam et al. (2006) with few modifications. The detection of V. 
cholerae was done by amplification of the ompW gene which targets the outer membrane 
protein; ctxA which targets the cholera toxin gene subunit A; and the O1rfb and O139rfb 
genes specific for serogroup O1 and O139 strains, in a uniplex PCR assays.  The primers 
used were; 
Table 3.4: PCR primers used in the study  
Primer no. Primer name Primer sequence Amplicon 
size(bp) 
1 ctxAF 5'-CTCAGACGGGATTTGTTAGGCACG-3' 310 
2 ctxAR 5'-TCTATCTCTGTAGCCCCTATTACG-3' 310 
3 O1rfbF 5'-GTTTCACTGAACAGATGGG-3' 200 
4 O1rfbR 5'-GGTCATCTGTAAGTACAAC-3' 200 
5 O139rfbF 5'-AGCCTCTTTATTACGGGTGG-3' 450 
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6 O139rfbR 5'-GTCAAACCCGATCGTAAAGG-3' 450 
7 ompWF 5'-CACCAAGAAGGTGACTTTATTGTG-3' 310 
8 ompWR 5'-GGTTTGTCGAATTAGCTTCACC-3' 310 
   
PCR amplification of V. cholera genes 
Four uniplex PCR assays were carried out in 12.5 μl reaction volumes consisting of 6.25 
μl One Taq Quick-Load 2X Master Mix with Standard Buffer (Biolabs, New England), 
4.75 μl of nuclease-free water, 1μl of the extracted DNA template, and 0.25 μl of 10 µM 
of each specific primer for each gene (Inqaba Biotec, West Africa Ltd).  Each reaction was 
thoroughly mixed by vortexing and flush centrifugation. This was then put in the PCR 
Biometra TRIO thermocycler (Analytik Jena, Germany). The conditions used in the PCR 
amplification consist of an initial denaturation at 94 0C for 1 min followed by 30 cycles of 
1 min denaturation at 94 0C, 1 min annealing at 510C for ompW and O139rfb genes, 52 0C 
for ctxA genes, and 45 0C for O1rfb genes followed by 1 min extension at 68 0C. A final 
extension was performed at 68 0C for 5 min. 
Agarose gel electrophoresis of amplified genes 
After the amplification, 10 μl of the amplicon was taken and electrophoresis was carried 
out in 1X Tris Acetate EDTA buffer at 250v for about 45 minutes on 1.5 % agarose gel 
containing 0.5 µg/ml ethidium bromide. The gel was visualized with a UV 
transilluminator and images digitized with a gel documentation system (UVITEC, 
Cambridge). The bands were estimated by comparing to a 50 base pair ladder.  
3.15.2 Wealth Index 
A total of 26 items were selected to determine the wealth index of the households using 
the principal components analysis (PCA). These items included demographic health 
survey variables such as access to electricity, ownership of television, ownership of 
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refrigerator, cooking fuel (LPG, charcoal, wood), type of dwelling (detached house, semi-
detached house, flat/apartment, compound house), and materials used for building 
(cement, mud). Fourteen (14) of the variables had frequencies less than 5% and greater 
than 95% and were excluded from the analysis. The remaining 12 variables (electricity, 
television, fridge, LPG, charcoal, wood, detached house, semi-detached house, 
flat/apartment, compound house, cement, and mud) were included in the PCA analysis. 
The variables were changed into binary as yes (present) or no (absent) and coded as ‘1’ 
and ‘0’ respectively.  The wealth index score was then produced into three equal parts 
(poor, medium, and wealthy).  
3.15.3 Sanitation Assessment 
In determining the community sanitation score index, a total of 14 items were selected to 
cover the conditions of the water supply pipelines, refuse and sewage disposal practices of 
the households. A total of 4 variables had frequencies less than 5% and greater than 95% 
and were excluded from the analysis. The remaining 10 items (variables) included in the 
PCA were; availability of exposed pipelines, accumulation of water around the pipelines, 
refuse dumpsite in the neighbourhood, refuse dump overflowing, house flies hovering 
around the dumpsite, refuse dumpsite located near a water source, evidence of open 
defecation, availability of public toilets, choked gutters or drains, indiscriminate disposal 
of solid waste, discharge of liquid waste or sewage into a water body. The variables were 
changed into binary as yes (present) or no (absent) and coded as ‘1’ and ‘0’ respectively. 
The principal component generated was used to assign to each of the households a 
sanitation score in relation to the other households in the sample. The sanitation 
assessment index score was then produced into three equal parts (poor, moderate, and 
good sanitation condition).   The reliability of the sanitation index was found to be 0.76 
and above the Cronbach’s alpha value of above 0.7 and acceptable. 
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3.14 Spatial Data Collection 
3.14.1 Cholera data abstraction 
Cholera incidence data for Greater Accra Region (GAR) from 2012 to 2015 obtained from 
the Greater Accra Regional Health Directorate was used for the study. Linelist from 
outbreaks that occurred within the period was obtained from Greater Accra Regional 
Health Directorate. The data were entered into Microsoft Excel 2016 and saved in a GIS 
usable format.  The variables included in the abstraction tool included: year, district, date 
of onset, the town of residence, and geographic position.  Garmin Hand Held GPS device 
(eTrex 10, Taiwan) was used to capture the spatial coordinates (accuracy of 12 metres) for 
the location of the cases and added to the cholera data abstracted. 
3.14.2 Other spatial data 
A digitized boundary map of Ghana showing the regions, and districts (GHA_ADM 0,1 
and 2) shapefile, a digitized elevation (raster), and Ghana town location was obtained from 
Land Use and Spatial Planning Authority-Ghana. The shapefiles were imported into 
ArcGIS and the query tab was used to subset it to GAR. This was used to generate 
shapefiles for district boundaries (vector), elevation (raster), and town location in GAR.  
3.15 Data Analysis 
3.15.1 Data processing and analysis 
The data collected from the survey questionnaire were coded and double entered in EPI 
Data version 3.1. It was exported into STATA software version 14.0 (State Cooperation, 
USA), cleaned, and analyzed. 
Descriptive statistics such as means and standard deviation for continuous variables and 
frequencies and percentages for categorical variables were used to summarize and present 
the background characteristics of the study participants.  
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For categorical data (nominal and ordinal variables) such as; sex, marital status, religion, 
ethnicity, employment status, level of education, residential unit, water source, water 
quality, piped water supply, water safety, and food safety results were presented by 
summary tables of counts and percentages or frequencies.  
For continuous variables such as; age, income level, household occupancy, duration to 
seek care, distance to a health facility, summary tables of means, median, and or ranges, 
and standard deviations were presented. For continuous variables that were skewed, the 
median and interquartile ranges were presented. 
Inferential statistics were applied to estimate parameters of the population based on the 
sample data.  Kruskal Wallis rank test, a non-parametric equivalent of the Analysis of 
Variance (ANOVA) test was performed to determine whether there were any differences 
between the means of the log of bacteria counts among some selected factor variables. 
Chi-square/Fisher exact test was used to perform a test of association between cholera and 
other independent variables. All independent variables with p-values less than or equal to 
0.2 significance level were retained in a multivariable penalized logistic regression model 
using forward stepwise deletion.  
A penalized logistic regression model was specified as the most appropriate statistical tool 
for the data because of the sparse data (small number of cholera cases relative to the 
sample size). The penalized logistic regressions model for a binary response was used to 
estimate the odds of cholera as a function of independent variables. To understand the 
effect of the independent variables on the dependent variable (cholera), the parameter 
estimated was interpreted in terms of odds ratios. The p-value less than 0.05 was 
interpreted as significant. 
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A multicollinearity test of the regression model was conducted using variance inflation 
factors (VIFs). The results from the socioeconomic characteristics, behavioural and 
environmental risk factors model showed the mean VIF values to be 1.53, 1.44 and 1.75 
respectively.  All the individual VIF values were less than 2.32 (lower than the widely 
used cutoff value of 5.0) as reported by Craney and Surles (2002) which suggest that 
multicollinearity was not of a concern. 
Goodness of fit test was conducted using the McFadden R-squared value. Models on 
socioeconomic characteristics, behavioural, and environmental risk factors were found to 
have an R-squared values of 0.102, 0.055, and 0.130 respectively. According to 
McFadden, Tye, and Train (1977), McFadden R-squared value between 0.20 to 0.40 tested 
represents an excellent fit. Based on this it was concluded that the models did not fit the 
data well. 
3.15.4 Spatial data processing and Analysis 
The Geographic Positioning System (GPS) waypoint data was imported into ArcGIS 
software version 10.2 by connecting the Universal Serial Bus (USB) port of the computer 
with the Garmin data cable. The data from data collectors were cleaned using Microsoft 
excel. The Geographic Information System (GIS) maps were developed to show the 
distribution of cholera cases from 2012 to 2015. Spatial point pattern analysis was 
employed to show the distribution of the cholera cases in GAR.  
3.15.5 Spatial point pattern analysis  
Firstly, the outline shapefile of GAR was imported and used as an outline map. This was 
done through the data menu and navigation to the location of the file. The cholera case 
location shapefile for each of the four years (2012 to 2015) was imported into the ArcGIS 
and laid on the outline map of GAR to generate a map showing the distribution of cholera 
in GAR for the respective years. Case magnitude was visualized using cell size graduated 
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symbol where larger cell size denotes a high number of reported cases and vice versa.  
However, to detect any change in the distribution pattern of the cholera cases over time for 
the four years, the cholera case location shapefile as graduated was computed for each of 
the four years and visualized. Geographic coordinates for significant environmental risk 
factors such as toilets, dumping sites, and big gutters were obtained. Each risk factor was 
imported into the GAR boundary map with the reported cases to show the proximity of 
risk factors to the reported cases. Subsequently, a shapefile of combined risk factors was 
imported onto the GAR boundary map to show the combined effects of the risk factors of 
the cholera incidence in the communities. Point pattern descriptors were used to show the 
distribution of cholera risk factors in endemic and non-endemic communities.   
 
Figure 3. 4: Screenshot of spatial pattern analysis 
 
3.15.6 Proximity analysis  
The spatial analysis tool of proximity function in ArcGIS was used to determine the 
relationship between the cholera cases in the community and the identified features 
particularly the environmental factors (toilets, big gutters, dumping sites, markets, and 
water bodies) associated with cholera. A 500m buffer distance was created for each risk 
factor to examine its relationship with the distribution of cases. Shapefile for all the risk 
factors (toilets, big gutters, dumping sites, markets, and water bodies) were imported onto 
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the classified GAR boundary map and the cholera outbreak distribution map at 500m 
buffer to examine the combined effects of the cholera outbreak.  
 
Figure 3. 5: Screenshot of proximity analysis 
 
3.16 Quality Assurance 
3.16.1 Questionnaire Development and Data Collection 
3.16.1.1 Training of Research Assistants 
Research assistants (8) for this study consisted of three field coordinators at the Dodowa 
Research Centre of the Ghana Health Service, one disease control officers, and four 
national service personnel. A one-day training was conducted at the School of Public 
Health, University of Ghana lecture Room G2. They were trained on the objectives of the 
study, data collection techniques as well as questionnaire administration.  They were also 
trained on the use of the GPS receiver to collect the geographic coordinates, perform an 
accuracy checkpoint (ACP) and verify if the set-up was correct.   
3.16.1.2 Pilot Study 
A pilot study was conducted to assess the practicality of the instrument to prevent 
divergences between research assistants and the attributes to be measured. The pilot study 
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was conducted in the Ashongman community in the Ga East Municipality of the GAR 
with similar population dynamics as the Accra Metropolis or LEKMA. The questionnaire 
was administered to 25 households and the outcome was used to make modifications to 
the questionnaire items before being used for all respondents during the actual fieldwork. 
The data was not included in the main study.  
3.16.1.3 Validity 
The questionnaire content was reviewed by environmental and health experts to ensure it 
measured items by the concept of what was intended.  
3.16.1.4 Reliability 
Since lack of reliability may arise from divergences between research assistants or the 
questionnaire of measurement or the instability of the attributes to be measured, the 
questionnaire was piloted, revised, and the same set of questionnaires administered to all 
respondents.  
3.16.1.5 Data Entry 
All questionnaires were cross-checked before entering into the database. The cross-
checking of questionnaires was to ensure data completeness and logical consistency. The 
questionnaire found to be incomplete or with errors were either taken back to the field or 
rectified by calling the participants within 24 hours. Data entry clerks were trained on the 
creation of the data entry screen and coding of the variables. Checks and skip patterns 
were created to ensure required variables are captured to eliminate data incompleteness 
during data entry.  
3.16.2 Spatial Data collection 
A positional accuracy check was conducted throughout the data collection. The maximum 
error distance allowed for taking the coordinate was 6 metres. The coordinates collected 
were plotted on a google map to validate the data obtained from the field.  
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3.16.3 Laboratory Analysis 
All the containers used for the collection of water samples from the field were sterilized by 
autoclaving and checking with an autoclave tape to ensure sterilization. The water samples 
were collected under strict aseptic techniques following the protocol and immediately 
stored in an insulated box at 40C and transported immediately to the laboratory. In case of 
a delay, the samples were stored in a refrigerator at 2 to 80C and transported within a day 
(within 24 hours) to the laboratory. 
All the bacteriological media were prepared in accordance with the manufacturer’s 
instructions and dispensed into disposable pre-sterilized plastic Petri dishes. A sterility test 
was performed on each batch of media prepared by incubating a plate at 35 to 370C 
overnight (18 to 24 hours) and examined for any contamination. A media performance test 
was also conducted by culturing in-house or reference bacteria strains obtained from the 
National Public Health and Reference Laboratory, Korle-bu to assess the growth 
characteristics of the media. The reference strains and in-house control strains were used 
as reference points to validate the results of the biochemical tests. 
Blank membrane filtration was carried out after every fifth sample. This was to ensure 
growths on the filter membrane were not influenced by the laboratory conditions. The 
filtration techniques were carried out in a laminar flow hood to avoid contamination as 
much as possible.  
Vibrio cholerae O1 toxigenic in-house strains were used as the positive controls and 
included each time during the extraction and amplification procedure of the DNA. The 
nuclease-free water and the master-mixed were used as the negative controls. The controls 
were read first in all cases to validate the test. 
3.17 Ethical Consideration 
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3.17.1 Ethical Approval 
Ethical clearance was obtained from the Ghana Health Service Ethical Review Committee 
(GHS-ERC) with approval number GHS-ERC 006/01/19 before the commencement of 
this study.   
3.17.2 Study Area Approval 
Permission was obtained from the Greater Accra Regional Health Directorate, Accra 
Metro Health Directorate, Ledzokuku-Krowor Municipal Health Directorate, Ningo 
Prampram, Ada West and Ada East District Health Directorates and the Accra 
Metropolitan Environmental and Sanitation Directorate to have access to the study area 
and their facilities before the field activities started.  
3.17.3 Informed consent 
Informed consent was obtained from potential study participants before they took part in 
the study. It was obtained without coercion, undue influence, or misrepresentation of the 
potential benefits and risks that might be associated with participation in the study. Before 
participation in this study, the research assistants reviewed the informed consent form with 
the participant in a language that was understandable to the participant. They informed 
them of the purpose, rationale of the study, how they were selected, the procedures, and 
the length of the interview. Those who agreed to participate consented by signing or 
thump printing two consent forms. A copy of the signed or thump printed consent form 
was given to the participant.   
3.17.4 Risk of the study 
No foreseen risks were associated with this study except for the time they spent 
responding to the questionnaire. 
3.17.5 Benefits 
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Participants did not benefit directly from the study but the results from the study would 
help identify cholera risk factors in the communities and make recommendations for 
policymakers to improve on how to prevent cholera outbreaks. 
3.17.6 Right to withdrawal 
Participants were not obliged to take part in the study and were allowed to freely opt-out at 
any stage of the study without any punishment, intimidation, losing any benefit 
whatsoever. 
3.17.7 Confidentiality/Anonymity 
Data were handled anonymously and confidentially. Extensive effort was made to 
minimize the physical movement of data and or devices containing them. Data were 
entered into electronic devices to avoid unauthorized persons having access to them. 
Efforts were also made to minimize the transfer of identifiable data in physical or 
electronic form. Anonymity was ensured by using other identifiers including codes instead 
of the names of participants in data collected and analyzed. GPS coordinates of household 
locations were converted to distances so that the individual locations are not revealed. The 
maps were also created from aggregated data of larger areas.  
3.18 Safety Precautions 
Universal safety measures were employed throughout sample collection and testing. 
Gloves and laboratory coats were worn during all laboratory procedures. The bench tops 
and hoods were regularly decontaminated with 5% hypochlorite. The sharps which 
included the used pipette tips were placed in puncture-resistant containers and the used 
media were decontaminated with 5% hypochlorite and placed in biohazard bags. They 
were autoclaved before incineration.  
 
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CHAPTER FOUR 
RESULTS  
4.1 Socioeconomic characteristics of households in the Greater Accra Region 
Table 4.1(a & b) provides descriptive information on the socioeconomic characteristics of 
the households. A total of 906 household respondents were interviewed with a 100% 
response rate to the survey questionnaire.  Of these 453 households, were sampled from 
both cholera endemic communities and non-endemic communities.  The mean age of the 
respondents was 41.52 ± 15.66 years in the endemic communities and 42.58 ± 14.29 years 
in the non-endemic communities. The female respondents were 343 (75.7%) and 269 
(59.4%) in the endemic and non-endemic communities respectively.   
With regards to the marital status of the respondent, the majority were married 215 
(47.5%) of the respondents been from the endemic communities and 307 (67.8%) in the 
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non-endemic communities. The majority of the respondents were Christians in both 
endemic 312 (68.9%) and non-endemic 392 (86.5%) communities.  
The respondents were predominantly 902 (99.6%) Ghanaians with 165 (36.4%) and 391 
(86.4%) of them belonging to the Ga-Dangme ethnic group in the endemic and non-
endemic communities respectively.  
More than three-quarters of the respondents in the endemic communities 390 (86.1%) and 
non-endemic communities 369 (81.5%) had primary education and above (basic 
education) whereas 63 (13.9%) and 84 (18.5%) had no formal education respectively.  
Concerning the employment status of respondents, more than two-thirds were employed in 
the informal sectors in both the endemic 329 (72.6%) and non-endemic communities 318 
(70.2%). However, less than a quarter of the respondents in the endemic communities 102 
(22.5%), and the non-endemic communities 82 (18.1%) were unemployed. Most of the 
respondents in the endemic communities 318 (70.2%) were in the low-income brackets of 
less than GH¢300 in average monthly earnings, whereas 200 (44.2%) of them were in the 
non-endemic communities earned a medium-income (GH¢300 - GH¢1000).  
In terms of wealth, the majority 218 (48.1%) of the households in the endemic 
communities were medium compared to households in the non-endemic communities who 
were poor 223 (49.3%). With regards to the household size, about half of the respondents 
had a household size of 4 to 6 in both communities.  
 
 
 
 
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Table 4.1a: Socioeconomic characteristics of household respondents in cholera endemic 
and non-endemic communities – (N=906) 
 Endemic Non-Endemic 
Variable  
     
No. % No. % 
Age (mean ± SD) in years 41.52 ± 15.66 42.58 ± 14.29 
Age Group     
 18-27 years 93 20.5 52 11.5 
 28-37 years 110 24.3 132 29.1 
 38-47 years 103 22.7 127 28.0 
 48-57 years 75 16.6 66 14.6 
 58-67 years 43 9.5 45 9.9 
 68+ years 29 6.4 31 6.8 
Length of time living in the community 15 (7-29) 14(8-25) 
(years) Median (IQR) 
Gender     
 Male 110 24.3 184 40.6 
 Female 343 75.7 269 59.4 
Marital Status     
 Single 100 22.1 40 8.8 
 Cohabiting 107 23.6 53 11.7 
 Married 215 47.5 307 67.8 
 Separated 8 1.8 12 2.6 
 Divorced 2 0.4 14 3.1 
 Widowed 21 4.6 27 6.0 
Religion     
 No Religion 1 0.2 7 1.6 
 Christian 312 68.9 392 86.5 
 Islam 139 30.7 16 3.5 
 Traditional 1 0.2 38 8.4 
Nationality     
 Ghanaian 452 99.8 450 99.6 
 Non-Ghanaian 1 0.2 3 0.4 
Ethnicity     
 Akan 98 21.6 26 5.7 
 Ewe 62 13.7 26 5.7 
 Ga-Dangme 165 36.4 391 86.4 
 Guan 6 1.3 0 0 
 Mole-Dagbon 121 26.7 8 1.8 
 Others 1 0.2 2 0.4 
Employment     
 Unemployed 102 22.5 82 18.1 
 Retired Worker 10 2.2 7 1.5 
 Formal Employment 12 2.7 46 10.2 
 Informal Employment 329 72.6 318 70.2 
 
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Table 4.1b: Socioeconomic characteristics of household respondents in cholera 
endemic and non-endemic communities – (N=906)  
Variable Endemic Non-Endemic 
  
      
No. % No. % 
Educational Level     
 No Formal Education 63 13.9 84 18.5 
 Primary Education 112 24.7 79 17.4 
 JSS/Middle School Education 172 38.0 144 31.8 
 Senior High Education 84 18.5 102 22.5 
 Tertiary Education 22 4.9 44 9.7 
Monthly income (earnings)     
 Low income(<Gh¢300) 318 70.2 198 43.7 
 Medium income (>Gh¢300 - Gh¢1000) 130 28.7 200 44.2 
 High income (>Gh¢1000 - Gh¢2000) 5 1.1 45 9.9 
 Highest income(>Gh¢2000) 0 0 10 2.2 
Wealth index     
 Poor 84 18.6 223 49.3 
 Medium 218 48.1 146 32.2 
 Wealthy 151 33.3 84 18.5 
Household size     
 1-3 193 42.6 91 20.0 
 4-6 227 50.1 224 49.5 
 7+ 33 7.3 138 30.5 
 
Table 4.2 (a & b) shows the drinking water sources and handling of households surveyed 
in both endemic and non-endemic communities.  
With respect to the source of drinking water as in table 4.2(a), households in the endemic 
communities 367 (81.0%) mostly drank sachet water, followed by 49 (10.8%) public pipe, 
36 (8.0%) private pipe, and 1(0.2%) borehole water. In the non-endemic communities, on 
the other hand, the majority of the household drank from water sources including; 171 
(37.7%) public pipe, 133 (29.4%) sachet water, 78 (17.2%) private pipe, 37 (8.2%) 
unprotected dug well, 33 (7.3%) surface water, and 1 (0.2%) borehole water. Apart from 
sachet water that was purchased from vendors, the majority of the households in the 
endemic 49 (57.0%) and non-endemic communities 243 (75.9%) had their drinking water 
sources located from outside their house dwelling or yards. The mean distance in minutes 
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to the drinking water source and back was 7.82 ± 3.85 in the endemic community and 
10.03 ± 5.53 in the non-endemic communities.  
Of the 406 households studied, only 8 (9.3%) in the endemic communities and 38 (11.9%) 
in the non-endemic communities treated their drinking water. Of the households that 
treated their drinking water in the endemic communities, half 4 (50.0%) boiled, 1 (12.5%) 
allowed the water to settled, and 3 (37.5%) others added camphor or naphthalene. In the 
non-endemic communities, 14 (36.8%) treated with bleach/chlorine/alum, 10 (26.3%) 
strained through a cloth/strainer, 8 (21.1%) allowed the water to settled, 8 (21.1%) boiled, 
7 (18.4%) applied camphor/naphthalene, and 1 (2.6%) filtered.  The households in the 
endemic communities mostly stored their water as sachet 367 (81.0%) and in plastic 
containers 84 (18.5%) with a few others storing in pot/earthenware vessels 2 (0.4%), metal 
1(0.2%) and elevated polytanks 1 (0.2%). In the non-endemic communities, their drinking 
water was mostly stored in (217, 47.8%) plastic containers, 133 (29.4%) sachet, 121 
(26.7%) pot/earthenware vessels, and a few 6 (1.3%) in metal and 2 (0.4%) elevated 
polytanks.  
In respect to the covering of the household drinking containers, the majority in the 
endemic 83 (96.5%) and non-endemic communities 285 (89.1%) were covered.  
 
 
 
 
 
 
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Table 4.2a: Water sources and handling factors among households in cholera endemic and 
non-endemic communities – (N=906) 
Variable Endemic Non-Endemic 
  
 No. % No. % 
Main source of drinking water 
 Private pipe 36 8.0 78 17.2 
 Public pipe 49 10.8 171 37.7 
 Tube well or borehole 1 0.2 1 0.2 
 Unprotected dug well 0 0.0 37 8.2 
 Surface water 0 0.0 33 7.3 
 Sachet water 367 81.0 133 29.4 
Location source of drinking water (n=406) 
 In own house/dwelling 35 40.7 68 21.3 
 In own yard 2 2.3 9 2.8 
 Elsewhere 49 57.0 243 75.9 
Distance to drinking water and back 7.82±3.85 10.03±5.53 
(Mean±SD) in minutes 
Treatment of drinking water (n=406) 
 Treated 8 9.3 38 11.9 
 Untreated 78 90.7 282 88.1 
Water treatment methods used(n=46) ** 
 Boil 4 50 8 21.1 
 Add bleach/chlorine/alum 0 0 14 36.8 
 Strain through a cloth/strainer 0 0 10 26.3 
 Use water filter 0 0 1 2.6 
 Stand and settle 1 12.5 8 21.1 
 Camphor/Naphthalene  3 37.5 7 18.4 
Storage of drinking water ** 
 Plastic Container 84 18.5 217 47.8 
 Pot/earthenware vessels 2 0.4 121 26.7 
 Metal container 1 0.2 6 1.3 
 Elevated polytanks 1 0.2 2 0.4 
 Bottled/Sachet 367 81.0 133 29.4 
Drinking water storage vessels (n=406) 
 Covered 83 96.5 285 89.1 
 Not covered 3 3.5 35 10.9 
**Multiple responses 
 
 
There were alternative water sources also used for other domestic purposes as shown in 
table 4.2 (b). Among these water sources, a public pipe was the most commonly used in 
both 270 (59.6%) endemic and 217 (47.8%) non-endemic communities.   
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In terms of pipe-borne (private and public pipe) water supply, the majority of the 
households in the endemic communities reported water shortages sometimes 368/446 
(82.5%) with only a few households that never experienced a shortage 3/446 (0.7%). In 
the non-endemic communities’ majority of the households reported water shortages 
sometimes 247/348 (71.0%) and non-reported never having any water shortages in the 
past. 
 
Table 4.2b: Water sources and handling factors among households in cholera 
endemic and non-endemic communities – (N=906) 
Variable Endemic Non-Endemic 
  
 No. % No. % 
Alternate sources of water for domestic purposes** 
 Private pipe 176 38.8 131 28.8 
 Public pipe 270 59.6 217 47.8 
 Borehole 4 0.9 31 6.8 
 Protected dug well 1 0.2 40 8.8 
 Unprotected dug well 0 0 67 14.8 
 Unprotected spring 0 0 3 0.7 
 Rainwater 3 0.7 180 39.6 
 Tanker truck 5 1.1 2 0.4 
 Surface water 0 0 91 20.0 
Water shortage experience  
 Always 18 4.0 7 2.0 
 Often 57 12.8 94 27.0 
 Sometimes 368 82.5 247 71.0 
 Never 3 0.7 0 0.0 
**Multiple responses 
 
 
Table 4.3 (a & b) shows the food eating practices of households surveyed. Over three-
quarters of the households in the endemic 331 (73.1%) and non-endemic 372 (82.1%) ate 
food cooked at home and outside the home as shown in table 4.3(a). In addition, only 4 
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(0.9%) of the households in the endemic community ate food from outside the home, 
whereas 118 (26.0%) only ate food cooked at home. In the non-endemic communities, 81 
(17.9%) only eat food cooked at home and no household ate food from outside the home.   
In terms of the household food cooking habit, 121 (27.0%) of them always cooked at 
home, 160 (35.6%) often cooked at home, and 168 (37.4%) sometimes cook at home in 
the endemic communities. In the non-endemic communities, on the other hand, 112 
(24.7%) always cooked at home, 236 (52.1%) often cooked at home, and 105 (23.2%) 
sometimes cooked at home. More than half 228 (50.8%) of households that cook at home 
in the endemic communities do the cooking outside, and 193 (43.0%) others cook from 
inside the house/dwelling. It was also observed that the majority 169 (37.3%) of the 
households in the non-endemic communities also cook outside, with others cooking inside 
the house dwelling 147 (32.5%) and in separate buildings 137 (30.2%).  
With the treatment of raw vegetables before eating, more than half 304 (67.1%) of the 
households in the endemic communities washed in only water, 116 (25.6%) washed in 
saltwater, 3 (0.7%) others heat steam or parboiled, 8 (1.8%) washed in water and heat 
steam, 15 (3.3%) washed in vinegar, whiles 2 (0.4%) ate without any treatment. In the 
non-endemic communities, raw vegetables were mostly 364 (80.4%) washed with only 
water, while 83 (18.3%) were washed in saltwater. In addition, only one (1) other 
household did not treat their vegetables before eating.   
It was revealed that the majority of the households in the endemic 441 (97.4%) and non-
endemic 448 (98.9%) communities ate leftover foods as in table 4.3(a).  
 
 
 
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Table 4.3a: Household food eating practices in the cholera endemic and non-endemic 
communities – (N=906) 
Endemic Non-Endemic 
Variables   
  No. % No. % 
Food eating habit  
  Only eat food cooked at home 118 26.0 81 17.9 
Eat food cooked from home and 
  331 73.1 372 82.1 
outside home 
  Only eat food from outside home 4 0.9 0 0 
Food cooking at home (n=902) 
  Yes, always 121 27.0 112 24.7 
  Yes, often 160 35.6 236 52.1 
  Yes, sometimes 168 37.4 105 23.2 
Where cooking is done (n=902) 
  Inside the house/dwelling 193 43.0 147 32.5 
  In a separate building 28 6.2 137 30.2 
  Outdoors (in the yard) 228 50.8 169 37.3 
Washing of raw vegetables before eating  
  Washed in water only 304 67.1 364 80.4 
  Washed in water and heat steam 8 1.8 2 0.4 
  Washed in salt water 116 25.6 83 18.3 
Washed in salt water and heat 
  0 0 2 0.4 
steam 
  Heat steam or parboiled only 3 0.7 0 0 
  Washed in vinegar 15 3.3 0 0 
  Washed in vinegar and heat steam 1 0.2 0 0 
Others (heat steam with 
  4 0.9 1 0.2 
salt/without salt) 
  Does nothing to it 2 0.4 1 0.2 
Leftover foods  
  Eaten 441 97.4 448 98.9 
  Not eaten 12 2.6 5 1.1 
  
 
 
 
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Of the 889 households where leftover foods were eaten, the majority 255 (57.8%) of them 
in the endemic communities stored their leftover foods in a refrigerator/fridge, and a few 
13 (2.9%) kept them frozen as shown in table 4.3(b). Among households in the non-
endemic communities, 310 (69.2%) stored their leftover foods covered in the 
room/kitchen, 91 (20.3%) stored in refrigerators whiles 47 (10.5%) others kept them 
frozen.  
It was also found that the majority of households in both endemic 413 (92.2%) and non-
endemic 438 (99.3%) communities treated their leftover stored foods by reheating to boil 
before eating. However, 22 (4.9%) of the households in the non-endemic communities ate 
the leftover foods cold without heating.  
In terms of handwashing practice of the households before meals, 268 (59.2%) washed 
their hands in a bowl of water, 157 (34.7%) washed with soap in a bowl of water, 21 
(4.6%) washed under running water and only 7 (1.5%) washed with soap under running 
water in endemic communities. In the non-endemic communities, 288 (63.6%) were 
washed in a bowl of water, 75 (16.5%) washed with soap in a bowl of water, 63 (13.9%) 
washed under running water and 27 (6.0%) washed with soap under running water. 
With the washing of fruits before eating such as mangoes, oranges, watermelon, apple 
most of the households 310 (68.4%) in the endemic communities washed their fruits in a 
bowl of water, 112 (24.7%) washed with safe running water, 16 (3.5%) in a bowl of water 
and soap and 6 (1.3%) did not wash before eating. In the non-endemic communities, 343 
(75.7%) were washed with water in a bowl, 75 (16.6%) were washed with safe running 
water, 25 (5.5%) were washed with water and soap in a bowl and 6 (1.3%) did not wash 
before eating as in table 4.3(b). 
  
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Table 4.3b: Household food eating practices in the cholera endemic and non-endemic 
communities – (N=906) 
Variables Endemic Non-Endemic 
  
 No. % No. % 
Storage of leftover foods at home (n=889) 
 Left uncovered in the room/kitchen 24 5.4 0 0.0 
 Covered and left in the room/kitchen 149 33.8 310 69.2 
 Put in the refrigerator/fridge 255 57.8 91 20.3 
 Put in a freezer 13 2.9 47 10.5 
Treatment of leftovers before eating (n=889) 
 Eaten cold in the next meal 0 0.0 22 4.9 
 Reheated to boil before eating 438 99.3 413 92.2 
 Warmed in the microwave before eaten 3 0.7 13 2.9 
Handwashing practice before eating 
 Wash hands in a bowl of water 268 59.2 288 63.6 
 Wash hands with soap in a bowl of 157 34.7 75 16.5 
water 
 Wash hands under running water 21 4.6 63 13.9 
 Wash hands with soap under running 7 1.5 27 6.0 
water 
Washing of fruits before eating 
 They are washed with soap under safe 9 2.0 4 0.9 
running water 
 They are washed with safe running 112 24.7 75 16.6 
water 
 They are washed with water and soap in 16 3.5 25 5.5 
a bowl 
 They are washed with water in a bowl 310 68.4 343 75.7 
 They are not washed 6 1.3 6 1.3 
 
Table 4.4 (a & b) shows the solid waste disposal practices among households in the 
endemic and non-endemic communities.  
Out of the 321 (70.9%) households that did not have toilet facilities in the endemic 
communities, 312 (68.9%) used public toilets, whiles 9 (2.0 %) practice open defecation as 
shown in table 4.4(a). Of the households with toilet facilities in the endemic communities, 
majority 73 (16.1%) used flush to piped sewer system, followed by 30 (6.4%) which used 
flush to septic tank and 2 (0.4%) used bucket as in table 4.4(a).  In the non-endemic 
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communities, 80 (17.7%) of the households used public toilets while 154 (33.9%) practice 
open defecation in the bushes. Of the households with toilet facilities majority 59 (13.0%) 
used flush to septic tank, followed by 52 (11.5%) used flush to pit latrine, no household 
was engaged in the use of a bucket toilet as in table 4.4(a). Out of the total of 351 
respondents who indicated that their households had toilet facilities, more than two-thirds 
in the endemic communities 91/132 (68.9%) and non-endemic communities 171/219 
(78.1%) shared their toilet facilities with other households.  It was observed that 37/132 
(28.0%) of households in the endemic communities did not share their toilet facility 
compared to 29/219 (13.2%) in the non-endemic communities.  A few other households in 
the endemic 4/132 (3.0%) and non-endemic 19/219 (8.7%) communities shared their toilet 
facilities with the general public. Of those households that did not have toilet facilities and 
used public toilet facilities, a mean time of 12.17 ± 6.47 and 9.50 ± 7.08 minutes round 
trip to use the toilet facility was observed in the endemic and non-endemic communities 
respectively.   
In respect to handwashing at household and public toilet facilities, more than three-
quarters 366/444 (82.4%) of the facilities had handwashing devices in the endemic 
communities and less than half 125/299 (41.8%) in the non-endemic communities.  
The most common storage medium used to temporally store refuse in the households were 
sacks 297 (65.6%) in the endemic communities and rubbish bins 146 (32.2%) in the non-
endemic communities as shown in table 4.4(a).  
 
 
 
 
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Table 4.4a: Solid waste disposal practices among households in cholera endemic and non-
endemic communities – (N=906) 
Endemic Non-Endemic 
Variable   
  No. % No. % 
Type of toilet facility used  
  Flush to piped sewer system 73 16.1 3 0.7 
  Flush to septic tank 30 6.4 59 13 
  Flush to pit latrine 19 4.2 36 7.9 
  Flush don't know where it goes 2 0.4 0 0 
  Ventilated improved pit latrine 1 0.2 20 4.4 
  Pit latrine 3 0.6 52 11.5 
  Pit latrine with slab 2 0.4 29 6.4 
  Pit latrine without slab/open pit 0 0 20 4.4 
  Bucket toilet 2 0.4 0 0 
  No toilet facility used bush/field 9 2.0 154 33.9 
  No toilet facility used public toilet 312 68.9 80 17.7 
Toilet facility in households (n=351) 
  Yes, shared with other households only 91 68.9 171 78.1 
  Yes, shared with public 4 3.0 19 8.7 
  No, used by household only 37 28.0 29 13.2 
Number of households using toilet  
5(3-6) 3(2-4) 
Median (IQR) 
Location of toilet facility in households (n=335) 
 In own house/dwelling 49 37.1 90 41.1 
 In own yard 83 62.9 113 51.6 
Distance from household to public toilet 
12.17±6.47 9.50 ± 7.08 
facility and back in minutes (n=392) 
Hand washing facility at the household and  
public toilet facilities (n=743) 
  Available 366 82.4 125 41.8 
  Not available 78 17.6 174 58.2 
Medium of storage of refuse 
  Plastic bags 46 10.1 133 29.4 
  Cardboard boxes 13 2.9 7 1.5 
  Rubbish bin 88 19.4 146 32.2 
  Sacks 297 65.6 64 14.1 
  No storage-direct disposal 9 2.0 90 19.9 
  Others 0 0 13 2.9 
 
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With regards to household’s solid waste disposal practices as in table 4.4(b), it was 
observed in the endemic communities that the majority 335 (73.9%) of their refuse were 
collected mostly by motorized tricycle operators (290, 86.6%) popularly known locally as 
‘Aboboyaa’. For those whose refuse was not collected by waste companies, they were 
disposed at public dumpsites covered or uncovered (69, 15.2%), burnt, 23 (5.1%), buried, 
1(0.2%) or dump indiscriminately, 25 (5.5%). In the non-endemic communities, more than 
half 265 (58.5%) burnt their households solid waste, 58 (12.8%) dump waste 
indiscriminately, whiles 46 (10.2%) had their households waste collected by waste 
companies. Among the waste companies, Zoomlion company was the most common (32, 
69.6%) in the non-endemic communities.  
The duration of waste collection by the companies in the endemic communities depended 
mostly on when the waste bin gets full 182 (54.3%), whereas that in the non-endemic 
communities were collected weekly 46 (97.9%).  The most common reasons given by 
households not accessing the services of waste companies in the endemic communities 
was the high financial charges 55 (46.6%), whiles non-availability of waste companies 
304 (74.7%) accounted for that in the non-endemic communities. There were more public 
waste dump sites in the endemic communities 322 (71.1%) than the non-endemic 
communities 176 (38.8%). The average time taken for a round trip to the dump waste site 
and return was 17.24±6.62 in the endemic communities and 11.77±8.51 in the non-
endemic communities as shown in table 4.4(b). 
 
 
 
 
 
 
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Table 4.4b: Solid waste disposal practices among households in cholera endemic and 
non-endemic communities – (N=906) 
Endemic Non-Endemic 
Variable   
  No. % No. % 
Disposal of solid waste** 
  Collected by a waste company 335 74.0 46 10.2 
  Burned by household 23 5.1 265 58.5 
  Public dump site (covered) 2 0.4 3 0.7 
  Public dump site (opened) 67 14.8 59 13.0 
  Dump indiscriminately 25 5.5 58 12.8 
  Buried by household 1 0.2 23 5.1 
Waste collection companies available (n=381) 
  Alliance waste 0 0 11 23.9 
  AMA waste company 1 0.3 3 6.5 
  Private motorized tricycle 290 86.6 0 0 
  Zoomlion 44 13.1 32 69.6 
Duration of waste collection (n=381) 
  Daily 78 23.3 0 0 
  Weekly 74 22.1 46 97.9 
  Monthly 1 0.3 0 0 
 As to when the waste bin is full 182 54.3 0 0 
Reasons for households refuse not collected by a waste company (n=525) ** 
  Financial reasons (high service charges) 55 46.6 9 2.2 
  Waste collection companies are not available 10 8.5 304 74.7 
Waste collection companies are available but 
 43 36.4 31 7.6 
not reliable 
  No waste disposal bin 50 42.4 147 36.1 
Availability of Public waste dumpsite 
  Available   322 71.1 176 38.8 
  Not available  131 28.9 277 61.2 
Distance to public dump site and back in 
17.24±6.62 11.77±8.51 
minutes 
 **Multiple responses 
 
 
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The liquid waste disposal practices of the households were surveyed as shown in Table 
4.5. A drainage system was available in most households in the endemic communities 342 
(75.5%) than in the non-endemic communities 42 (9.3%). Out of the 342 households in 
the endemic communities that had a drainage system, 323 (94.4%) of them were mostly 
open gutters. For the 42 households with drainage in the non-endemic communities, the 
majority of 36 (83.7%) were underground drainage types.  
In the endemic communities, about three-quarters, 329 (72.6%) of the liquid waste was 
from domestic chores and 328 (72.4%) from the bath were disposed directly into the 
gutters. On the other hand, 235 (51.9%) of the liquid waste from domestic chores and 229 
(50.5%) of the bath were disposed onto the compounds in the non-endemic communities.  
 
 
 
 
 
 
 
 
 
 
 
 
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Table 4. 5: Liquid waste disposal practices among households in cholera endemic and 
non-endemic communities – (N=906) 
Endemic Non-Endemic 
Variable   
  No. % No. % 
Availability of drainage system  
  Available 342 75.5 42 9.3 
  Not available 111 24.5 411 90.7 
Type of drainage systems (n=402) 
  Open drainage (open gutter) 323 94.4 1 2.4 
  Covered drainage (covered gutter) 14 4.1 5 11.9 
 Underground drainage (pipes 4 1.2 36 83.7 
 connection to sewage) 
  Others 1 0.3 0 0 
Liquid waste disposal domestic chores 
Through the sewage system to 
  6 1.3 50 11.1 
septic tank 
  Thrown onto the street/outside 60 13.3 165 36.4 
  Thrown into gutter 329 72.6 2 0.4 
  Thrown onto the compound 58 12.8 235 51.9 
  Others 0 0 1 0.2 
Liquid waste disposal from the bath 
  Through the sewage system 6 1.3 9 2 
  Through drainage into a pit 7 1.5 77 17 
  Thrown onto the street/outside 59 13.0 138 30.5 
  Thrown into gutter 328 72.4 0 0 
  Thrown onto the compound 53 11.7 229 50.5 
 
Table 4.6 shows the environmental predisposing factors of cholera in both endemic and 
non-endemic communities. With regards to water bodies, it was observed that 203 (44.8%) 
households in the endemic communities had water bodies in their neighbourhoods 
compared to 183 (40.4%) in the non-endemic communities. The majority of the residents 
in the endemic communities lived closed to water bodies such as the sea 123 (60.6%), 
lagoons 59 (29.1%), and rivers/stream 41 (20.2%).  
In the non-endemic communities, the households lived in proximity to the lagoons 113 
(61.8%), sea 74 (40.4%), and river/streams 31 (16.8%). It was observed that an average 
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time round trip to the water body site and return was 14.70±9.06 in the endemic 
communities and 11.17±7.27 in the non-endemic communities.  
Two hundred (200, 44.1%), of the households, had a market in their neighbourhood, 
whereas there were no records of a market in the vicinity of the households interviewed in 
the non-endemic communities. For those communities in the endemic communities with 
neighbourhood markets, the majority 195 (97.5%) of their households bought foodstuff 
from those markets. Most of the respondents 160 (80.0%) who bought from the markets 
indicated that the vendors sometimes screened their smoked/fried fish from flies in the 
market. The average time taken for a round trip to the market and return was 22.07±9.53 
in the endemic communities.  
There were more abattoirs or slaughterhouses in the neighbourhoods of households in the 
endemic communities 39 (8.6%) than in the non-endemic communities 2 (0.4%). In the 
endemic communities where abattoirs were present, about half 20 (51.3%) of the 
respondents stated that the butchers never screened their meat, 14 (35.9%) indicated they 
sometimes screened and 5 (12.8%) stated they often screened. There were only two (2) 
households in the non-endemic communities who lived near an abattoir in the 
neighbourhood and one indicated the butchers always protected the meat from flies and 
dust and the other indicated they did sometimes. The average time taken for a round trip to 
the abattoir and return was 19.21±4.47 in the endemic communities and 17.5±3.54 in the 
non-endemic communities. 
 
 
Table 4. 6: Environmental predisposing factors to cholera in endemic and non-endemic 
communities – (N=906) 
Endemic Non-Endemic 
Variable   
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  No.  % No. % 
Water body in neighbourhood 
  Present 203 44.8 183 40.4 
  Not present 250 55.2 270 59.6 
Distance to water body in minutes 14.70±9.06 11.17±7.27 
Type of water body(n=386) ** 
  River/Stream 41 20.2 31 16.8 
  Lagoon 59 29.1 113 61.8 
  Sea 123 60.6 74 40.4 
Market in neighbourhood 
  Present 200 44.1 0 0 
  Not present 253 55.9 453 100 
Distance to market and back in minutes 22.07±9.53 - 
Food stuff (n=200) 
  Food stuff bought from the market 195 97.5 0 0 
  Food stuff bought from else where 5 2.5 0 0 
Vendors screen their smoked/fried fish from flies and dust (n=200) 
  Yes, always 2 1 0 0 
  Yes, often 34 17.0 0 0 
  Yes, sometimes 160 80.0 0 0 
  No, never 4 2.0 0 0 
Abattoir/slaughter house in neighbourhood 
  Present 39 8.6 2 0.4 
  Not present 414 91.4 451 99.6 
Distance from abattoir and back in 19.21±4.47 17.5±3.54 
minutes 
Butchers screen to protect the meat from flies and dust(n=41) 
  Yes, always 0 0 1 50 
  Yes, often 5 12.8 0 0 
  Yes, sometimes 14 35.9 1 50 
  No, never 20 51.3 0 0 
 **Multiple responses 
 
Table 4.7 shows cholera infection in the households and neighbourhood in the past years.   
Household respondents in the endemic 453 (100%) and non-endemic 432 (95.4%) 
communities were aware of the symptoms of cholera. Among the households surveyed, 38 
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of the households ever reported a case of cholera. Thirty-six (36, 94.7%) of the cases 
occurred in the endemic communities and 2 (5.3%) in the non-endemic communities.  
With regards to cholera cases in the neighbourhood, 189 (41.7%) of the households ever 
heard of a cholera case in the neighbourhood, 69 (15.2%) never heard of a case, and 195 
(43.1%) were not aware of a case in the endemic communities. In the non-endemic 
communities 20 (4.4%) of the households ever heard of a case of cholera in the 
neighbourhood, 302 (66.7%) never heard of a case and 131 (28.9%) were not aware of any 
case in the neighbourhood. 
Table 4. 7: Cholera infection in the households and neighbourhood – (N=906) 
Variable  Endemic Non-Endemic 
  
  No. % No. % 
Cholera symptoms awareness 
 Aware symptoms 453 100.0 432 95.4 
 Not aware of symptoms 0 0.0 21 4.6 
Cholera infection in the household 
 Ever suffered from cholera 36 7.9 2 0.4 
 Never suffered from cholera 417 92.0 451 99.6 
Cholera infection in the neighbourhood   
 Ever reported a case of cholera 189 41.7 20 4.4 
 Never reported a case of cholera  69 15.2 302 66.7 
 Don’t Know 195 43.1 131 28.9 
 
  
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4.2 Associations between socioeconomic characteristics of household respondents and cholera in 
the Greater Accra Region 
Tables 4.8 show the association between socioeconomic characteristics of the household 
respondent and cholera occurrence. A higher proportion of cholera was observed among 
households whose respondents were in the age groups of 28-37 years 11 (28.9%) and 38-
47 years 11 (28.9%) with no recorded case of cholera among those in the age group of 58-
67 years. However, the differences in the proportions of cholera in the different age groups 
were found to be statistically non-significant (p=0.232). With regards to the sex of 
respondents, female respondents 24 (63.2%) mostly recorded cholera cases in their 
households than their male 14 (36.8%) counterparts but this was found not to be 
statistically significant (p=0.555).  
More cholera cases were recorded among households whose respondents were 
cohabitating (14, 36.8%), compared to those who were married (13, 34.2%), with no 
recorded cholera cases among households whose respondents were either separated or 
divorced. A significant association was found between the marital status of the 
respondents and cholera (p=0.009).  
The religion of the respondents whose household ever had cholera were mostly Christians 
25 (65.8%), followed by Islam 13 (34.2%) with no recorded cases among those with no 
religion or those who practiced traditional religion. These differences were also found to 
be statistically significant (p=0.042).  
The ethnicity of the respondents whose households had the most cases of cholera was the 
Ga-Dangmes 14 (36.8%), with the least been the Guans 1 (2.6%). The differences in 
cholera distribution among the ethnic groups of respondents were found to be statistically 
significant (p=0.015). With the employment status of the respondents and cholera cases, it 
was found that 29 (76.3%) in informal employment were the households most affected by 
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cholera but this was not statistically significant (p=0.858) when compared to those who 
were unemployed 8 (21.0%), retired worker 0 (0.0%), or informal employment 1 (2.6%).  
With regard to education, those respondents with JSS/middle school level education 16 
(42.1%) had their households mostly affected with the least been among those with 
tertiary education 2 (5.3%). However, the differences were not statistically significant 
(p=0.670).  
In terms of the wealth status of the respondents, households with medium wealth 19 
(50.0%) were more affected by cholera, compared to poor 8 (21.0%) or wealthy 11 
(29.0%) households. This was, however, found not to be statistically significant (p=0.176).  
With regards to household income or earnings, respondents with low income (<GH¢300) 
recorded the highest cases of cholera 30 (78.9%) followed by (8, 21.0%) those with a 
medium-income (>GH¢300 - GH¢1000), and no cholera case was found among those 
within the higher income brackets (GH¢1000 - ˃GH¢2000). These differences were found 
to be statistically significant (p=0.042). Also, those respondents with a family size of 4-6 
recorded more cholera cases in the households (20, 52.6%) compared to those with smaller 
(1-3) and larger family sizes (>7). This was, however, not statistically significant 
(p=0.385). 
 
 
 
 
 
 
 
 
 
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Table 4.8a: Associations between socioeconomic characteristics of respondent and cholera 
in the Greater Accra Region 
Variables Cholera P-Value 
Yes = 38 No=868 
No. % No. % 
Age Group                                                                                                               0.232                                                                                                                                    
 18-27yrs 9 23.7 136 15.7  
 28-37yrs 11 28.9 231 26.6  
 38-47yrs 11 28.9 219 25.2  
 48-57yrs 5 13.2 136 15.7  
 58-67yrs* 0 0.0 88 10.1  
 68 yrs and above* 2 5.3 58 6.7  
Sex                                                                                                                            0.555                                             
 Male 14 36.8 280 32.3  
 Female 24  63.2 588 67.7  
Marital Status                                                                                                          0.009                                   
 Single 10 26.3 130 15.0  
 Cohabiting 14 36.8 146 16.8  
 Married 13 34.2 509 58.6  
 Separated* 0 0.0 20 2.3  
 Divorced* 0 0.0 16 1.8  
 Widowed* 1 2.6 47 5.4  
Religion                                                                                                                     0.042                                                                                           
 No Religion* 0 0.0 8 0.9  
 Christian 25 65.8 679 78.2  
 Islam 13 34.2 142 16.4  
 Traditional* 0 0.0 39 4.5  
Ethnicity                                                                                                                   0.015                            
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 Akan 8  21.0 116 13.4  
 Ewe 5  13.2 83 9.6  
 Ga-Dangme 14 36.8 542 62.4  
 Guan* 1  2.6 5 0.6  
 Mole-Dagbon 10  26.3 119 13.7  
 Others* 0  0.0 3 0.3  
Employment                                                                                                             0.858                        
 Unemployed 8  21.0 176 20.3  
 Retired Worker* 0  0.0 17 2.0  
 Formal Employment* 1  2.6 57 6.5  
 Informal Employment 29  76.3 618 71.2  
Educational Level                                                                                                   0.670                         
 No Formal Education 5  13.2 142 16.4  
 Primary Education 10 26.3 181 20.8  
 JSS/Middle School 16 42.1 300 34.6  
Education 
 Senior High Education 5 13.2 181 20.8  
 Tertiary Education* 2  5.3 64 7.4  
P-value is significant if p < 0.05, *Fishers Exact Test 
Table 4.8b: Associations between socioeconomic characteristics of respondents and 
cholera in selected households in the Greater Accra Region 
Variables                          Cholera P-Value 
      Yes = 38       No = 868 
 No. % No. %  
Wealth Status     0.176 
Poor 8 21.0 299 34.5  
Medium 19 50.0 324 37.3  
Wealthy 11 29.0 245 28.2  
Income     0.042 
Low income (<Gh¢300) 30 78.9 486 56.0  
Medium income (>Gh¢300 - Gh¢1000) 8 21.0 322 37.1  
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High income (>Gh¢1000 - Gh¢2000)* 0 0.0 50 5.8  
Highest income (>Gh¢2000)* 0 0.0 10 1.1  
Family Size     0.385 
1-3 14 36.8 270 31.1  
4-6 20 52.6 431 49.7  
7+* 4 10.5 167 19.2  
P value is significant if p < 0.05, *Fishers Exact Test 
 
A penalized multivariable logistic regression model was used to determine the impact of 
each socioeconomic predictor variable on cholera risk in the study communities as shown 
in Table 4.9.  
With regards to the marital status, households of cohabiting respondents were significantly 
protective by 67.0% against cholera compared to households of respondents who were 
single (OR=0.33, 95% CI: 0.14-0.75, p=0.009).  However, after adjusting for other 
predictor variables found households with respondents who were married to be 64.0% 
protective against cholera and were statistically significant (AOR=0.36, 95% CI: 0.14-
0.90, p=0.028).  
Respondents with high income were 65.0% protected against cholera compared to their 
counterparts who had low income (OR=0.35, 95% CI: 0.16-0.77, p=0.008). This 
association was not significant after adjusting for other predictor variables (AOR=0.48, 
95% CI: 0.20-1.16, p=0.102).  
Other predictor variables including; religion, level of education, employment and wealth 
status of respondents were found not to be significantly associated with cholera as in Table 
4.9. 
Table 4.9: Assessing the association between socioeconomic factors and cholera using a 
penalized multivariable logistic regression model 
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Variable OR (95% CI) P-value AOR (95% CI) P-value 
Marital status  
 Single 1  1  
 Married 1.23 (0.54-2.82) 0.624 0.36 (0.14-0.90) 0.028 
 Co-habiting 0.33 (0.14-0.75) 0.009 1.10 (0.44-2.65) 0.857 
 Separated 0.3 (0.02-5.37) 0.416 0.35 (0.02-6.76) 0.491 
 Divorced 0.38 (0.02-6.73) 0.507 0.41 (0.02-7.90) 0.558 
 Widow 0.39 (0.07-2.24) 0.293 0.46 (0.07-2.89) 0.405 
Religion 
 No Religion 1  1  
 Christian 0.64 (0.04-11.36) 0.760 0.88 (0.04-17.30) 0.935 
 Islam 1.61 (0.09-29.45) 0.748 1.92 (0.09-39.27) 0.671 
 Traditional 0.22 (0-11.62) 0.450 0.39 (0.01-22.94) 0.649 
Level of Education 
 None 1  1  
 Primary 1.5 (0.52-4.3) 0.452 1.23 (0.41-3.66) 0.708 
 JSS/Middle School 1.42 (0.53-3.81) 0.483 0.97 (0.33-2.83) 0.958 
 SHS 0.79 (0.24-2.61) 0.693 0.57 (0.15-2.16) 0.408 
 Tertiary 1 (0.22-4.61) 0.996 1.16 (0.16-8.25) 0.883 
Employment 
 Unemployed 1  1  
 Retired worker 0.59 (0.03-10.72) 0.724 1.15 (0.05-24.44) 0.927 
 Formal Employed 0.54 (0.09-3.15) 0.495 1.27 (0.14-11.73) 0.834 
 Informal Employed 0.99 (0.45-2.16) 0.981 1.23 (0.52-2.89) 0.637 
Income 
 Low 1  1  
 High 0.35 (0.16-0.77) 0.008 0.48 (0.20-1.16) 0.102 
Wealth Index 
 Poor 1  1  
 Medium 2.12 (0.93-4.81) 0.073 1.69 (0.73-3.94) 0.224 
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 Wealthy 1.65 (0.67-4.07) 0.276 1.51 (0.56-4.05) 0.418 
OR – Odds Ratio, AOR – Adjusted Odds Ratio, CI – Confidence Interval, Significant (p<0.05) 
 
4.3 Associations between behavioural factors and cholera in the Greater Accra Region 
4.3.1 Drinking water sources and handling practices among households and cholera 
The water sources and handling practices of household members pose a risk to cholera as 
shown in Table 4.10a. It was observed that households whose main source of drinking 
water was sachet water recorded the highest cases of cholera 32 (84.2%) compared to 
those who drank private piped water 3 (7.9%), public pipe 2 (5.3%), or unprotected dug 
well 1 (2.6%). This was found to be statistically significant (p=0.002). A higher proportion 
of cholera cases 35 (92.1%) were also found to be associated with households that had 
their main drinking water sources located in the household dwelling than those in the yard 
0 (0.0%) or elsewhere 3 (7.9%) and was found to be statistically significant (p=0.002).  
Among the households, more cases of cholera were detected among households that drank 
untreated water 5 (83.3%) than those that drank treated water 1 (16.7%). However, this 
was tested statistically and found not to be significant (p=0.516).  Drinking from a covered 
storage vessel recorded more cases of cholera 5 (83.3%) than from uncovered 1 (16.7%) 
but was not statistically significant (p=0.442). 
4.3.2 Food eating habits and cholera 
The food eating habits of the households could pose a risk to cholera as shown in Table 
4.10a. With the food eating habit, most households ate food cooked from home and 
outside the home and a recorded majority of the cholera cases 32 (84.2%) than the 
households that ate only food cooked at home 4 (10.5%) or from outside home 2 (5.3%). 
The differences were statistically significant (p=0.003).  
Most households cook food in the yard, whiles others cooked inside the house or in a 
separate building. It was observed that those who cooked inside the house recorded most 
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cases of cholera 22 (61.1%). The differences in the distribution of the cholera cases by 
location were found to be statistically significant (p=0.008).  
Most households ate leftover foods, and cholera was found to be common 36 (94.7%) 
among households that ate left-over foods. Eating leftover foods was however found not to 
be associated with cholera (p=0.157). The main treatment method of the left-over food 
before eating was reheating to boil recorded the highest proportion of cholera cases 36 
(100.0%) compared to the others, however was found not to be significantly associated 
with cholera (p=1.000).   
With regards to the handwashing before meals, the majority of household members who 
washed in a bowl of water had cholera 28 (73.7%) compared to those who used the other 
methods of hand washing. The differences, however, were found not to be statistically 
significant (p=0.298). 
4.3.3 Solid waste disposal practices and cholera  
As shown in Table 4.10b, the location of toilet facility in own house dwelling had more 
cases of cholera 7 (77.8%) than those located in the yard 2 (22.2%) or elsewhere 0 (0.0%). 
Also, toilet facilities that had a handwashing device, recorded more cases of cholera 31 
(93.9%) than those without a handwashing device 2 (6.1%) and was found to be 
statistically significant (p=0.001).  
Various mediums were employed in the storage of refuse as in Table 4.10. Those who 
stored their refuse in sacks had a higher proportion of cholera cases 29 (76.3%) than the 
others and was found to be statistically significant (p=0.001).   
4.3.4 Liquid waste disposal and cholera  
Table 4.10b shows the association between household liquid waste disposal and cholera. 
Among the several methods employed in liquid waste disposal from the households, the 
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most predominantly used was the disposal into the gutters which recorded the highest 
cholera cases of 31 (81.6%). When compared to the other methods of disposal was found 
to be statistically significant (p<0.001). 
  
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Table 4.10a: Associations between household behavioural factors and cholera in the 
Greater Accra Region 
Variables Cholera P-Value 
Yes = 38 No=868 
No. % No. %  
Drinking water sources and handling practices 
Main source of drinking water                                                                                                      0.002 
 Private pipe* 3  7.9 111  12.8  
 Public pipe* 2  5.3 220  25.4  
 Unprotected dug well* 1 2.6 69 7.9  
 Sachet water 32 84.2 468 53.9  
Location of source of drinking water                                                                                            0.002 
 In own house/dwelling 35 92.1 568 65.4  
 In own yard* 0 0.0 11 1.3  
 Elsewhere* 3 7.9 289 33.3  
Water treatment(n=406)                                                                                                                 0.516 
 Drinking treated water* 1 16.7 45 11.3  
 Drinking untreated water 5 83.3 355 88.7  
Drinking water storage vessel(n=406)                                                                                           0.442 
 Covered 5  83.3 379 90.9  
 Uncovered* 1  16.7 38 9.1  
Food eating practices 
Food eating habit                                                                                                                             0.003 
 Only eat food cooked at home* 4  10.5 195 22.5  
 Eat food cooked from home and 32 84.2 671 77.3  
outside 
 Only eat food from outside* 2 5.3 2 0.2  
Location where food is cooked                                                                                                        0.008 
 Inside the house/dwelling 22 61.1 318 36.7  
 In a separate building* 2 5.6 163 18.8  
 Outdoors (in the yard) 12 33.3 385 44.5  
Leftover foods                                                                                                                                   0.157 
 Eaten 36 94.7 853 98.3  
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 Not eaten* 2  5.3 15 1.7  
Method of treating left over foods before eating                                                                           1.000 
 Eaten cold in the next meal* 0 0.0 22 2.6   
 Reheated to boil before eaten 36 100.0 816 95.5  
 Warmed in the microwave before 0 0.0 16 1.9  
eaten* 
Method of washing hands before eating                                                                                         0.298 
 Wash hands in a bowl of water 28 73.7 528 60.8       
 Wash hands with soap in a bowl of 9 23.7 223 25.7  
water 
 Wash hands under running water* 1 2.6 83 9.6  
 Wash hands with soap and water* 0 0.0 34 3.9  
under running water 
P value is significant if p < 0.05, *Fishers Exact Test 
 
 
  
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Table 4.10b: Associations between household behavioural factors and cholera in the 
Greater Accra Region  
Variables Cholera P-Value 
Yes = 38 No=868 
No. % No. %  
 Solid waste disposal factors 
Location of toilet facility                                                                                                                0.103 
 In own house/dwelling 7  77.8 132 38.6  
 In own yard* 2  22.2 194 56.7  
 Elsewhere* 0  0.0 16 4.7  
Hand washing facility in the toilet                                                                                                 0.001 
 Available 31 93.9 460 64.8  
 Not available* 2 6.1 250 35.2  
Medium of storage of refuse                                                                                                          0.001 
 Plastic bags* 3 7.9 176 20.3  
 Cardboard boxes* 0 0.0 20 2.3  
 Rubbish bin 5  13.2 229 26.4  
 Sacks 29 76.3 332 38.3  
 No storage- direct disposal* 1 2.6 98  11.3  
 Others* 0  0.0 13  1.5  
Liquid waste disposal factors 
Method of disposal                                                                                                                        <0.001 
 Through the sewage system* 0  0.0 15 1.7  
 Through drainage into a pit* 1  2.6 83 9.6  
 Thrown onto the street/outside* 1 2.6 196 22.6  
 Thrown into gutter 31 81.6 297 34.2  
 Thrown onto the compound 5 13.2 277 31.9  
P value is significant if p < 0.05, *Fishers Exact Test 
 
A penalized multivariable logistic regression model was further used to identify the 
behavioural risk factors for cholera infection in the study communities as shown in Table 
4.11.  
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With the eating habits of households, the odds of having cholera was 43.44 times more 
likely among households that only ate food from outside the home compared to those who 
ate food cooked only at home (OR=43.44, 95% CI:5.96-316.73, p<0.001).  This was not 
significant after adjusting for other predictor variables.  
Households that cooked food in the yard and a separate building (detached kitchen) were 
54% and 78% less likely to have suffered from cholera respectively compared to those that 
cooked inside the house dwelling. After adjusting for other predictor variables were found 
to be significant for cooking outdoors (AOR=0.42, 95% CI: 0.21-0.86, p=0.017) and 
cooking in a separate building (AOR=0.42, 95% CI: 0.06-0.82, p=0.024).  
Predictor variable such as handwashing practice before meals were found not to be 
associated with cholera.  
Table 4.11: Assessing the association between behavioural factors and cholera using 
penalized multivariable logistic regression model 
Variable OR (95% CI) P-value AOR (95% CI) P-value 
Food eating habits 
   
Only eat food cooked at 1 1 
home 
 Eat food cooked from home 2.1 (0.77-5.71) 0.145 2.09 (0.76-5.81) 0.155 
and outside 
 
Only eat food from outside 43.44 (5.96-316.73) <0.001 - - 
home 
Location where cooking is done 
   
Inside the house/dwelling 1 1 
 
In a separate building 0.22 (0.06-0.81) 0.023 0.22 (0.06-0.82) 0.024 
 
Outdoors (in the yard) 0.46 (0.23-0.93) 0.031 0.42 (0.21-0.86) 0.017 
Hand washing practice before eating 
   
Wash hands in a bowl of 1 1 
water 
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Wash hands with soap in a 0.79 (0.37-1.67) 0.534 0.94 (0.42-2.10) 0.876 
bowl of water 
 
Wash hands under running 0.33 (0.06-1.75) 0.194 0.30 (0.06-1.60) 0.160 
water 
  Wash hands with soap 0.27 (0.02-4.5) 0.361 0.23 (0.01-3.93) 0.312 
under running water 
OR – Odds Ratio, AOR – Adjusted Odds Ratio, CI – Confidence Interval, Significant (p<0.05) 
4.4 Assessment of the bacteriological quality of drinking water and cholera risk in Greater Accra 
Region 
The household drinking water quality was assessed for the presence of Vibrio cholerae 
strains and indicator (coliform) bacteria (Tables 4.12 and 4.13).  High levels of total 
coliform counts (TCC) were observed in ten communities with a mean count of 7.73 log 
cfu/100ml and 9.86 log cfu/100ml respectively in the dry and wet seasons as shown in 
Table 4.12. Feacal coliforms (FCC) were generally present in the private pipe water 
sources in both seasons except in a few communities: Agege and Dansoman which did not 
record any counts in both seasons. Vibrio counts (VC) were absent in the private pipe 
water sources except in Mamprobi which recorded 6.91 log cfu/100ml in the wet season. 
The direct public pipe also had a high mean TCC of 7.82 log cfu/100ml in the dry season 
and 9.64 log cfu/100ml in the wet season.  The mean FCC was also found to be 5.24 log 
cfu/100ml and 10.06 log cfu/100ml respectively in the dry and wet seasons. No VC was 
observed in the communities (Agbogbloshie and James Town) during both seasons.  When 
the differences between the mean rank score of the log of TCC (ꭓ2 =0.182, p=0.669), FCC 
(ꭓ2=2.591, p=0.107) and VC (ꭓ2=0.200, p=0.655) were assessed among the direct water 
sources there were no statistical differences as shown in Table 4.14.  
In the endemic communities’ also household drinking water stored in vessels was also 
analyzed in both seasons. Of the 216 water samples; 110 were private pipes, 23 were 
public pipes, and 83 were sachet water. The highest mean TCC and FCC in both seasons 
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were found in stored public pipe water compared to stored private pipe water and sachet 
water in the households (Table 4.12). Suspected vibrio counts were present in all 
household stored drinking water samples (Table 4.12). However, when the differences 
between the bacterial mean counts were assessed for the stored household drinking water, 
the mean rank score of the log of TCC (ꭓ2=7.704, p=0.021), FCC (ꭓ2 =2.591, p<0.001) and 
VC (ꭓ2=12.101, p=0.002) differed significantly (Table 4.14). The bacterial counts were 
generally higher in the wet season than the dry season during the period for both the water 
collected directly from the source and that stored in vessels in the households. 
In the non-endemic communities also, 24-direct water sources were sampled from private 
pipe (4), public pipe (16), and unprotected wells (4) in both seasons (Table 4.13). The 
direct private piped water sources were found in Dawhenya and Kofikope and recorded a 
mean TCC of 8.57 log cfu/100ml in the dry season and 10.12 log cfu/100ml in the wet 
season. The mean FCC was 4.50 log cfu/100ml and 8.61 log cfu/ml in the dry and wet 
seasons respectively, with no recorded VC. The public pipe samples recorded a mean FCC 
of 8.44 log cfu/ml in the dry season and 9.64 log cfu/ml in the wet season. The mean FCC 
was 5.24 log cfu/100ml in the dry season and 9.39 log cfu/100ml in the wet season, 
although six of the communities (Dawa, Dogobom, Adedetsekope, Asigbeykope, 
Awhiam, Adjumanikope) did not record any feacal coliforms. Anyaman East community, 
on the other hand, recorded the highest TCC and FCC in both seasons. Except for Awhiam 
community that had a VC of 6.91 log cfu/100ml, all other communities did not record any 
counts. The unprotected wells also recorded a mean TCC of 8.61 log cfu/100ml in the dry 
season and 10.20 log cfu/100ml in the wet season. The mean FCC was 5.53 log cfu/100ml 
in the dry season and 9.45 log cfu/100ml in the wet season with a mean VC of 10.31 log 
cfu/100ml. The differences in the mean rank score between the log of FCC among the 
direct water sources were assessed and found to be statistically significant (ꭓ2 = 10.212, 
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p=0.006).  Whereas, the mean rank score of the log of TCC and VC among the direct 
water sources did not differ (ꭓ2=5.171, p=0.075: ꭓ2=2.029, p=0.363) as shown in Table 
4.15.     
The two hundred and sixteen (216) household stored drinking water in the non-endemic 
communities made up of; 34 private piped water, 136 public pipe water, 36 unprotected 
dug well, 8 dam water, and 2 sachet waters stored in the household. Except VC which was 
not found in sachet water, TCC, FCC, and VC were generally present in all household 
water stored in vessels for the period. The bacterial counts in the stored water samples 
were higher than those collected from the direct water sources. The TCC and FCC were 
generally observed to be higher during the wet season than the dry season. The differences 
between the bacterial mean counts were assessed for the household drinking water stored 
and a statistically significant difference was found in the mean rank score of the log of 
TCC and FCC (ꭓ2=14.165, p=0.007: ꭓ2=33.901, p<0.001), whiles the mean rank scores for 
log of VC (ꭓ2=6.051, p=0.195) was not significant (Table 4.15).
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Table 4.12: Mean log of bacterial counts in the dry and wet seasons across some selected background characteristics in Endemic communities 
Study variable Characteristics TCC (log cfu/ 100 ml) FCC (log cfu /100 ml) VC (log cfu /100 ml) 
Dry Wet Dry Wet Dry Wet 
Direct water Community Mean(sd) Mean(sd) Mean(sd) Mean(sd) Mean(sd) Mean(sd) 
sources 
Private pipe Adabraka 8.16 10.04 5.35 9.30 0 0 
 Nungua 7.24 12.10 4.50 10.57 0 0 
 Agege 8.07 8.85 0 0 0 0 
 Chorkor 7.60 8.52 4.60 0 0 0 
 Dansoman 7.74 9.39 0 0 0 0 
 Kanehsie  8.16 10.93 0 6.91 0 0 
 Mamobi 8.04 10.46 4.79 8.29 0 0 
 Mamprobi  6.91 9.61 5.13 0 0 6.91 
 Nima 7.60 8.52 4.79 8.52 0 0 
 Teshie 7.74 10.20 4.50 10.13 0 0 
 
Total 7.73(0.41) 9.86(0.36) 4.81(0.32) 8.95(1.34) 0 6.91 
 Public pipe Agbogbloshie 8.04 10.60 5.13 10.34 0 0 
 James town 7.60 10.78 4.79 9.80 0 0 
 
Total 7.82(0.31) 9.64(1.29) 5.24(0.65) 10.06(0.38) 0 0 
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Water stored in Private pipe  8.26(0.38) 10.76(1.13) 5.53(0.45) 10.04(1.09) 2.40 (0.69) 9.91(1.15) 
vessels 
 
Public pipe  8.49(0.37) 11.75(0.38) 5.80(0.44) 11.16(0.76) 1.77(0.88) 9.76(1.52) 
 
Sachet 8.45(0.39) 10.51(1.08) 5.60(0.41) 10.18(0.99) 2.29(0.71) 10.49(0.57) 
Note: All bacterial counts have been log transformed, TCC=Total coliform count, FCC=Faecal coliform count, VC=Vibrio count  
 
 
Table 4.13: Mean log of bacterial counts in the dry and wet seasons across some selected background characteristics in non-endemic 
communities 
Study variable Characteristics TCC (log cfu/ 100 ml) FCC (log cfu /100 ml) VC (log cfu /100 ml) 
Dry Wet Dry Wet Dry Wet 
Direct water sources Community Mean(sd) Mean(sd) Mean(sd) Mean(sd) Mean(sd) Mean(sd) 
Private pipe Dawhenya 8.48 10.09 0 8.70 0 0 
 Kofikope 8.66 10.16 4.50 8.52 0 0 
 Total 8.57(0.13) 10.12(0.06) 4.50 8.61(0.13) 0 0 
Public pipe Addokope 8.63 9.21 4.79 0 0 0 
 Dawa 8.29 0 0 0 0 0 
 Dogobom 8.34 8.00 0 0 0 0 
 Adedetsekope 8.27 0 0 0 0 0 
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Anyaman East 8.81 10.60 5.70 9.39 0 0 
 Asigbeykope 8.57 0 0 0 0 0 
 
Awhiam 8.48 10.76 0 0 0 6.91 
 Adjumanikope 8.16 0 0 0 0 0 
 Total 8.44(0.22) 9.64(1.29) 5.24(0.65) 9.39 0 6.91 
Unprotected Dug well Angomya-Ada 8.41 11.00 5.67 9.80 0 10.31 
 Kopeheum Kasseh 8.81 9.39 5.39 9.10 0 0 
 Total 8.61(0.28) 10.20(1.14) 5.53(0.19) 9.45(0.49) 0 10.31 
Water stored in vessels Private pipe  8.92(0.26) 11.10(0.68) 6.16(0.36) 10.27(0.71) 1.84(0.62) 9.92(1.24) 
 Public pipe 8.77(0.26) 10.45(1.13) 6.03(0.34) 9.59(1.08) 2.23(0.92) 9.73(1.08) 
 
Sachet  8.88 12.21 5.74 10.93 0 0 
 Unprotected dug well  8.81(0.31) 11.16(0.61) 6.10(0.40) 10.39(0.77) 2.48(0.59) 11.19(0.78) 
 Dam  9.05(0.23) 11.83(0.13) 6.44(0.23) 10.60(0.18) 2.91(0.77) 9.24(0.34) 
Note: All bacterial counts have been log transformed, TCC=Total coliform count, FCC=Faecal coliform count, VC=Vibrio count 
 
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Table 4.14: Assessing the differences in log bacterial count among household drinking 
water stored in vessels and from direct water sources in endemic 
communities   
 n Rank Sum ꭓ2 with ties P-Value 
Total Coliform count 
Direct source                                                                                                    0.182             0.669 
 Private Pipe 4 55.50   
 Public Pipe 20 244.50   
Water stored in vessels                                                                                   7.704              0.021 
 Private Pipe Stored 110 12068.50   
 Public Pipe Stored 23 3198.50   
 Sachet water 83 8169   
Faecal coliform count 
Direct source                                                                                                   2.591              0.107 
 Private Pipe 4 70.50   
 Public Pipe 20 229.50   
Water stored in vessels                                                                                  17.156           <0.001 
 Private Pipe Stored 110 12170   
 Public Pipe Stored 23 3532.50   
 Sachet water 83 7733.50   
Suspected Vibrio count 
Direct source                                                                                                   0.200              0.655 
 Private Pipe 4 48   
 Public Pipe 20 252   
Water stored in vessels                                                                                  12.101             0.002 
 Private Pipe Stored 110 12094   
 Public Pipe Stored 23 3289   
 Sachet water 83 8053   
 
 
 
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Table 4.15: Assessing the differences in log bacterial count among household drinking 
water stored in vessels and from direct water sources in non-endemic 
communities 
 n Rank Sum ꭓ2 with ties P-Value 
Total Coliform count 
Direct source                                                                                                       5.171            0.075 
 Private pipe 4 67.50   
 Public pipe 16 163   
 Unprotected dug well 4 69.50   
Water stored in vessels                                                                                      14.165           0.007 
 Unprotected dug well  36 4423.0   
 Dam water  8 1189.5   
 Private pipe 34 4357.5   
 Public pipe  136 13168.0   
 Sachet 2 298.0   
Faecal Coliform count 
Direct source                                                                                                      10.212           0.006 
 Private pipe 4 63.50   
 Public pipe 16 155.50   
 Unprotected dug well 4 81   
Water stored in vessels                                                                                      33.901         <0.001   
 Unprotected dug well  36 4972.0   
 Dam  8 1257.5   
 Private pipe 34 4743.0   
 Public pipe 136 12205.5   
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 Sachet 2 258.0   
Suspected Vibrio count 
Direct source                                                                                                       2.029            0.363 
 Private pipe 4 46   
 Public pipe 16 195.50   
 Unprotected dug well 4 58.50   
Water stored in vessels                                                                                       6.051            0.195 
 Unprotected dug well 36 4206.5   
 Dam 8 1152.0   
 Private pipe  34 3525.5   
 Public pipe  135 14226.0   
 Sachet 2 110.0   
 
Table 4.16 & 4.17 shows the different coliform and other bacteria isolated from the 
household drinking water in the endemic and non-endemic communities. Out of 120 
household drinking water samples that were collected, in the endemic communities for 
each of the seasons, 76 (63.3%) and 82 (68.3%) positive growths were found respectively 
in the wet and dry seasons. In some of the water samples, multiple growths of the bacteria 
were found. Among the positive isolates, the predominant organism occurring in both 
seasons was Klebsiella pneumoniae 24 (31.6%) followed by Escherichia coli 13 (17.1%). 
There were no confirmed Vibrio cholerae strains in the household drinking water samples 
in the endemic communities. 
Table 4.16: Microorganisms isolated from the household drinking water samples collected 
in the endemic communities 
                       Wet Season 
Organisms Frequency Percent 
Acinetobacter baumanni/calcoaceticus 1 1.3 
Citrobacter freundii 6 7.9 
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Enterococcus faecalis 1 1.3  
Enterobacter sp 9 11.8 
Enterococcus sp 3 4.0 
Escherichia coli 13 17.1 
Klebsiella pneumoniae 24 31.6 
Proteus mirabilis 8 10.5 
Proteus vulgaris 1 1.3 
Pseudomonas aeruginosa 9 11.8 
Serratia ficaria 1 1.3 
Total 76 100.0 
                         Dry Season 
Acinetobacter baumanni/calcoaceticus 3 3.7 
Citrobacter freundii 7 8.5 
Enterobacter sp 11 13.4 
Enterococcus sp 10 12.2 
Escherichia coli 16 19.5 
Klebsiella pneumoniae 23 28.1 
Proteus mirabilis 7 8.5 
Pseudomonas aeruginosa 5 6.1 
Total 82 100.0 
 
A hundred and twenty (120) drinking water samples were sampled from the non-endemic 
communities in each of the seasons (wet and dry). A hundred and four (104, 86.7%) 
isolates were identified during the wet season (Table 4.17).  Of the 11 different bacteria 
identified in the wet season, Escherichia coli 18 (17.3%) was the most common isolate 
followed by Klebsiella pneumoniae 17 (16.4%). In the dry season, 88 (73.3%) had 
positive growth with  Klebsiella pneumoniae (22.7%) as the most frequently occurring 
followed by Escherichia coli (18.2%).  There were also multiple growths in some of the 
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water samples. No Vibrio cholerae strains were isolated in the household drinking water 
samples. 
Table 4.17: Microorganisms isolated from the household drinking water samples collected 
in the non-endemic communities  
                       Wet Season 
Organisms Frequency Percent 
Acinetobacter baumanni/calcoaceticus 2 1.9 
Citrobacter freundii 7 6.7 
Enterobacter sp 13 12.5 
Enterococcus sp 11 10.6 
Escherichia coli 18 17.3 
Klebsiella pneumoniae 17 16.4 
Proteus mirabilis 15 14.4 
Proteus vulgaris 2 1.9 
Pseudomonas aeruginosa 16 15.4 
Staphylococcus aureus 2 1.9 
Yersinia pestis 1 1.0 
Total 104 100.0 
                         Dry Season 
Aeromonas hydrophilia 2 2.3 
Acinetobacter baumanni/calcoaceticus 1 1.1 
Citrobacter freundii 7 8.0 
Enterobacter sp 14 15.9 
Enterococcus sp 10 11.4 
Escherichia coli 16 18.2 
Klebsiella pneumoniae 20 22.7 
Proteus mirabilis 7 8.0 
Pseudomonas aeruginosa 11 12.5 
Total 88 100.0 
 
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4.5 Environmental assessment for the presence of Vibrio cholerae O1/O139 toxigenic strains in 
the water bodies in the communities 
The survey involved the collection of environmental water samples from selected 
communities where water bodies were present to test for the presence of V. cholerae 
O1/O139 or Non-V. cholerae O1/O139 and other vibrio species that may pose a risk to 
cholera transmission in the endemic or non-endemic communities. All 15 water bodies 
such as lagoons, estuaries, rivers/streams, and dams were identified in the endemic and 
non-endemic communities (Table 4.18 & 4.19).   
A total of 30 environmental water samples were collected from the water bodies during 
the wet season (June to August 2019) and dry season (January to March 2020). The 15 
water samples collected and cultured during the wet season did not yield V. cholerae 
O1/O139 or Non-V. cholerae O1/O139. However, 26.7% (4/15) of the water bodies 
sampled contained Vibrio fluvialis. These were isolated from Korle estuarine, Chemunaa 
estuaries, Sango lagoon, and estuarine in the cholera endemic communities (Table 4.18).  
OmpW, O1rfb, O139rfb, and ctxA genes for V. cholerae, were not detected using the 
uniplex PCR. 
 
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Table 4.18: Detection and Isolation of V. cholerae O1, O139, and non-O1/non-O139 from environmental water samples in cholera endemic and non-
endemic communities during the wet season 
    
Culture PCR 
    
S/N Endemic Type of Water Vibrio Vibrio Vibrio Other vibrio  OmpW O1rfb O139rfb ctxA 
Community Body cholerae cholerae cholerae Non 
O1 O139 O1/O139 
1 James Town Korle Lagoon - - - -  - - - - 
2 James Town Korle Estuarine - - - Vibrio fluvalis  - - - - 
Beach 
3 Agbogbloshie   Odorna River - - - -  - - - - 
4 Chorkor  Chemunaa - - - -  - - - - 
Lagoon 
5 Chorkor Chemunaa - - - Vibrio  - - - - 
Estuarine fluvialis 
6 Adabraka Odorna River - - - -  - - - - 
(Upper stream)  
7 Adabraka Odorna River - - - -  - - - - 
(Lower stream) 
8 Teshie South Sango Lagoon - - - Vibrio  - - - - 
fluvialis 
9 Teshie South Sango Estuarine - - - Vibrio  - - - - 
fluivalis 
 Non-Endemic           
Community 
10 Dawa Dam  - - - -  - - - - 
11 Dogobom Dam - - - -  - - - - 
12 Awhiam Dam - - - -  - - - - 
13 Anyaman East Dam - - - -  - - - - 
14 Angomya-Ada River (Upper) - - - -  - - - - 
15 Angomya-Ada River (Lower) - - - -   - - - 
‘-’indicates no detection or isolation, ‘+’indicates detection or isolation. 
 
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During the dry season, a total of 15 water samples were collected from the same sites as in 
the wet season. Of the 15 samples analysed, only 2 (13.3%) were positive for V. cholerae 
O1 and 1 (6.7%) positive for OmpW (Table 4.19).  Vibrio algionolyticus was also isolated 
from the Sango lagoon and estuarine.  
Uniplex PCR for the amplification of the genes encoding OmpW (310bp), O1rfb (200bp), 
O139rfb (450bp), and ctxA (310bp) was performed to confirm the presence of these 
pathogens. In all, 3 (20%) OmpW (310bp) and 2 (13.3%) O1rfb (200bp) showed positive 
bands for V. cholerae (Figures 4.1 – 4.6). Vibrio cholerae O1 non-toxigenic strains (O1rfb 
(200bp), OmpW (310bp) gene-positive, and ctxA (310bp) negative) were detected in two 
of the water samples in Awhiam and Dawa in the cholera non-endemic community (Table 
4.19). Non-V. cholerae O1/O139 (OmpW (310bp) positive gene) was also detected in the 
water sample in Odorna river in the cholera endemic community (Table 4.19).
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Table 4.19: Detection and Isolation of V. cholerae O1, O139, and non-O1/non-O139 from environmental water samples in cholera endemic and 
non-endemic communities during the dry season 
                            
                                                Culture                             PCR  
S/N Endemic Type of Water Vibrio Vibrio Vibrio Other vibrio  OmpW O1rfb O139rfb ctxA 
Community Body cholerae cholerae cholerae Non 
O1 O139 O1/O139 
1 James Town Korle Lagoon - - - -  - - - - 
2 James Town Korle Estuarine - - - -  - - - - 
3 Agbogbloshie Odorna River - - - -  - - - - 
4 Chorkor Chemunaa - - - -  - - - - 
Lagoon 
5 Chorkor Chemunaa - - - -  - - - - 
Estuarine 
6 Adabraka Odorna River - - - -  + - - - 
(Upper stream) 
7 Adabraka Odorna River - - - -  - -  - 
(Lower stream) 
8 Teshie South Sango Lagoon - - - Vibrio  - - - - 
algionolyticus 
9 Teshie South Sango Estuarine - - - Vibrio  - - - - 
algionolyticus 
 Non-Endemic           
Community 
10 Dawa Dam + - - -  + + - - 
11 Dogobom Dam - - - -  - - - - 
12 Awhiam Dam + - - -  + + - - 
13 Anyaman East Dam - - - -  - - - - 
14 Angomya-Ada River (Upper) - - - -  - - - - 
15 Angomya-Ada River (Lower) - - - -  - - - - 
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‘-’indicates no detection or isolation, ‘+’indicates detection or isolation 
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M     9   10   11   12   13    14    15   16    17    18    19   20   21   22   23 
200bp 
 
Figure 4.1: Uniplex PCR products of O1rfb [200bp] amplified from environmental water 
samples and analyzed by 1.5% agarose gel electrophoresis. Lane M, is 50bp 
molecular base marker. Lane 9 is a positive control. Lane 15 is positive and 
corresponds to S/N 12 in table 4.18. Lanes 10 to 14 & 16 to 23 are negative. 
Lane 23 is the negative control. 
 
 
 
   M           1              2           3             4          5          6          7          8        
310bp 
 
Figure 4.2: Uniplex PCR products of ctxA [310bp] amplified from environmental water 
samples analyzed by 1.5% agarose gel electrophoresis. Lane M, is 50bp 
molecular base marker. Lane 1 is a positive control. Lanes 2 to 7 are 
negatives. Lane 8 is a negative control. 
 
 
M     9   10   11   12    13    14    15    16    17     18     19    20    21    22   23      
310 bp 
 
Figure 4.3: Uniplex PCR products of ctxA [310bp] amplified from environmental water 
samples analyzed by 1.5% agarose gel electrophoresis. Lane M, is 50bp 
molecular base marker. Lane 9 is a positive control. Lane 10 to 23 are 
negatives. Lane 23 is a negative control. 
 
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4.6 Environmental assessment of the sanitation and cholera risk in the communities    
An assessment of the sanitation situation of the households and their neighbourhood was 
conducted for both endemic and non-endemic communities. Of the ten items which 
covered responses in the water supply pipelines, refuse, sewage, and excreta waste 
disposal practices, more than half 300 (66.2%) of the households in the endemic 
communities recorded poor environmental sanitation, 153 (33.8%) had moderate 
environmental sanitation and no community had good sanitation as shown in Table 4.20.  
All households in Adabraka, Agbogbloshie, Chorkor, Maamobi, and Nima recorded 100% 
poor environmental sanitation. Agege, Dansoman, James Town, Mamprobi, Nungua 
recorded less than 50% poor environmental sanitation and above 50% moderate sanitation. 
Teshie, on the other hand, had a majority of (56, 67.9%) of the households having poor 
sanitation conditions and 32.1% reported moderate conditions.  Kaneshie had 100.0% of 
the households reporting moderate sanitation.  
In most of the reported poor sanitation communities, the water pipeline network 
connections were laid in open gutters which were choked with refuse. Most of the gutters 
were choked with garbage, consisting of black polythene bags some containing human 
excreta, plastic bottles, and sachet water rappers indiscriminately dumped in the drains.  
Some waste dumpsites were observed to be overflowing with refuse that attracted 
houseflies because of the bad odour emanating from the waste. The poor sanitation 
conditions were common in communities with public toilet facilities. Although some of 
the toilets were neat and devoid of houseflies’ others were unclean with a bad odour that 
attracted houseflies. Open defecation was observed especially along the undeveloped 
beaches and waste dumpsites near the bushes around the railway lines in some of these 
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communities. Figures 4.7 to 4.17 show some poor environmental sanitation observed in 
some of the communities.   
In the non-endemic communities, on the other hand, 306 (67.5%) of the households had 
good sanitation conditions. Among communities where households recorded more than 
90% of good sanitation were; Adedetsekope, Angomya-Ada, Asigbeykope, Dogobom, 
Kopehem-Kasseh, Dawhenya North. One hundred and forty-four households (144, 31.8%) 
recorded moderate sanitation conditions, with households in Addokope and Awhim 
recorded 100% moderate conditions. Adjumanikope and Kofikope reported 95.7% and 
82.8% good sanitation conditions respectively.   
Anyaman East and Dawa communities in the non-endemic communities had over 90% 
moderate sanitation condition as shown in Table 4.20.  Unlike the endemic communities, 
there were no open gutters, and pipelines were mostly buried in the ground. Their water 
sources were mostly standing pipes or pipes connected into the household dwelling. The 
waste in these communities were mostly burnt. Most of the households in the non-endemic 
communities had toilet facilities. It was however observed that there was open defecation 
in the bushes in some of the communities.  
  
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Table 4.20: Environmental assessment of the sanitation conditions in communities using 
Principal Components Analysis 
  Sanitation condition 
  Poor Moderate Good 
  No. % No. % No. % 
Endemic Communities 
 Adabraka 30 100.0 0 0.0 0 0.0 
 Agbogbloshie 32 100.0 0 0.0 0 0.0 
 Agege 6 46.2 7 53.8 0 0.0 
 Chorkor 22 100.0 0 0.0 0 0.0 
 Dansoman 20 43.5 26 56.5 0 0.0 
 James Town 0 0.0 7 100.0 0 0.0 
 Kaneshie 0 0.0 25 100.0 0 0.0 
 Maamobi 50 100.0 0 0.0 0 0.0 
 Mamprobi 1 4.8 20 95.2 0 0.0 
 Nima 66 100.0 0 0.0 0 0.0 
 Nungua 17 28.8 42 71.2 0 0.0 
 Teshie 55 67.9 26 32.1 0 0.0 
Total  300 66.2 153 33.8 0 0.0 
Non-endemic Communities 
 Addokope 0 0.0 35 100.0 0 0.0 
 Adedetsekope 0 0.0 0 0.0 36 100.0 
 Adjumanikope 0 0.0 2 4.3 45 95.7 
 Angomya-Ada 0 0.0 0 0.0 28 100.0 
 Anyaman East 2 4.6 42 95.4 0 0.0 
 Asigbeykope 0 0.0 0 0.0 46 100.0 
 Awhiam 0 0.0 34 100.0 0 0.0 
 Dawa 0 0.0 29 93.6 2 6.4 
 Dawhenya North 0 0.0 0 0.0 44 100.0 
 Dogbom 0 0.0 0 0.0 25 100.0 
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 Kofikope 1 2.4 2 4.8 39 82.8 
 Kopehem-Kasseh 0 0.0 0 0.0 41 100.0 
Total  3 0.7 144 31.8 306 67.5 
* A score of >1 was classified as poor, 0 to 1 moderate and < 1 was classified as good  
 
 
 
 
 
 
Figure 4.4: Choked gutters at Adabraka, Accra  
 
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Figure 4.5: Choked gutters within households in Agbogbloshie, Accra 
 
Figure 4.6: Waste dump sites near a slum community at Agbogbloshie, Accra 
 
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Figure 4.7: Makeshift structures in a slum community along Odorna river in 
Agbogbloshie, Accra 
 
Figure 4.8: Open defecation along the Odorna river near Agblogbloshie, Accra 
 
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Figure 4.9: Waste dumpsite close to the Chemuna Lagoon at Chorkor, Accra 
 
 
 
 
 
Figure 4.10: Garbage disposed into open drain with water pipelines in Chorkor, Accra 
 
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Figure 4.11: Waste dumpsite along a big gutter at Maamobi, Accra 
 
Figure 4.12: Waste overflow at Nungua market dumping site, Accra  
 
 
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Figure 4.13: A public toilet located in the compound of a household in Akpeshika in 
Nungua, Accra 
 
 
 
 
Figure 4.17: Garbage disposed into open drain with water pipelines in Nima, Accra 
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4.7 Assessment and identification of environmental risk factors of cholera in the Greater Accra 
Region 
4.7.1 Associations between environmental risk factors and cholera  
With regards to environmental factors as in Table 4.21, households with toilet facilities in 
their household or neighbourhood had more cases of cholera 33 (86.8%) than those 
without toilet facilities 5 (13.2%), but this was found to be statistically insignificant 
(p=0.428). Also, those communities with public dumpsites in their neighbourhood 
recorded more cases of cholera 33 (86.8%) than those communities without 5 (13.2%). 
The difference was statistically significant (p<0.001).  
In terms of the availability of a drainage system for the disposal of household liquid waste, 
more cholera cases 31 (81.6%) were recorded among households with a drainage system 
than those without a drainage system 7 (18.4%). This association was found to be 
statistically significant (p<0.001).  
Cholera cases were equally distributed among households in communities with water 
bodies 19 (50.0%) and those communities without water bodies 19 (50.0%) in the 
neighbourhood and were found to be insignificantly (p=0.346).  
Those neighbourhoods without an abattoir recorded the majority of the cases 35 (92.1%). 
However, the differences were not statistically significant (p=0.244). The presence of a 
market in the neighbourhood demonstrated a higher proportion of cholera cases 21 
(55.3%) compared to those without a market 17 (44.7%) and was found to be significantly 
associated with cholera (p=<0.001).  
Table 4.21: Associations between environmental risk factors and cholera in Greater Accra 
Region 
Variables Cholera P-Value 
Yes = 38 No=868 
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No. % No. %  
 Environmental factors 
Public toilet facility                                                                                                    0.428 
 Present 33  86.8 710 81.8  
 Not present 5 13.2 158 18.2  
Public dumpsite                                                                                                        <0.001 
 Present 33 86.8 465 53.6  
 Not present 5 13.2 403  46.4  
Drainage (gutters)                                                                                                    <0.001 
 Present 31 81.6 353 40.7  
 Not present 7 18.4 515 59.3  
Water body                                                                                                                0.346 
 Present 19  50.0 367 42.3  
 Not present 19  50.0 501 57.7  
Market                                                                                                                      <0.001 
 Present 21 55.3 179 20.6  
 Not present 17 44.7 689 79.4  
Abattoir                                                                                                                       0.244 
 Present* 3 7.9 38 4.4  
 Not present 35 92.1 830 95.6  
P value is significant if p < 0.05, *Fishers Exact Test 
 
A penalized multivariable logistic regression model was further used to determine the 
impact of the environmental factors on cholera risk in the study communities as shown in 
Table 4.22. The presence of a toilet facility at home or in the neighbourhood (public toilet) 
was found to be 72% less likely to have cholera compared to households without toilets or 
neighbourhood toilets and this was statistically significant after adjusting for other 
predictor variables (AOR=0.28, 95% CI: 0.08-0.97, p=0.046).   
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The odds of cholera occurrence were found to be 5.28 times higher among households 
located in a neighbourhood with a waste dumpsite compared to those with no waste 
dumpsite in their neighbourhood (OR=5.28, 95% CI: 2.12-13.14, p<0.001). The adjusted 
model was found to be significant (AOR=2.96, 95% CI: 1.11-7.88, p=0.030).   
Households living near a drainage system (open gutters) were 6.12 times more likely to 
have reported a case of cholera compared to households without a drainage system 
(OR=6.12, 95% CI: 2.73-13.74, p=<0.001). After adjusting for other predictor variables 
was found to be significantly associated with cholera occurrence (AOR=5.78, 95% CI: 
1.89-17.72, p=0.002).   
Households living in a community with a neighbourhood market were 4.72 times more 
likely to have ever suffered from cholera compared to those living in households without a 
neighbourhood market (OR=4.72, 95% CI: 2.46-9.06, p<0.001). The adjusted model was 
however not significant (AOR=1.79, 95% CI: 0.82-3.94, p=0.145).  
Table 4.22: Assessment of environmental risk factors of cholera using a penalized 
multivariable logistic regression model 
Variable OR (95%CI) P-value AOR (95% CI) P-value 
Public toilet facility     
Not present 1  1  
Present 1.36 (0.54-3.40) 0.513 0.28 (0.08-0.97) 0.046 
Public dumpsite     
Not present 1    
Present 5.28 (2.12-13.14) <0.001 2.96 (1.11-7.88) 0.030 
Drainage  (gutters)     
Not present 1  1  
Present 6.12 (2.73-13.74) <0.001 5.78 (1.89-17.72) 0.002 
Market     
Not present 1  1  
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Present 4.72 (2.46-9.06) <0.001 1.79 (0.82-3.94) 0.145 
OR – Odds Ratio, AOR – Adjusted Odds Ratio, CI – Confidence Interval, Significant (p<0.05) 
 
4.8 Spatial relationship between significant environmental risk factors and the spread of cholera  
Cholera cases were spatially distributed in the endemic communities over the period (2012 
to 2015) as shown in Figures 4.18 to 4.22.  It was observed that the majority of the cholera 
cases were recorded in 2014 and the least in 2013. Except for Dawhenya North and 
Kopehem Kasseh in the non-endemic communities that recorded a few cases of cholera 
during the major outbreak in 2014, no other community recorded a case during the period 
(Figure 4.20).  
In the endemic area, public toilets, public dumpsites, drainage systems, markets, abattoirs, 
and water bodies (rivers, streams, lagoon, estuarine) were the potential risk factors 
identified in the communities. All the 12 communities in the endemic area recorded 
multiple environmental risk factors. In the non-endemic area, water bodies and public 
toilets were identified in the communities.  A penalized multivariate logistic regression 
model was used to identify public toilets, public dumpsites, and drainage systems (gutters) 
to be significantly associated with cholera as shown in Figures 4.18 to 4.22.  
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Figure 4.18: Spatial distribution of the significant environmental risk factors and cholera 
cases in the communities in 2012 
 
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Figure 4.19: Spatial distribution of the significant environmental risk factors and cholera 
cases in the communities in 2013 
 
 
 
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Figure 4.20: Spatial distribution of the significant environmental risk factors and cholera 
cases in the communities in 2014 
 
 
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Figure 4.21: Spatial distribution of the significant environmental risk factors and cholera 
cases in the communities in 2015 
 
Spatial analysis of 500m buffer was created with public toilet facilities as the reference to 
show the different ‘hotspot’ communities and the significant environmental risk factors 
that were associated with the cholera incidence as shown in Figure 4.22.  
 
 
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Figure 4.22: Spatial relationship between the significant environmental risk factors and 
cholera cases within 500m buffer  
 
 
  
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CHAPTER FIVE 
DISCUSSIONS 
Summary of Major Findings 
The study compared cholera endemic and non-endemic communities to identify the most 
significant risk factors responsible for the cholera endemicity in the Greater Accra Region. 
The most important behavioural factor was the unsafe drinking water sources, lack of 
household toilet facilities. The household cooking location was protective against cholera. 
The household drinking sources and storage were highly contaminated with total and 
faecal coliforms.  
The study demonstrated the absence of the toxigenic V. cholerae O1 and O139 in the 
environmental water bodies and household drinking water sources or storage. However, 
revealed the presence of Vibrio fluvialis and Vibrio algionolyticus in some environmental 
water bodies.  
The environmental assessment showed pipe network contamination, indiscriminate 
dumping of refuse including human excreta, open defecation was still prevalent in the 
endemic communities.  
The study further identified the significant environmental risk factors such as waste 
dumpsites, open drainage, and public toilets to be close (500m) to each other and the 
historical cholera cases.  
5.1 Behavioural Factors Associated with Cholera Outbreaks 
5.1.1 Water sources and handling factors 
The main drinking water sources identified in this study were; private pipe, public pipe, 
borehole, unprotected well, surface, and sachet water. The study further revealed that most 
communities in both the endemic (99.8%) and non-endemic communities (84.3%) have 
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access to improved water sources (i.e private pipe, public pipe) and sachet water. The 
findings suggest an improvement over the national coverage of 44.3%  to 79.0% access to 
improved water as reported by the Ghana Living Standard Survey in 2017 (Ghana 
Statistical Service, 2018; Government of Ghana, 2019). The improvement may reflect 
government efforts to focus on water and sanitation issues to achieve the Sustainable 
Development Goal (SDG) 6 by 2030. The access to improved water by communities, 
however, does not guarantee safety. This current study found a significant association 
between the main sources of household drinking water and cholera. An earlier study 
during the 2014 cholera outbreak in the Osu Klottey sub metropolis in Accra similarly 
found drinking pipe-borne water to be associated with cholera (Davies-Teye, Vanotoo, 
Yabani, & Kwakye-Maclean, 2014).  The study also observed that the majority of the 
water sources in the endemic (57.0%) and non-endemic (75.9%) communities were 
located elsewhere outside their households. A significant association was found between 
cholera cases and the location of the drinking water sources. This may be attributed to 
inadequate treatment at the water source or contamination along with the pipe network in 
the case of pipe-borne water. This is supported by  Karikari and Ampofo (2013) of 
unsuitable levels of chlorine in the Accra water network which may be attributable to 
incomplete treatment of pipe-borne water.  
Despite the challenge with drinking water safety many communities do not treat their 
water at the point-of-use. This study found low water treatment at the point-of-use in both 
endemic (9.3%) and non-endemic communities (11.9%). This finding is consistent with 
other studies which similarly found low treatment of water at the point-of-use 
(Kaniambady, Vasu, Sandhya, & Kulkarni, 2017; Lartey, 2019). However, this contrasts a 
community-based study in Mangalore, South India which reported a high (95.0%) 
household water treatment as a result of the high literacy rate of the participants (Mithra et 
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al., 2010). Although more cholera cases were recorded among households that did not 
treat their drinking water at the point-of-used it was not significant. Our findings 
nonetheless give an indication of the low promotion of household water treatment in the 
communities and the need for water treatment intervention to protect the high-risk 
population from cholera infection.  
The study findings also revealed that the majority of households in the endemic (97.8%) 
and non-endemic communities (100.0%) experienced pipe-borne water shortages. These 
shortages are attributed to the high demand exceeding the production as a result of the 
rapid urbanization of the communities in the region.  Amidst water scarcity, households 
relied on other unimproved water sources such as surface water and dug well as observed 
in the non-endemic communities, and tanker water supply as found in the endemic 
communities. This scarcity and rationing of pipe-borne water also make households resort 
to a longer storage of their water leading to contamination as has been reported in other 
previous studies (Boateng et al., 2013; Gizachew et al., 2020). There is the need to ensure 
a regular supply of pipe-borne water to prevent cholera in at-risk populations.  
5.1.2 Food eating practices 
There are many foods related habits that are associated with cholera. This mostly occurs 
through the unhygienic handling of food which may lead to contamination with the Vibrio 
cholerae bacterium. In this current study, household food eating habits were explored. 
This study did not find any significant association between households that ate food from 
outside the home compared to those who ate from only home. This finding is consistent 
with a study by Moradi et al. (2016) conducted in Iran that did not also find any significant 
association between cholera and the consumption of food from street vendors. This 
finding, however, contrasts other studies which attributed cholera infection to the 
consumption of food sold by street vendors (Nsagha et al., 2015; Ohene-Adjei et al., 
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2017). They attributed the unhygienic way ready-to-eat foods are handled and sold by 
vendors to the cholera infection. Although this study did not find any significant relation 
with food eating habits of the households, street vendor foods are mostly sold by 
unlicensed vendors whose food safety manners may be compromised and a likely source 
of cholera transmission (Cummings et al., 2012; Nguyen et al., 2014). Thus, District 
Assemblies should ensure food vendors are adequately screened and licensed to operate to 
protect the population from cholera. 
The study also assessed the location where food was cooked in the household. It was 
observed that the majority of the households in both endemic (51.9%) and non-endemic 
communities (37.3%) cook in the yard compared to those who cooked inside the house or 
in a separate building. This study demonstrated that households that cooked in a separate 
building or the yard were protected from cholera infection compared to households that 
cooked in household dwelling. Despite this finding, the protection from cholera is 
dependent on the hygienic conditions of the cooking area.  
This study also investigated the household’s treatment of their vegetables before 
consumption.  The study revealed that vegetables were treated with; only water, water and 
heat steam, water and salt, salt solution and heat steam, vinegar and heat steam. The study 
observed that most communities in the endemic (67.1%) and non-endemic (80.4%) treated 
their vegetables by washing with only water. The good practice is to wash with salt and 
heat steam or washed in vinegar and heat steam which only a few did.  This finding 
however was not significantly associated with cholera. Notwithstanding, it is worrisome 
that most households are treated only by washing with water as these vegetables could be 
contaminated on the farm with sewage or manure of human origin and brought onto the 
market for sale. This was the case in Zambia, where the outbreak was linked to the 
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consumption of raw vegetables  (DuBois et al., 2006). A similar study in Ethiopia was also 
linked to the consumption of raw vegetables (Dinede et al., 2020). There is a need for 
education on the adequate treatment of vegetables before consumption to avoid 
contracting cholera.    
The eating of leftover foods is common in most countries, however, the risk of cholera 
transmission becomes important when the food is treated before eating (Tang et al., 2013). 
In this study, there was no significant association between cholera and the households’ 
habit of eating leftover foods. The study findings revealed that the majority of the 
households treated their leftover foods by heating them before eating. Only 4.9% of 
households in the non-endemic communities claimed they did not heat their leftover foods 
before eating and were at risk of cholera. Nonetheless, no significant association with the 
methods of household treatment of leftover foods and cholera was observed. This contrast 
a study carried out in Sierra Leone which found eating hot food to be protective (Nguyen 
et al., 2014).  V. cholerae can survive in food that is refrigerated or stored at room 
temperature and heating the food is the remedy to destroy the bacterium in the food (Tang 
et al., 2013; Waturangi et al., 2015). 
Handwashing before eating is a good practice to prevent many diseases including cholera. 
This study assessed the handwashing habit of households before meals and found a 
majority of households in both endemic (59.2%) and non-endemic (63.6%) communities 
wash their hands with only water before meals. On the other handwashing techniques used 
were; washing with soap in a bowl of water, washing hands in a running pipe-borne water, 
and washing with soap and running pipe-borne or ‘Veronica bucket’ (i.e a bucket with a 
tap connected). The washing of hands in a bowl of water is inappropriate because the 
germs that are washed off are picked up again. Only a few households practiced proper 
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handwashing with soap under running tap water. The results of the findings however did 
not reveal any significant association between hand washing before meals and cholera 
infection. This study, however, contrasts other studies that reported handwashing with 
soap under running water to be protective against cholera (Dan-Nwafor et al., 2019; 
Richterman, Sainvilien, Eberly, & Ivers, 2018; Wolfe, 2018).  
The proper washing of fruits with soap under running pipe-borne water was also not 
practiced in the studied communities. The majority of the households washed their fruits 
including mangoes, oranges, apples, watermelons, etc in a bowl of water. This practice has 
the disadvantage of recontamination of the fruits in the same water during the washing 
process.  This study did not find any significant association between cholera and the 
washing of fruits before eating. This study's findings contrast that of Moradi et al. (2016) 
conducted in Iran which associated the eating of fruits to cholera outbreaks which they 
speculated spread cholera in the province. This often occurs when the fruits are 
inadequately washed before eating.  
5.1.3 Solid waste disposal factors 
The faecal oral route transmission of diarrheal diseases can be prevented through the 
proper disposal of human excreta (Chikwe et al., 2020). In this study, it was observed that 
70.9% of households in the endemic and 51.7% in the non-endemic communities did not 
have toilet facilities in their homes and relied on public toilets or practice open defecation. 
This is consistent with other previous studies conducted in Prampram and Dodowa in the 
Greater Accra Region which revealed 85.0% and 85.9% of households respectively 
lacking access to toilet facilities in their homes (Akpakli, Manyeh, Akpakli, Kukula, & 
Gyapong, 2018; Obeng et al., 2015). The lack of funds and inadequate space to construct 
toilets especially in the poverty-driven communities may explain the low access to toilet 
facilities in the households in the endemic communities. The much-improved access to 
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household toilet facilities in the non-endemic communities on the other hand may be due 
to compliance of household heads to the district by-laws to include toilet facilities in the 
building plans. This study however did not find any association between cholera and the 
availability of household toilet facilities. This notwithstanding, the lack of household 
toilets may encourage the practice of open defecation especially at night if household 
members cannot visit the public toilet facilities. The average round trip time to go and use 
a public toilet facility was also examined in this study. It was observed that it takes an 
average round trip of 12.17 minutes and 9.50 minutes for households in the endemic and 
non-endemic communities respectively to go and use a public toilet facility.  Although it 
appears closer to the households, access could be a challenge at night. As such 
household’s ownership of toilets should be encouraged and public toilet facilities limited 
to public places such as markets, shopping malls, or lorry stations. This will help to 
prevent people from defecating into chamber pots and plastic bags and throwing them into 
gutters at night when it becomes impossible to visit the public toilets.  
With regards to the sharing of household toilets, the study revealed that 71.3% of 
households in the endemic and 86.8% in non-endemic communities shared their toilets 
with other households or the public. This study corroborates with the finding from the 
study by  Akpakli et al. (2018) which found 85.9% of households in Dodowa sharing toilet 
facilities. Toilets that are shared by more than one household are considered unimproved 
according to WHO because of the likelihood of contact with human excreta and the high 
risk of cholera infection (UNICEF and WHO, 2019). It was observed that shared toilet 
facilities exceed the national coverage of 56.7% in this study, demonstrating the challenge 
of the use of unimproved sanitation facilities in Ghana (Appiah-Effah et al., 2019). This 
contrasts with the study by Kaniambady et al. (2017) in Karnataka, India where all 
households used improved sanitation facilities.  The high use of shared toilet facilities in 
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our study area maybe because most of our participants lived in compound houses where 
toilet facilities are shared.  
This study supports Just et al. (2018), that demonstrated the increasing incidence of 
diarrhoeal diseases with increasing coverage of sharing toilets using mathematical 
modelling. This they attributed to the challenge of maintaining good hygienic practices in 
shared toilets. A survey of 570 households in a slum community by Heijnen, Routray, 
Torondel, and Clasen (2015) also suggested that shared toilets were more likely to be 
unclean with faeces and flies. This study also found some households in the endemic 
communities to be using bucket toilets which have a high risk of cholera transmission 
because of the possibility of contact with faeces and prohibited by the District Assembles. 
Although shared toilets are mostly used by households in urban communities the hygienic 
conditions of such facilities must be maintained to avoid spreading cholera and other 
diarrhoeal diseases.   
Handwashing after defecation is important in preventing faecal oral route transmission of 
diseases (Chikwe et al., 2020). The availability of handwashing devices near the toilet 
facilities encourages people to wash their hands after defecation. In this current study, 
82.4% of households in the endemic communities had handwashing devices (running tap 
water and soap) near the toilet facilities for immediate use after defecation compared to 
41.8% in non-endemic communities.  A study in Kersa Woreda reported only 8.3% of the 
households have hand washing facilities near the toilet (Mengistie & Baraki, 2010). The 
availability of handwashing devices at the toilet facilities was significantly associated with 
cholera (p=0.001). This suggests that having a handwashing device does not necessarily 
guarantee effective handwashing. In the non-endemic communities where toilet ownership 
was common, they lacked handwashing devices. There is the need for the provision of 
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handwashing devices at all toilet facilities (home or public) and community members 
should be educated on effective handwashing after defecation to prevent the transmission 
of cholera. 
In urban communities, large tonnes of waste is produced as a result of the rapid 
urbanization and high population density (Anaman & Nyadzi, 2015; Ohene-Adjei et al., 
2017). Unfortunately, the waste companies are not able to manage the large quantities of 
this waste produced in the urban communities and these are often left to overflow and, in 
some cases, disposed of indiscriminately into gutters and on the street. In this current 
study, it was found that most households temporally stored their waste in sacks and 
rubbish bins before disposal. Households’ temporal storage of waste was significantly 
associated with cholera. This may be explained by the odour generated from the waste that 
might attract flies or other rodents which could act as vectors in the transmission of 
cholera especially if the waste is kept for long periods before final disposal.  
In this study majority (86.6%) of the waste was collected by the motorized tricycles also 
known locally as ‘Aboboyaa’ in the endemic communities whereas Zoomlion Company 
mostly (69.6%) collected the waste in the non-endemic communities. The engagement of 
these motorized tricycles waste collectors to do the door-to-door collection of solid waste 
has significantly improved waste collection in most homes as they do not have to wait for 
the waste companies’ vehicles which are not regular (Issahaku, Nyame, & Brimah, 2014).  
This has helped to manage the tonnes of waste to substantial levels, although more needs 
to be done. For household’s solid waste that is not collected by any waste company, they 
were disposed of through burning, burying, indiscriminate dumping, or at public 
dumpsites. This attitude of disposal could be attributed to a lack of education on the 
harmful effects of such practices as similarly observed by Kanhai, Agyei-Mensah, and 
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Mudu (2019) in Accra. The burning of waste was the most common means of disposing of 
waste in the non-endemic communities because of its rural setting and the lack of waste 
bins and vehicles to convey the waste.  Therefore, motorized tricycles should be 
encouraged to augment the services of the other waste companies that exist in such 
communities. Households that were not patronizing the services of the waste companies in 
both communities gave reasons as the high charges and the lack of waste bins.  
5.1.4 Liquid waste disposal factors 
Liquid waste disposal from households involves wastewater from the bath and other 
domestic chores. In this study the drainage systems identified for disposal of liquid waste 
were; open gutters and those with pipe connections underground into a septic tank. In the 
study also, the liquid waste from the domestic waste which includes that from kitchen and 
washings were either disposed through the sewage system into a septic tank or thrown 
onto the streets, gutters, or compounds. Our findings reveal 94.4% of the drainage in the 
endemic communities to be open gutters whiles 83.7% of the drainage in the non-endemic 
communities was the underground drainage type. Irrespective of the type of drainage there 
was no significant association with cholera. The liquid waste from the bath was discarded 
in a similar manner depending on whether the bath was connected to a septic tank or into a 
gutter or sock away. The methods of household liquid waste disposal were significantly 
associated with cholera. This may be attributed to the sanitary conditions of the drains 
which were predominantly open gutters.    
5.2 Bacteriological quality of household drinking water  
The bacteriological quality of water can be affected by the natural presence of 
microorganisms or from contamination by human activities which may pose a risk to 
cholera and other diarrhoeal diseases (WHO, 2017c). The total coliform and faecal 
coliform counts are known to indicate faecal contamination of the drinking water and high 
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risk to potentially harmful pathogens. This current assessment of the bacteriological 
quality of water was carried out to determine the risk of household drinking water and 
cholera infection. The presence of V. cholerae or bacterial indicators of water quality in 
direct water sources and the household drinking water storage were assessed. In the 
endemic communities, the water source collected for drinking was from a private pipe or 
public pipe. In the non-endemic communities on the other hand the sources were from 
private, public and unprotected wells. This study demonstrated that the direct pipe, public 
pipe, unprotected well water sources collected from most of the communities during the 
dry and wet season were contaminated with total and or faecal coliform counts above the 
WHO and Ghana standards of zero (0) cfu/100 ml for drinking water both in the endemic 
and non-endemic communities, making them unwholesome for consumption (Ghana 
Standard Authority, 2009; WHO, 1993).  These findings are consistent with other studies 
that recorded high total and faecal coliform counts in directly collected piped and well 
water (Oyedum, Adabara, & Kuta, 2016; Tekpor, Akrong, Asmah, Banu, & Ansa, 2017). 
The high bacterial counts in the piped water sources may be attributed to the practice of 
laying pipelines in gutters and the lack of maintenance of the pipelines. Inadequate 
chlorination may also account for these high bacterial counts as reported by Karikari and 
Ampofo (2013) in an earlier study that revealed unsuitable chlorine levels and the 
presence of faecal coliform in the Accra water network. The differences in bacteria counts 
between the direct pipe and public taps in the endemic communities did not show any 
statistical significance, indicating that their contamination levels were similar.  
The same was the bacteria counts in the non-endemic communities except faecal coliform 
counts that showed significant differences in private, public, and unprotected well water. 
The private and public piped water are supplied by Ghana Water Company and may just 
be a reflection of their service delivery that needs improvement to reduce the risk of 
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cholera and diarrheal disease transmission. The unprotected wells may have run-off water 
contamination of the wells especially during the rainy season that might account for the 
high counts from the direct well water. This notwithstanding, the direct main public tap 
water in Dawa, Aedetsekope, Asigbeykope, and Adjumanikope did not record any 
coliform counts and was considered wholesome by the standards in the wet season. These 
communities have a community public standpipe located at a central point in the 
community and either connected to a borehole or directly to a high-level elevated tank, 
thus have few pipeline connections, unlike in the endemic communities where the public 
standpipes were connected to the general pipeline distribution and subject to more 
contamination. With regards to seasonality, higher total and faecal coliform counts were 
generally observed in the wet season than in the dry season in both the endemic and non-
endemic communities. This finding is in agreement with other studies that similarly found 
higher total and faecal coliform counts in the wet season than the dry season (Dongzagla, 
Jewitt, & O'Hara, 2021; Odonkor & Mahami, 2020). This may occur as a result of the poor 
environmental conditions around some of these water sources in the communities.  
In this study, the water stored for drinking by the households was also assessed for the 
level of contamination. The source water was collected and stored mostly in plastic 
containers and a few in earthenware/pot.  The study results revealed that irrespective of the 
water source (a private pipe, public pipe, sachet water, well, or dam) the contamination 
levels for total and faecal coliforms were higher than that directly collected from the water 
source. In the endemic communities, our study found a significant difference between the 
bacterial contamination levels and the water sources stored in the household. This was 
similarly observed in the non-endemic communities, except the Vibrio count which did 
not show any significant differences with the water sources stored.  This study is 
consistent with the findings of Meierhofer, Wietlisbach, and Matiko (2019) in Kenya 
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which found higher contamination levels in the storage containers. The reports of  Boateng 
et al. (2013) and Agensi et al. (2019) in Tamale, Ghana, and Kisoro, Uganda respectively, 
are similarly in line with this study's findings. The cleanliness of the storage vessels, 
methods of drawing water from the storage container, and the length of the storage were 
implicated for the high bacterial counts  (Asfaw, Reta, & Yimer, 2016; Lartey, 2019).  
This study findings also revealed that sachet water described as ‘pure water’ and 
increasingly relied on by most residents in the endemic communities recorded similarly 
high levels of contamination with total and faecal coliforms as the private pipe and public 
tap water. Earlier studies in Ghana and Nigeria have variously indicated sachet water to be 
contaminated with faecal coliform and other pathogenic bacteria and not wholesome 
(Aslan et al., 2020; Mosi, Adadey, Sowah, & Yeboah, 2019; Oluwafemi & Oluwole, 
2012). Semey et al. (2020) explained in their study that the contamination might be due to 
the unhygienic handling by factory workers during production. It may also occur if the 
source water used in the packaging is already contaminated without any further treatment. 
Dzodzomenyo et al. (2018) have further indicated that some of the sachet water companies 
are not formally registered by the Food and Drug Authority and might be violating the 
guidelines of the standard for quality water production. It is therefore not surprising that 
Aslan et al. (2020) study that examined the sachet bag observed some bags not to have a 
batch number, date of manufacture, and no information on treatment. This is worrisome as 
the shift to drinking sachet water might not necessarily be protective against cholera.  
Further analysis was conducted to confirm the suspected Vibrio isolates that were mostly 
detected in the household drinking water storage in both seasons. The most frequently 
isolated organisms in both seasons were; Escherichia coli and Klebsiella pneumoniae. The 
presence of these organisms indicates the possibility of the presence of potentially harmful 
bacteria. The suspected Vibrio counts observed were confirmed to be negative for Vibrio 
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cholerae, instead were identified as Pseudomonas aeruginosa, Proteus sp. and Aeromonas 
hydrophilia. Our findings did not detect the presence of V. cholerae and contrast that of  
Yirenya-Tawiah et al. (2018) that found Vibrio cholerae O1 strains in household drinking 
water storage in some communities in Accra just before the major cholera outbreak in 
2014. The absence of   V. cholerae in the current study explains the reason for the absence 
of a cholera outbreak during the study period.  The findings further strengthens the 
importance of regular environmental surveillance to predict cholera outbreaks. 
5.3 Assessment of environmental water bodies for the presence of V. cholerae O1/O139   
The water bodies in the selected communities for the study were assessed for the presence 
of toxigenic V. cholerae O1/O139, a potential risk for cholera infection.  This study 
revealed the presence of non-toxigenic V. cholerae O1 strains in dam water in Awhiam 
and Dawa in the non-endemic communities. V. cholerae non O1/non O139 was also found 
in the Odorna River in the endemic communities. These findings are consistent with that 
by Bwire et al. (2018) that examined major surface water bodies in Uganda but did not 
find any toxigenic V. cholerae O1/O139 strains. Similar studies in Cameroon and Burkina 
Faso did not also identify toxigenic strains in surface water (Akoachere & Mbuntcha, 
2014; Kaboré et al., 2018). The findings however contrast an earlier study by Abana et al. 
(2019) that identified toxigenic strains in environmental water samples in some cholera 
endemic communities in Accra.  
Other studies in Haiti also identified toxigenic V. cholerae O1 from some surface water 
(M. T. Alam et al., 2015; M. T. Alam et al., 2014). Toxigenic V. cholerae is believed to be 
transiently present in surface water during outbreaks. The Abana et al. (2019) study was 
conducted after the major 2014 cholera outbreak and the spillover of the cases into 2015 
may explain the presence of the toxigenic strains. The absence of the toxigenic strains of 
V. cholerae O1 and O139 may explain the reason for the absence of an outbreak of cholera 
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in the region. It also indicates that environmental surveillance of V. cholerae may be able 
to predict future outbreaks. This notwithstanding, non-toxigenic V. cholerae strains exist 
naturally in coastal waters, including areas where clinical cases did not exist (Almagro-
Moreno & Taylor, 2014). These non-toxigenic strains however have been recognized to be 
associated with localized outbreaks of diarrhoea and gastroenteritis and are of public 
health concern (Aydanian et al., 2015; Kaboré et al., 2018; Marin et al., 2013). It has also 
been reported that a few non-toxigenic V. cholerae strains could evolve to become 
pathogenic strains under selection pressure and their presence in the aquatic environment 
in the communities is important (Islam et al., 2020). This is however yet to be established 
in the Ghanaian water bodies as other researchers have disputed the existence of the 
possibility of an indigenous source (aquatic source or human carriers) and have attributed 
cholera outbreaks to mobile populations within the sub-region (Moore et al., 2018).  
This study did not detect V. cholerae O139 strains in the water bodies and the findings are 
consistent with similar studies in Burkina Faso and Cameroon but contrast the findings of 
Bwire et al. (2018) in Uganda which observed the presence of non-toxigenic V. cholerae 
O139. Hitherto, V. cholerae O139 strains were limited to India, Bangladesh, and some 
East Asian countries (Chowdhury et al., 2015; Mahapatra et al., 2014). This suggests the 
possibility of a spread to areas that were not originally indigenous for V. cholerae O139 
strains. All the V. cholerae strains identified in this study were identified during the dry 
season and contrast other studies in Cameroon and Uganda where V. cholerae were 
frequently identified during the rainy season (Akoachere & Mbuntcha, 2014; Bwire et al., 
2018). Although our detection occurred during the dry season there were intermittent rains 
during the period and the warmer temperatures could have supported their proliferation as 
reported by Emch et al. (2008) in an earlier study. Nevertheless, cholera transmission can 
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occur during any season but usually more commonly spread with the flood waters in the 
rainy season.  
Other Vibrio’s with similar phenotypic resemblance to V. cholerae were further analysed 
and revealed to be Vibrio fluvialis and Vibrio algionolyticus. These pathogens can be 
easily isolated with routine cultural techniques, but are difficult to differentiate between 
the species (Ramamurthy, Chowdhury, Pazhani, & Shinoda, 2014). This study used the 
mini Antigenic Profile Index (API E20) to identify them for the first time in the Ghanaian 
water bodies.  Vibrio fluvialis was detected in the lagoon and estuaries in the endemic 
communities during the rainy season. The V. algionolyticus on the other hand was 
identified in the Sango lagoon and estuarine in Teshie during the dry season. Like the 
other Vibrios, these have also been found to exist naturally in coastal water bodies with 
poor sanitation conditions. V. fluvialis is a fast emerging pathogen that presents with a 
cholera-like diarrhoea, gastroenteritis, and septicaemia in immunocompromised patients 
(Liu, Chiu, Chao, Hou, & Lai, 2011; Usó, Tirado, Moreno, & Campos, 2010). The V. 
fluvialis has haemolysin and metallprotease toxin genes which increases their virulence 
and are associated with foodborne outbreaks especially among people who eat 
inadequately cooked seafoods (Chowdhury et al., 2012; Liang, Cui, Du, Kan, & Liang, 
2013). A suspected case of cholera that was reported from a fisher folk at the time of this 
study, was confirmed to be caused by V. fluvialis and is an important organism to study in 
the future to elucidate its public health importance for inclusion in the national disease 
surveillance programme.  The V. algionolyticus is also known to cause chronic diarrhoea, 
otitis, wound infection, and septicaemia when exposed to contaminated seawater (Citil, 
Derin, Sankur, Sahan, & Citil, 2015). 
5.4 Assessment of Environmental Sanitation Condition of the Communities 
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The assessment of the environmental sanitation condition revealed that most of the 
communities in the endemic communities had poor sanitation with a few categorized to be 
moderate. The poor environmental sanitation was associated with contamination of the 
water supply pipe network laid in open gutters, indiscriminate dumping of refuse 
including human excreta as well as the presence of open defecation. The findings reflect a 
systematic review on cholera outbreaks in Ghana by Donkor and Namaitijiang (2019)that 
described the sanitation situation to be unsatisfactory. The poor environmental sanitation 
in Accra has similarly been reported by Ohene-Adjei et al. (2017) during the major cholera 
outbreak in 2014. In their study, they indicated that the index cases for the 2014 cholera 
outbreak were found in locations in Accra where unhygienic and poor environmental 
sanitation existed. Dzotsi et al. (2016) in an isolated case-control study in Accra during the 
cholera outbreak in 2014, also attributed contamination of water supply pipelines, crude 
dumping of refuse, poor drainage, choked gutters, and open defecation to the outbreak. In 
that study, they observed all the cholera cases resided in communities that had generally 
poor sanitation conditions.  Although governments in the past and present have attempted 
to address the sanitation situation through the creation of a ministry for sanitation and 
water resource, ‘national sanitation day’ and the ‘one house, one toilet’ initiative by the 
Accra Metropolitan Assembly, sanitation issues remain a challenge as revealed by our 
current study. This notwithstanding most communities in the non-endemic area had good 
or moderate sanitation because they had their pipelines buried in the ground with no open 
gutters even though open defecation was observed in bushes in some of the communities, 
they were not washed to contaminate the water pipelines. On the whole, the non-endemic 
communities had a lesser risk of cholera transmission than the endemic communities. This 
indicates that we are not out of the cholera menace yet and need to further enforce and 
implement the Assembly by-laws on sanitation to prevent these diseases.  
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5.5 Assessment of Environmental related factors associated with cholera 
5.5.1 Environmental factors and cholera 
This study assessed the associations between cholera and other potential environmental 
factors such as the presence of public toilets, waste dumpsites, open gutters, water bodies, 
and abattoirs in the neighbourhood of the households.  
This study's findings indicate that 68.9% of endemic communities had public toilets 
compared to 17.7% in the non-endemic communities. This reflects the lack of household 
toilet facilities in the endemic communities. The findings however indicated that 
households with neighbourhood public toilets were 72% protected from cholera compared 
to those households without any neighbourhood toilets and this was significant. The 
availability of public toilets in communities without household toilets could encourage 
their usage and prevent open defecation which is associated with cholera risk. This 
however was not the case in this study as some household members were engaged in open 
defecation despite the presence of public toilets.  A minimal amount ranging from fifty 
Ghana pesewas to one Ghana Cedi was charged at the time of the study to use the public 
toilet facilities. Some households with large family sizes claimed they could not afford the 
daily use of the public toilets because of the cost.  Others gave reasons for the poor 
hygienic conditions of the toilet facilities that made them resort to open defecations. There 
may be other cultural or belief systems as suggested by Osumanu, Kosoe, and Ategeeng 
(2019) in their study in the Wa Municipality that could also influence the practice of open 
defecation and thus present the risk to cholera. The Community-Led Total Sanitation 
(CLTS) approach and the enforcement of the District Assembly by-laws on sanitation 
could help prevent open defecation in these communities. 
This study findings revealed more waste dumpsites in the endemic (71.1%) communities 
than the non-endemic communities (38.8%). It further found that households with 
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neighbourhood waste dumpsites were more likely to contract cholera than those without 
waste dumpsites in their neighbourhood and this was significant. These households were 
estimated to be located at the average round distance of 17.24 minutes in the endemic 
communities and 11.77 minutes in the non-endemic communities. Other studies have 
similarly suggested proximity to the waste dumpsite as a risk factor to cholera. For 
instance, Suleman, Darko, and Agyemang-Duah (2015) indicated in a related study in 
Sawaba in the Kumasi Metropolis that waste dumpsites located at a distance of fewer than 
5 minutes to the households reported more cases of cholera. Other geospatial analyses by 
Olanrewaju and Adepoju (2017) in Ife, Nigeria, and Osei and Duker (2008b) in Kumasi 
also suggested proximity to waste dumpsite as a risk factor for cholera infection. The 
houseflies and other flies hovering around the waste dumpsites are vectors of transmitting 
disease pathogens and could aid in the contamination of nearby exposed foods in the 
households.  
This study's findings showed that there were more open gutters in the endemic 
communities (94.4%) than in the non-endemic communities (2.4%). The presence of open 
gutters in the neighbourhood was more likely to suffer from cholera compared to those 
households without neighbourhood open gutters and this was significant. The drainage 
system in most households is open gutters and liquid waste together with solid waste is 
disposed. There is no proper drainage system in most households in the disposal of liquid 
waste. As such most households dispose of the house liquid and solid waste into the 
gutters. These often result in the choking of gutters and serve as a reservoir for many 
pathogens including Vibrio cholerae.   
This study assessed the proximity of the water bodies in selected communities and cholera 
infection. The study identified water bodies including lagoons, rivers, streams, and sea to 
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be present and located at an average of 14.70 minutes round trip distance to endemic and 
11.17 minutes in the non-endemic communities. This study's findings however did not 
reveal any significant association between household’s location to the water bodies and 
cholera infection. This contrasts with the study by Stoltzfus et al. (2014) that showed the 
proximity of 5 km from the population to water bodies to have an increased risk of cholera 
in Kenya. Other studies support the findings that proximity to water bodies increased the 
risk of cholera infection (Bompangue et al., 2008; Kiiru et al., 2013; Nkoko et al., 2011; 
Olanrewaju & Adepoju, 2017). Although this study did not find any significant relation, it 
is known that water bodies that contain phytoplankton and zooplankton serve as a 
reservoir for V. cholerae and may explain the reason for the increased risk of cholera 
(Colwell et al., 1996; de Magny et al., 2011). This is especially important during the rainy 
season when floodwater from the water bodies contaminates the drinking water sources or 
if water is directly used for domestic chores. Other studies have also speculated that 
swimming or bathing in contaminated water bodies poses a risk of cholera infection 
(Rebaudet, Sudre, Faucher, & Piarroux, 2013). It is obvious households who are fisher 
folks or live near water bodies such as lakes, rivers, and sea may swim in them not 
knowing the risk it poses. 
Concerning the proximity of households to markets, this study found markets only in the 
endemic areas and they were within 11.04 minutes average walking distance away. The 
findings revealed that households with neighbourhood’s markets were more likely to 
suffer from cholera compared to those households without markets in their 
neighbourhoods which was significant. However, in a penalized logistic regression model, 
this was found not to be significant. This contrasts the Olanrewaju and Adepoju (2017) 
study which found 7 out of 18 markets to be in close proximity to historical cholera cases 
in Ife, Nigeria. Other studies also found cholera hotspots to be located close to market 
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places (Griffiths et al., 2021; Luquero et al., 2011; Zerbo, Delgado, & González, 2020). 
They attributed their findings to the waste that is dumped near marketplaces to be the 
possible reason. In our current study, similar heaps of waste were found in most of the 
marketplaces. Managing and disposing of waste at the marketplaces could help to contain 
the spread of cholera in such neighbourhoods with markets.  
This study identified a few unapproved abattoirs or slaughterhouses in the endemic 
communities (8.6%) and non-endemic communities (0.4%). They were located at an 
average distance of 9.61 minutes and 8.75 minutes in the endemic and non-endemic 
communities respectively. The study did not find any significant association between the 
presence of neighbourhood abattoir or slaughterhouses and cholera. The Olanrewaju and 
Adepoju (2017) study in Nigeria indicated 2 out of 36 abattoirs to be associated with 
historical cholera cases. In unapproved abattoirs that are not equipped with facilities to 
protect against houseflies, the meat attracts flies which could aid transmission by 
contaminating the meat or nearby foods in the neighbourhood.  
5.6 Spatial relationship between significant environmental risk factors and the spread of cholera  
Geographical Information System (GIS) was used to map the location of the significant 
environmental risk factors of cholera and to determine the spread in the communities. In 
this study, the Spatio-temporal effect observed from 2012 to 2015 demonstrates a possible 
environmental influence of cholera in the Greater Accra Region. In this study, public 
toilets, waste dumpsites, and open drainage were the significant environmental risk factors 
found to be associated with cholera. The proximity of the location of cholera cases to these 
environmental risk factors also shows the relationship to the transmission and endemicity 
of cholera in the communities.  
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This study revealed that waste dumpsites, open drainage, and public toilets risks factors 
were within 500m proximity in the cholera endemic communities. The multiple presences 
of these environmental factors may explain the reason for the transmission and the 
endemicity of cholera in the endemic communities compared to the non-endemic 
communities. This is consistent with the study of Olanrewaju and Adepoju (2017), which 
also found cholera to occur close to waste dumpsites near markets, rivers/streams, and 
abattoirs.  The effect of living near environmental risk factors was similarly demonstrated 
by Osei and Duker (2008b) in a study in Kumasi. They expressed the spread to the effect 
of distance on spatial interaction with the risk. Thus, suggesting the risk of contracting 
cholera to be minimal as the risk was further away. Public toilets, waste dumpsites, and 
open drainage may constitute a major breeding site for vectors such as houseflies and 
rodents which are capable of spreading diseases including cholera. Fotedar (2001) in a 
study in India demonstrated the potential for houseflies (Musca domestica) or flies to act 
as mechanical vectors for the spread of V. cholerae. Public toilet facilities that are unclean 
and smell bad odour attract houseflies and may aid in the spread of the cholera bacterium 
to households in close proximity. Waste dumpsites may serve as breeding sites for 
disease-causing flies and rodents depending on the state of waste and the length of storage.  
The findings from this study agree with an earlier study by Osei and Duker (2008b) which 
demonstrated the role of proximity and density of open refuse dumps to cholera 
transmission in Kumasi. They indicated that open refuse dumps serve as niches for cholera 
infection and individual households living within a 500m radius were more at risk of 
cholera infection.  The study of Olanrewaju and Adepoju (2017) also identified waste 
dumpsite as a major risk for cholera. With the current use of motorized tricycles in the 
Accra Metropolis, waste collection has improved except for the very deprived slum 
communities where indiscriminate dumping of waste is still rampant. This study also 
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found proximity to open drainage to play a role in the spread of cholera. The practice of 
dumping biodegradable waste including human excreta in plastic bags remains a challenge 
in most of the endemic communities and most often choke the drains. These choked drains 
may serve as breeding sites for flies which may aid the spread of cholera in nearby 
households in the communities.  Except for a few public toilets in the non-endemic 
communities, waste dumpsites and open drainages were uncommon and do not have a 
high risk of cholera spread. It is therefore not surprising that the non-endemic 
communities did not report a case of cholera over the years despite the ongoing 
surveillance. It was only in 2014 when the country experienced a major cholera outbreak 
that Dawhenya North and Kopehem Kasseh communities in the non-endemic area 
reported a few imported cases from the Accra Metropolis.  This was however, not wide 
spread and was contained.  In order to reduce the risk of cholera spread the siting of public 
toilets, waste dumpsites should be sited at beyond 500m radius in the communities. Open 
drains should also be covered. 
5.7 Limitations of the Study 
The findings from this study are subject to some limitations. The most important limitation 
lies in the fact that our study was cross-sectional in design and concluding on causality, 
however inferences about associations between the potential risk factors and cholera 
occurrence were made.  
The respondents to the questionnaire were the head of households, nonetheless, difficulties 
with the recall of household information on the reported household cholera infection was 
possible. This might have accounted for the low number of household cholera cases 
reported in the endemic area even though the endemic communities were purposefully 
selected.  
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The self-reporting of the cholera cases in the households and social desirability biases, 
unmeasured confounders and possibility of residual confounding was also a limitation of 
the study. 
The line list of historical cholera cases obtained from the study did not have information 
on the GPS location of the cases. As such the maps were drawn based on the aggregated 
data of cases in each particular community, instead of the case-by-case mapping to 
demonstrate how the cases clustered within the communities. 
  
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CHAPTER SIX 
CONCLUSION AND RECOMMENDATIONS 
6.1 Conclusion 
This study assessed the behavioural risk factors in both endemic and non-endemic 
communities. The findings showed that household drinking water was contaminated from 
the source and unsafe for drinking. However, most households did not treat them at the 
point-of-used prior to consumption, which may have contributed to the cholera outbreaks 
in the communities. Additionally, it showed that households who cooked outside/yard or 
in separate building had a lower chance of contracting cholera and this practice should be 
promoted. The study further demonstrated that households lacking toilet facilities shared 
with other households or relied on public toilets or engaged in open defecation. Through 
this behaviour, others run the risk of coming into contact with human excreta in the 
environment, which increases their risk of contracting cholera or other diarrheal diseases.  
The bacteriological assessment of the household drinking water quality revealed that total 
and faecal coliform counts exceeded the Ghana and WHO recommendation in the endemic 
and non-endemic communities. Thus, suggesting the contamination to likely be from 
source, length of storage or from the container and unfit for human for consumption. The 
sachet water which was the most preferred drinking water source in the endemic 
communities was also highly contaminated with total and faecal coliforms and increased 
the risk of cholera spread. The bacterial counts followed a seasonal pattern peaking during 
the wet season compared to the dry season possibly resulting from contamination of water 
sources from run-off flood waters.  Escherichia coli and Klebsiella pneumoniae were the 
most common coliforms recovered with no V. cholerae strains isolated from both the 
direct or stored household drinking water.  
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Toxigenic strains of V. cholerae O1 and O139 were absent in the environmental water 
bodies in the study communities suggesting a reduced infection rates in both endemic and 
non-endemic communities.  However, other Vibrio strains such as Vibrio fluvialis and 
Vibrio algionolyticus which presents with cholera-like diarrhoea were isolated in the 
lagoon and estuarine waters in the endemic communities.  
When compared to non-endemic communities, the endemic communities had less 
satisfactory (poor) sanitation standards, as evidenced by the contamination of pipe 
networks, indiscriminate disposal of waste, including human excreta, and the prevalence 
of open defecation. 
The three main environmental risk factors identified were public toilets, waste dumpsite, 
and open drainage. The multiple presences of these environmental risk factors within a 
500 m radius to each other provided evidence of the interaction of the risk and the 
relationship to cholera endemicity in the endemic communities compared to the non-
endemic communities. 
6.2 Recommendations 
The following recommendations were made from the study findings: 
1.  The household drinking water from direct and stored vessels were contaminated with 
coliforms, an indication for the possible presence of pathogenic organisms. However, the 
water was consumed without treatment by most households. It is therefore recommended 
as a short-term measure, to the Municipal and District Health Directorates in the Greater 
Accra Region to; 
1. Educate the community leaders (chiefs, assembly men, community volunteers) to 
support their respective communities in promoting household drinking water 
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treatment at the point-of-used to reduce the risk of transmission of cholera and 
other diarrheal diseases. 
 
2. Sachet water which is highly patronized in the endemic communities was also highly 
contaminated with coliforms and a high risk to cholera infection. As a short-term measure, 
Ghana Standard Authority/Food and Drug Authority should; 
1. Regularly monitor the bacteriological quality of sachet water sold on the market 
and sanction sachet water manufacturing companies not conforming to the quality 
standard. 
 
3. Most households in the endemic and non-endemic communities that lacked toilet 
facilities shared toilets with other households or used public toilets or were engaged in 
open defecation. To avoid the spread of diarrheal diseases including cholera it is important 
for every household to have a toilet. It is therefore recommended as a short to medium-
term measure, to the Municipal or District Assemblies in the Greater Accra Region to 
strengthen and enforce laws on; 
1. ‘One-house-one-toilet’ policy in the endemic communities and adopt the 
‘community-led total sanitation’ approach in the non-endemic communities to 
improve on household access to toilets and prevent open defecation. 
4. The environmental sanitation conditions assessed revealed the endemic communities to 
have unsatisfactory (poor) sanitation. This was due to the indiscriminate dumping of solid 
waste mostly resulting from the absence of bins and the unavailability of waste collection 
companies to pick up the waste in some communities. It is therefore recommended as a 
short to medium-term measure, to the Municipal or District Assemblies to improve on 
waste collection and disposal in the communities by; 
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1. The provision of waste bins to households and to also place bins at vantage points 
in the communities 
2. The use of motorized tricycles on door-to-door waste collection complement the 
effort of the waste collection companies to rid the communities of solid waste. 
3. Community participation in the monthly clean-up campaigns to improve the 
sanitation conditions of the communities. 
4. Considering siting public waste dumpsites at a distance of 500 m from the 
households to reduce the risk of cholera transmission in the communities. 
 
5. Future research is needed to: 
1. Further, determine the importance of environmental surveillance of the cholera 
aetiological agents in the environmental water bodies or household drinking water 
in predicting cholera outbreaks. 
2. To determine the emerging pathogenic strains of V. fluvialis and V. algionolyticus 
isolated from the environmental water bodies to establish their public health 
importance and possible inclusion in the national surveillance system. 
 
6.3 Contribution to Knowledge 
1. This research provides evidence that V. cholerae O1 and O139 is not permanently     
present in the Ghanaian water bodies. 
2. To the best of my knowledge V. fluvialis and V. algionolyticus were isolated for 
the first time in the Ghanaian environmental water bodies. These Vibrios are fast 
emerging pathogens that present with cholera-like diarrhoea, gastroenteritis, and 
septicaemia in immunocompromised patients and if their public health importance 
is established could be included in the national surveillance system. 
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3. This research demonstrated that the mini Antigenic Profile Index for 
Enterobacteriaceae (API 20E) could be used routinely to identify other Vibrios 
such as V. fluvialis and V. algionolyticus in patients presenting with cholera-like 
diarrhoea for effective management. 
4. This research work also demonstrated that multiple presences of environmental 
risk factors close to each other could account for cholera endemicity or persistence 
in a community. 
 
 
 
  
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APPENDICES 
Appendix A: Bacteriological Media Preparations 
Buffered Peptone Water (BPW) (Oxoid, UK) 
BPW is a non-selective pre-enrichment medium used for recovering bacteria from foods 
or clinical specimen. 
It was prepared by weighing an amount of 20g of BPW dehydrated agar and dissolved in 
1litre of distilled water. It was dispensed into bottles and sterilized in an autoclave at 
1210C for 15minutes at 15lbs pressure. 
Eosin Methylene Blue Agar (EMB) (Microbes Laboratories) 
EMB agar is a selective and differential medium used to isolate faecal coliforms. 
It was prepared by weighing an amount of 35.96g of dehydrated EMB and dissolved in 1 
litre of distilled water. The medium was heated to boil to dissolve the media completely. 
The medium was distributed into bottles and sterilized by autoclaving at 1210C for 
15minutes at 15lbs pressure. The medium was allowed to cool to about 500C and 
dispensed into 15ml sterile petri dishes. 
Violet Red Bile Agar (VRD) (Oxoid, UK) 
VRB gar is a selective medium used to detect and enumerate lactose fermenting colonies. 
It was prepared by weighing 38.5g of VRB and dissolved in 1 litre of distilled water. It 
was heated to boil and cool to 500C before dispensing into 15ml sterile petri dishes. 
Plate Count Agar (PC) (Neogen Company, UK) 
PC is used to enumerate bacteria in water, wastewater, food and dairy products in the 
laboratory. 
It was prepared by weighing an amount of 23.5g of the dehydrated PC agar and dissolved 
in 1 litre of distilled water. It was heated to boil and dissolve completely. The media was 
autoclaved at 1210C for 15minutes at 15lbs pressure. The medium was allowed to cool to 
45 to 500C and dispensed into 15ml sterile petri dishes. 
Thiosulfate-Citrate-Bile-Sucrose Agar (TCBS) (Park Scientific Ltd) 
TCBS is a selective medium used to isolate Vibrio species. 
It was prepared by weighing 88g of TCBS dehydrated powder and dissolved in 1 litre of 
distilled water. It was allowed to soak for 10 minutes and swirled to mix completely. It 
was then brought to boil and cooled to 470C and poured into 15ml sterile petri dishes.  
Tryptone Soy Agar (TSA) (Neogen Company, UK) 
TSA is a general purpose, non-selective media that allows the growth of most bacteria. 
It was prepared by weighing 39g of TSA powder and dissolved in 1 litre of distilled water. 
It was mixed and boiled to dissolve completely. It was then autoclaved at 1210C for 
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15minutes at 15lbs pressure and distributed into 15ml sterile petri dishes after cooling to 
500C. 
MacConkey Agar (MAC) (Difco Laboratories) 
MAC is a selective and differential medium designed to isolate non-fastidious gram-
negative bacteria. 
It was prepared by weighing 51.53g of the MAC powder and dissolved in 1 litre of 
distilled water. It was heated to boil with gentle agitation to dissolve completely. It was 
then autoclaved at 1210C for 15minutes at 15lbs pressure and distributed into 15ml sterile 
petri dishes after cooling to 500C. 
Simmons Citrate Agar (Neogen Company, UK) 
Simmons Citrate is used to differentiate the bacteria ability to utilized citrate. 
An amount of 24g of the dehydrated powder was dissolved in 1 litre of distilled water, 
swirled to mixed and brought to boil. It was then dispensed into tubes and sterilized by 
autoclaving for 15mins at 1210C at 15lbs pressure. The tubes were slanted and allowed to 
cool and solidified. 
Motility Indole Ornithine (MIO) (Becton, Dickinson and Company, France) 
MIO is used to differentiate Enterobacteriaceae based on motility, ornithine decarboxylase 
activity and indole production. 
It was prepared by weighing 31g of the powder and dissolved in 1 litre of distilled water 
by heating with frequent agitation to boil for 1minute. It was then dispensed into tubes and 
autoclaved at 1210C for 15minutes at 15lbs pressure. 
Triple Sugar Iron Agar (TSI) (Rapid Labs, UK) 
TSI is a microbiological media with the ability to test bacteria fermentation of sugars (1% 
lactose, 1% sucrose, 0.1% glucose) with the production of hydrogen sulphide. 
It was prepared by weighing 65g of the dehydrated powder of TSI and dissolved in 1 litre 
of distilled water. It was mixed and heated to boil to completely dissolve the agar and 
dispensed into tubes and sterilized at 1210C for 15minutes at 15lbs pressure. The tubes 
were then slanted and allowed to solidify before used. 
Luvia Broth 
A litre of Luvia broth was prepared by weighing; 
Tryptone -10g 
Yeast extract – 5g 
Sodium chloride – 10g 
NaOH – 0.2g 
And dissolved in 1 litre of distilled water and dispensed in bottles. This was sterilized at 
1210C for 15minutes at 15lbs pressure and cooled to room temperature before used. 
Appendix B: Biochemical Test and Staining Techniques 
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Biochemical Test 
Oxidase Test 
The test use Kovac’s oxidase reagent (tetramethyl-p-phenylenediamine dihydrochloride) 
that changes colour when it becomes oxidized by cytochrome C oxidase.  
Purpose 
This test is helpful in identifying members of Neisseria, Enterobacteriaceae, 
Pseudomonadaceae, to aid in differentiating Gram negative non-enterics from 
Enterobacteriaceae, and in identifying a few others.  
Requirements 
1. Oxidase reagent droppers 0.5ml (1% tetramethyl-p-phenylene-diamine 
dihydrochloride) (Becton Dickson Company, USA) 
2. Positive control bacteria- Pseudomonas aeruginosa ATCC 27853 
3. Negative control bacteria-Escherichia coli ATCC 25922 
Procedure 
1. A test bacterium grown within 18 to 24 hours on TSA was used.  
2. Two to three drops of the oxidase reagent was dispensed on some of the growth. 
3. This was examined within 20 seconds for a colour change. 
Results 
1. The organism was considered positive for the presence of cytochrome C oxidase if 
a dark-purple colour develops within 20 seconds and negative if there was no 
colour. 
 Catalase Test 
Hydrogen peroxide, an end product of aerobic carbohydrate metabolism, is extremely 
toxic to bacteria. Bacteria containing the enzyme catalase break down hydrogen peroxide 
into oxygen and water. Bacteria that possess catalase demonstrate the reaction in 3% 
hydrogen peroxide by the rapid appearance of gas bubbles.  
Purpose 
The catalase test facilitates the detection of the enzyme catalase in bacteria and used to 
differentiate between bacteria that contains the enzyme and those that does not. 
Requirements 
2. Catalase Reagent Droppers contain: 3% Hydrogen Peroxide and 0.05% or less of 
stabilizer (Becton Dickson Company, USA) 
3. Platinum inoculating loop 
4. Glass slides 
5. Bunsen burner 
6. Positive control bacteria- Staphylococcus aureus ATCC 33592 
7. Negative control bacteria-Enterococcus faecalis ATCC 29212 
 
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Procedure 
1. A drop or two of the catalase reagents was taken onto a clean glass slide. 
2. An inoculating needle was used to pick a well-isolated colony grown within 18 to 
24 hours, without touching the media and placed on the catalase reagent. 
3. This was examined for the rapid production of gas bubbles. 
Results 
1. Positive catalase reactions were denoted by the production of bubbles. 
 
Triple Sugar Iron Test 
The Triple Sugar Iron (TSI) agar test is designed to differentiate among the different 
groups or genera of the Enterobacteriaceae, which are all gram-negative bacilli capable of 
fermenting glucose with the production of acid, and to distinguish them from other gram-
negative intestinal bacilli. The differentiation is based on fermentation of glucose and 
lactose or sucrose and hydrogen sulphide (H2S) production. TSI medium contains 10 parts 
of lactose: 10 parts of sucrose: 1 part of glucose and peptone. Phenol red and ferrous 
sulphate serve as indicators of acidification and H2S formation, respectively. The acid base 
indicator phenol red incorporated for detecting carbohydrate fermentation is indicated by 
the change in colour of the carbohydrate medium from orange red to yellow in the 
presence of acids.  In case of oxidative decarboxylation of peptone, alkaline products are 
built and the pH rises. This is indicated by the change in colour of the medium from 
orange red to deep red. Sodium thiosulfate and ferrous ammonium sulphate present in the 
medium detects the production of hydrogen sulphide and is indicated by the black colour 
in the butt of the tube. 
Purpose 
The TSI is designed to differentiate among bacteria based on the differences in 
carbohydrates fermentation patterns and hydrogen sulphide production. 
Requirements 
2. TSI medium prepared 
3. Straight inoculating needle 
4. Bunsen burner 
5. Control organisms e.g Pseudomonas aeruginosa ATCC 27853, Escherichia coli 
ATCC 25922 
 
Procedure 
1. The top of a well-isolated colony was touched using a sterile straight inoculation 
needle 
2. The inoculation was done by first stabbing through the centre of the medium to the 
bottom of the tube and then streaking on the surface of the agar slant.  
3. The Inoculated TSI tube was loosely closed and incubated at 35°C in ambient air 
for 18 to 24 hours. 
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4. The TSI tube was examined for colour change in the slant and butt, blackening and 
cracks in the medium. 
  
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Results interpretation 
1. If lactose (or sucrose) was fermented a large amount of acid was produced and 
turned the phenol red indicator yellow in the butt and slant.  
2. If lactose was not fermented but the small amount of glucose was, the oxygen-
deficient butt was yellow but the slant indicating the acid produced was yellow. 
3. If neither lactose/sucrose nor glucose was fermented, both the butt and the slant 
were red.  
4. If organisms generated gases was indicated by bubbles/cracks on the medium. 
5. If H2S was produced resulted in the blackening of the medium.  
Motility Indole Ornithine Medium (MIO) 
The casein and gelatine peptones, yeast extract and dextrose provide nitrogenous and 
carbonaceous substances, vitamins and minerals essential for bacterial metabolism. When 
ornithine decarboxylase is present, the ornithine is decarboxylated to putrescine which 
causes a rise in the pH and corresponding colour change of bromocresol purple from 
yellow to purple. 
Purpose 
MIO medium is used to demonstrate motility, indole production and ornithine 
decarboxylase activity for the differentiation of Enterobacteriaceae. 
Requirements 
6. MIO medium prepared (Becton, Dickinson and Company, France) 
7. Kovac’s reagent 
8. Straight inoculating needle 
9. Bunsen burner 
10. Positive control bacteria- Escherichia coli ATCC 25922 
11. Negative control bacteria- Klebsiella pneumoniae ATCC 13883 
 
Procedure 
12. The top of a well-isolated colony grown between 18 to 24 hours was touched using 
a sterile straight inoculation needle. 
13. The inoculation was done by a single stab through the centre of the medium to 
within ¼ inch of the bottom of the medium.  
14. The Inoculated MIO tube was incubated at 35 ±2°C for 18 to 24 hours. 
15. The MIO tube was examined for growth, presence of motility, ornithine 
decarboxylase and indole reactions. If the reaction was negative was incubated for 
a further 24 hours. 
Results 
1. Motility was indicated by growth extending from the line of inoculation. The 
nonmotile organisms grew only alone the line of inoculation. 
2. Decarboxylation of ornithine was indicated by the development of a turbid purple 
to faded yellow purple colour. A negative reaction was indicted by a yellow colour. 
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3. Indole production was indicated by the formation of a pink to red colour after the 
addition of three or four drops of kovac’s reagent to the surface of the medium and 
gentle shaking. A negative reaction was indicated by the development of a yellow 
colour. 
Control Organisms 
No. Control Organisms used Results after 18 – 48 hrs 
1 Escherichia coli Motility – Positive 
ATCC 25922 Ornithine – Positive 
Indole - Positive 
2 Klebsiella pneumoniae Motility – Negative 
ATCC 13883 Ornithine – Negative 
Indole - Negative 
 
Gram Staining Technique 
Gram staining technique is a differential stain used to classify bacteria into Gram-positive 
and Gram-negative bacteria. 
Requirements 
1. Becton Dickinson (BD) Gram Stain (2g crystal violet, 20ml 95% ethyl alcohol, 
0.8g ammonium oxalate and 100ml distilled water) 
2. BD Grams iodine (2g potassium iodide, 1g iodine crystal, 100ml distilled water) 
3. BD Decolourizer (50ml acetone and 50 ml ethanol) 
4. BD Safranin (4g safranin, 200ml 95% ethanol, 800ml distilled water) 
5. Glass slide 
6. Bunsen burner 
7. Platinum inoculating loop 
8. Water 
9. Staining rack 
10. Slide rack 
11. Gram Positive bacteria – Staphylococcus aureus ATCC 33592 
12. Gram Negative bacteria - Escherichia coli ATCC 25922 
 
Procedure 
1. One or two pure colonies were touched and a smear prepared on a clean slide by 
mixing and spreading it out. The slide was labelled and placed on the staining rack 
to air dry. 
2. The smear was then heat fixed by passing the slide two to three times in a Bunsen 
burner flame with smear uppermost. 
3. The smear was covered completely with the BD Gram stain and left on it for 60 
seconds and washed off with water. 
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4. The smear was covered completely with Gram’s iodine solution and allowed to 
stand for 30 seconds and washed off with water. 
5. The smear was decolourized with BD decolourizer for 10 seconds and washed with 
water. 
6. The smear was completely covered with BD safranin for 60 seconds to 
counterstain and washed with water. 
7. The back of the slide was wiped of the excess water and air dried on a slide rack 
8. The slide was examined with the microscope using the X100 objective and oil 
immersion on it. 
Results 
1. GRAM positive bacteria are violet in colour 
2. GRAM negative bacteria are red/pink  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Appendix C: Antigenic Profile Index 20 Enterobacteriaceae Biochemical Testing 
Oxidase Test 
The Oxidase Test was first performed on the colonies to be tested according to the 
manufacturer’s instructions (Becton Dickson Company, USA).  
Preparation of the API Strip 
An incubation box consisting of a tray and lid was prepared and about 5ml of distilled 
water distributed into the honey-combed wells of the tray to create a humid atmosphere. 
The strip was removed from the packaging and placed in the incubation box. 
Preparation of the inoculum 
An ampule of the API NaCI 0.85% medium (5ml) was inoculated with the test organism 
using a sterile pipette used to remove the colony from the culture plate. (Young colonies 
grown within 18 to 24 hours were used). 
This was carefully emulsified to achieve a homogenous bacterial suspension. 
Inoculation of the Strip 
Using the same pipette, the bacterial suspension was distributed into the tubes of the strip 
without creating bubbles in sequence as in the table. 
Table: API 20E Biochemical Tests and their Abbreviations 
Test Biochemical Test Test Abbreviation 
sequence 
1 O-Nitrophenl-B-D-galactosidase ONPG 
2 Arginine dihydrolase ADH 
3 Lysine decarboxylase LDC 
4 Ornithine decarboxylase ODC 
5 Citrate Utilization CIT 
6 Hydrogen Sulfide production H2S 
7 Urease production URE 
8 Tryptophane deaminase production TDA 
9 Indole production IND 
10 Acetoin production VP 
11 Gelatinase production GEL 
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12 Glucose fermentation GLU 
13 Mannitol fermentation MAN 
14 Inositol fermentation INO 
15 Sorbitol fermentation SOR 
16 Rhamnose fermentation RHA 
17 Sucrose fermentation SAC 
18 Melibiose fermentation MEL 
19 Amygdaline fermentation AMY 
20 Arabinose fermentation ARA 
 
For the CIT, VP and GEL tests both the tubes and the cupule of the test was filled with the 
bacterial suspension. 
For the other tests only, the tubes were filled. 
For ADH, LDC, ODC, H2S and URE an anaerobic condition was created by overlaying 
with mineral oil. 
The tubes and the cupules were incubated at 360C±20C for 18 to 24 hours. 
Reading of results 
After the incubation period the Strip was read. 
If three or more tests are positive all the spontaneous reactions are recorded on the result 
sheet.  
For tests such as TDA, IND and VP that required addition of reagents that was performed 
as follows; 
TDA – A drop of TDA reagent was added. A reddish-brown colour indicated a positive 
reaction 
IND – A drop of JAMES reagent was added. The development of a pink colour indicated a 
positive reaction. 
VP – A drop of VP 1 and VP 2 reagents were added. The development of a pink or red 
colour within 10 minutes indicated a positive reaction. 
Interpretation 
On the result sheet the tests are separated into three groups and a value of 1, 2, or 4 
indicated for each.  
By adding together, the values corresponding to positive reactions within group, a 7-digit 
profile number was obtained for the 20 tests of the API 20E Strip. The oxidase test which 
was performed first constitutes the 21st test and has a value of 4 if it was positive. 
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Identification 
The identification was performed by keying in the 7-digit numerical profile in the API 20 
E database (bioMérieux, France). 
Appendix D: Polymerase Chain Reaction work 
Zymo Research DNA Extraction Kit (USA) 
Kit Content (ready for use) 
Quick DNA mini preparation D3024  
Kit size 50 preparations 
Genomic lysis buffer 50ml 
DNA Pre-wash buffer 15ml 
g-DNA wash buffer 50ml 
DNA elution buffer 10ml 
Zymo-Spin Columns 50 
Collection tubes 100 
 
Preparation of PCR reagents 
Primers reconstitutions (Inqaba Biotec West Africa Ltd) 
1. ctxAF – sequence:CTCAGACGGGATTTGTTAGGCACG – 44.92nmoles. 100µM 
stock was prepared by adding 449.19µl of Tris EDTA buffer. 
2. ctxAR – sequence:TCTATCTCTGTAGCCCCTATTACG – 35.27nmoles. 100µM 
stock was prepared by adding 352.69µl of Tris EDTA buffer. 
3. O139rfbF – sequence: AGCCTCTTTATTACGGGTGG – 79.87nmoles. 100µM 
stock was prepared by adding 798.66µl of Tris EDTA buffer. 
4. O139rfbR – sequence: GTCAAACCCGATCGTAAAGG – 31.17nmoles. 100µM 
stock was prepared by adding 311.69µl of Tris EDTA buffer. 
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5. ompWF - sequence: CACCAAGAAGGTGACTTTATTGTG – 45.03nmoles. 
100µM stock was prepared by adding 450.3 µl of Tris EDTA buffer. 
6. ompWR - sequence: GGTTTGTCGAATTAGCTTCACC – 39.11nmoles. 100µM 
stock was prepared by adding 391.05µl of Tris EDTA buffer. 
7. O1rfbF - sequence: GTTTCACTGAACAGATGGG – 42.14nmoles. 100µM stock 
was prepared by adding 421.4 µl of Tris EDTA buffer. 
8. O1rfbR - sequence: GGTCATCTGTAAGTACAAC – 64.87nmoles. 100µM stock 
was prepared by adding 648.7µl of Tris EDTA buffer. 
 
Preparation of working primer solution from the stock 
To prepare 10µM from the working stock solution, 10µl of the reconstituted stock was 
taken and 90µl of nuclease-free water added. 
All stock and the working primer solutions were stored at -200C. 
 
Preparation of 1.5% agarose gel for PCR Amplification 
1. 1.5% (1.5g) of agarose was weighted and dissolve in 100ml 1% Tris acetate EDTA 
buffer. 
2. It was heated to melt completely and allowed to cool to about 450C. 
3. 3µl of ethidium bromide was added to the 100ml. 
4. The gel casting tray was arranged together with the comb. 
5. The molten agarose gel was poured into the casting tray and allowed to set. 
 
Preparation of Master Mix for PCR 
1. 
 Components Volume for 1 tube Volume for 38 tubes 
1 1 Taq 2X Master Mix buffer 6.25µl 237.5µl 
2 10µM ctxAF primer 0.25µl 9.5µl 
3 10µM ctxAR primer 0.25µl 9.5µl 
4 Template DNA 1µl - 
5 Nuclease-free water 4.75µl 179.5µl 
6 Total vol. 12.5µl 436µl 
 
2. 
 Components Volume for 1 tube Volume for 38 tubes 
1 1 Taq 2X Master Mix buffer 6.25µl 237.5µl 
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2 10µM ompWF primer 0.25µl 9.5µl 
3 10µM ompWR primer 0.25µl 9.5µl 
4 Template DNA 1µl - 
5 Nuclease-free water 4.75µl 179.5µl 
6 Total vol. 12.5µl 436µl 
 
3.  
 Components Volume for 1 tube Volume for 38 tubes 
1 1 Taq 2X Master Mix buffer 6.25µl 237.5µl 
2 10µM O1rfbF primer 0.25µl 9.5µl 
3 10µM O1rfbR primer 0.25µl 9.5µl 
4 Template DNA 1µl - 
5 Nuclease-free water 4.75µl 179.5µl 
6 Total vol. 12.5µl 436µl 
 
4. 
 Components Volume for 1 tube Volume for 38 tubes 
1 1 Taq 2X Master Mix buffer 6.25µl 237.5µl 
2 10µM O139rfbF primer 0.25µl 9.5µl 
3 10µM O139rfbR primer 0.25µl 9.5µl 
4 Template DNA 1µl - 
5 Nuclease-free water 4.75µl 179.5µl 
6 Total vol. 12.5µl 436µl 
 
Appendix E: Outputs for Multicollinearity, goodness of fit and reliability tests 
Multicollinearity Test 
Socioeconomic Characteristics 
Variable VIF SQRT VIF Tolerance R-Squared 
Religion 1.02 1.01 0.9797 0.0203 
Marital Status 1.13 1.06 0.8819 0.1181 
Employment status 1.13 1.06 0.8887 0.1113 
Educational level 1.48 1.22 0.6751 0.3249 
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Wealth index 1.23 1.11 0.8144 0.1856 
Income 1.32 1.15 0.7568 0.2432 
Mean VIF 1.22       
 
Behavioural 
Variable VIF SQRT VIF Tolerance R-Squared 
q59eat 1.01 1 0.9913 0.0087 
q61cook 1.01 1.01 0.9897 0.0103 
q66hawas 1.02 1.01 0.985 0.0150 
Mean VIF 1.01       
 
Environmental Risk Factors 
Variable VIF SQRT VIF Tolerance R-Squared 
          
Landfill site 1.18 1.08 0.8498 0.1502 
Toilet facility 1.18 1.09 0.8491 0.1509 
Drainage system 1.48 1.22 0.6766 0.3234 
Market 1.46 1.21 0.684 0.316 
Mean VIF 1.32       
 
 
 
 
 
Goodness of Fit Test 
Socio-
  Behavioural Environmental 
demographics 
Log-likelihood                   
Intercept only 147.835 -145.264 -152.259 
Full model 132.719 -137.288 -132.412 
        
Information criteria                                      
AIC 315.439 294.575 282.825 
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BIC 435.665 342.621 326.106 
        
R^2                                      
Cox-Snell/ML 0.033 0.018 0.043 
Cragg-Uhler/Nagelkerke 0.118 0.064 0.15 
Efron 0.041 0.025 0.042 
McFadden 0.102 0.055 0.130 
McFadden(adj) -0.067 -0.014 0.071 
McKelvey & Zavoina 0.175 0.149 0.307 
Tjur's D 0.047 0.023 0.047 
 
Reliability test for sanitation index score 
Test Scale Mean (unstandardized items) 
Average interitem covariance  0.0286011 
Number items in the scale 13 
Scale reliability coefficient 0.7591 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Appendix F: Household Questionnaire  
Form Number    
 
House Number/landmark  
 
Head of household or responder’s contact/  
phone number 
Name of location/zone  
 
Name of Community  
 
Name of Sub Metropolis  
 
Name of Metropolis/Municipality/District  
 
Indicate whether community is Endemic or  
Non endemic for cholera 
 
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NAME OF RESEARCH ASSISTANT    
NAME: ……………………………………… DATE………………………………………
  
 
DATA KEYED IN BY    
NAME: ……………………………………… DATE: …………………………………… 
RESULT CODES 
  
01 Completed  
02 Not completed  
Record Start Time (GMT): 
 
 
Record Finish Time (GMT) 
 
Household GPS Coordinates: 
Lat:________________________________________ 
 
Long:_______________________________________ 
INTRODUCTION AND INFORMED CONSENT  
NOTE: DO NOT BEGIN INTERVIEW WITHOUT GOING THROUGH THE 
CONSENT PROCESS. REFER TO INFORMED CONSENT FORM ATTACHED. The 
head of household or senior member (male or female) who can provide the household 
information is to be interviewed.  
INSTRCTIONS: Circle the appropriate response codes or specify your response by 
writing in the space provided 
Q.no. Questions  Codes/Answers Skips FIELDS 
1. ID        ID  
 
 
2. Date of Interview          DOI 
 
 
 Socio-demographic    
Factors 
3. How old are you?(age   AGE 
in completed years) 
  
  
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4.  What is your sex? 1. Male    SEX 
2.Female 
 
5. What is your marital 1. Single  MAR 
status? 
2. Cohabitating 
3. Married 
4. Separated 
5. Divorced 
6. Widowed 
 
6. What religion do you 1.No religion  RELG 
belong to? 
2.Christian 
3.Islam 
4.Traditional 
5.Others (specify) 
 
    --------------------------------- 
 
7. What is your 1.Ghanaian  NAT 
nationality? 
2.Non Ghanaian (specify) 
 
-------------------------------------- 
 
8. To which ethnic group   ETHN 
do you belong? 
------------------------------- 
 
 
 
 
9. What is your current 1.Unemployed Skip to11 EMPL 
employment status? 
2.Retired worker               
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3.Formal employed 
4.Informal employed 
 
10. What is your   OCCP 
occupation? 
----------------------------------------- 
 
11. What is your 1.No formal Education  EDUC 
educational level? 
2.Primary Education 
3.JSS/Middle school Education 
4.Senior High Education 
5.Tertiary Education 
 
12. What is your income 1.Low income ( <Gh₵300)  INCOM 
level? (salary, business, 
2.Medium income (>Gh₵300 - 
remittance, pensions 
Gh₵1000) 
etc) 
3.High income (>Gh₵1000 –  Gh₵2000) 
 
4.Highest income (>Gh₵2000) 
(Average per month) 
 
 
13. Does your household 1.Yes  ELECT 
have electricity supply? 
2.No   Skip to15 
 
14. What is the source of 1.ECG  SOELE 
the electricity? 
2.Own generator 
3.Solar cells 
4.Other (specify) 
----------------------------------------- 
 
15. Does your household 1.Yes  TV 
have a Television set? 
2.No 
 
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16. Does your household 1.Yes  REFRI 
have a refrigerator? 
2.No 
 
17. What type of fuel does 1.Electricity  FUEL 
your household use for 
2.LPG 
cooking? 
3.Natural gas 
 
4.Biogas 
(Multiple response 
possible) 5.Kerosene 
6.Coal 
7.Charcoal 
8.Wood 
9.Straw/grass 
10.Animal dung 
11.Other (specify) 
………………………………….. 
12. No food cooked in the household 
 
 
18. In what type of building 1.Detached  house  DWELL 
does the household 
2.Semi-detached 
live? 
3.Flat/apartment 
4.Compound house (rooms) 
5.Tent 
6.Improvised house (kiosk/container) 
7.Living quarters attached to office/shop 
8.Uncompleted building 
9.Other (Specify) 
 
--------------------------------- 
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19. What kind of material 1.Cemented block house  MATER 
was used for the 
2.Brick house 
building? 
3.Stone house 
3.Mud house 
4.Wooden/plywood house 
5.Other (Specify) 
 
   -------------------------------- 
 
20. How long have you   LENGT 
been living in this 
  
community? 
  
 
(in years) 
 
21. How many people live   NUMB 
in your household 
  
including you? 
 
 
 Water related factors    
 
 
 
22. What is the main source 1.Piped into house Skip to 27 WASO 
of drinking water for 
2.Piped to yard/plot Skip to 27 
members of your 
household? 3.Public tap/standpipe  
 4.Tube well or borehole  
(Choose only one) 5.Protected dug well   
6.Unprotected dug well  
7.Protected spring  
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8.Unprotected spring  
9.Rain water  
10.Tanker truck  
11. Cart with small tank  
12.Surface water  
(river/dam/lake/pond/stream/canal/irrigati
 
on channel) 
 
13.Bottled water 
Skip to 27 
14.Sachet water 
Skip to 27 
15.Others (specify) 
 
----------------------------------- 
 
23. Where is that drinking 1.In own house/dwelling Skip to 25 WASOL 
water, source located? 
2.In own yard Skip to 25 
3.Elsewhere  
 
24. How long does it take   TIMWS 
to go there, get your 
  
drinking water, and 
 
come back? 
 
 (in minutes) 
 
25. Do you do anything to 1.Yes   
the water to make it 
2.No Skip to 28 
safer to drink? 
3.Don’t know Skip to 28 
 
26. What do you usually do 1.Boil  WTREAT 
to make the water safer 
2.Add bleach/chlorine/alum 
to drink? 
3.Strain through a cloth/ strainer 
 
4.Use water filter (e.g ceramic, sand, 
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(Multiple response composite etc) 
possible) 
5.Solar disinfection 
 
6.Let it stand and settle 
 
7.Camphor/naphthalene 
 
8.Purification tablet 
 
9.Others (specify) 
---------------------------------------------- 
27. If your main source of    
drinking water is 
 
bottled or sachet water, 
what is the brand that -------------------------------------------- 
your household mostly 
drink? 
 
28. How does your 1.Plastic container (buckets/barrels/jerry  WASTOR 
household store cans) 
 
drinking water? 
2.Pot/earthenware vessels  
 
 
3.Metal container  
 
(Multiple response 
4.Elevated polytank  
possible)  
5.Bottled/sachet 
 Skip to 30 
6.Others (specify) 
 
 
---------------------------------------- 
 
29. Is the storage vessel for 1.Yes  STCOV 
the stored drinking 
2.No 
water always covered 
or closed? 3.Don’t know 
  
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30. Apart from the drinking 1.Piped into house  WADOME 
water sources, what 
2.Piped to yard/plot  
other water sources do 
you use for domestic 3.Public tap/standpipe  
purposes such as 
4.Tube well or borehole Skip to 32 
bathing, cooking and 
washing of utensils 5.Protected dug well  Skip to 32 
(plates, spoons, bowls 
etc) 6.Unprotected dug well Skip to 32 
 7.Protected spring Skip to 32 
(Multiple response 8.Unprotected spring Skip to 32 
possible) 9.Rain water Skip to 32 
 10.Tanker truck Skip to 32 
 11. Cart with small tank Skip to 32 
 12.Surface water Skip to 32 
(river/dam/lake/pond/stream/canal/irrigati
 
on channel) 
Skip to 32 
13.Others (specify) 
 
 
 
----------------------------------- 
 
31. If your household uses 1.Always  WASUL 
piped borne water, do 
2.Often 
you experience any 
shortages? 3.Sometimes 
 4.Never 
(Choose only one) 5.Don’t know 
  
 Solid waste disposal    
factors 
32. What kind of toilet 1.Flush to piped sewer system  KTOI 
facility is used by 
2.Flush to septic tank  
members of your 
household at home? 3.Flush to pit latrine  
 4.Flush to somewhere else  
(choose only one) 5.Flush don’t know where it goes  
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6.Ventilated improved pit latrine (KVIP)  
7.Pit latrine  
8.Pit latrine with slab  
9.Pit latrine without slab/open pit  
10.Bucket toilet  
11.No facility/bush/field  
12.No facility/use public toilet Skip to 38 
13.Others (specify) Skip to 36 
 
------------------------------- 
 
33. If there is a toilet 1.Yes, with other households only  TOISHAR 
facility at home, do you 
2.Yes, with public Skip to 35 
share this with other 
households? 3.No   Skip to 35 
  
34. How many households   NUMTOI 
use or share this toilet 
  
facility? 
 
 
35. Where is this household 1.In own house/dwelling Skip to 37 TOILOC 
toilet facility located? 
2.In own yard Skip to 37 
  
36. How long does it take    
to go to the public 
  
toilet, use it, and come 
back?  
     (minutes)  
37. Is a hand washing 1.Yes  HWDH 
facility/device available 
2.No  
for use immediately 
after defecation at the 
toilet? 
 
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38. Where do you usually 1.Plastic bags  REFSTOR 
store your household 
2.Cardboard boxes  
refuse (rubbish) before 
disposal? 3.Rubbish bin  
4.Sacks  
5. No storage-direct disposal   
6.Others (specify)  
  
------------------------------  
39. How does the 1.Collected by a waste company  REFDIS 
household dispose of 
2.Burned by household Skip to 42 
refuse (rubbish)? 
3.Public dump site (covered) Skip to 42 
 
Skip to 42 
4.Public dump site (opened) 
(Multiple response 
Skip to 42 
possible) 5.Dumped indiscriminately 
Skip to 42 
 6.Buried by household 
Skip to 42 
7.Others (specify) 
 
----------------------------- 
40. Which waste collection   WASCOM 
company collects your 
------------------------------------------ 
household waste? 
 
 
41. How often is refuse 1.Daily Skip to 43 TWASC 
(rubbish) collected by 
2.Weekly Skip to 43 
the waste collection 
company? 3.Monthly Skip to 43 
4.As to when the waste bin is full Skip to 43 
5.Never collected Skip to 43 
 
42. Why is your household 1.Financial reasons (charges are high)  WNC 
refuse not collected by 
2.Waste collection companies are not 
a waste collection 
available 
company? 
3. Waste collection companies are 
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 available but not reliable 
(multiple responses 4.No waste disposal bin 
possible) 
5. others (specify) 
 
 
----------------------------------------- 
 
43. Do you have a public 1.Yes  PUBREF 
refuse (rubbish) dump 
2.No Skip to 45 
site or landfill site near 
your neigbourhood? 3.Don’t know Skip to 45 
 
44. How long does it take   TPUBREF 
you to walk from home 
  
to the refuse disposal 
 
site or landfill site? 
(in minutes) 
 
 Liquid waste disposal    
factors 
 
45. Is there a drainage 1.Yes  BATHF 
system to take away the 
2.No Skip to 47 
household liquid waste? 
3.Don’t know Skip to 47 
 
46. What kind of drainage 1.Open drainage (open gutter)  KDRAIN 
system is it? 
2.Covered drainage (covered gutters) 
3.Underground drainage (pipes 
connection to sewage) 
4. Others (specify) 
 
---------------------------------- 
 
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47. How does your 1.Through the sewage system to septic  DISLIQK 
household dispose-off tank 
liquid waste from 
2.Thrown onto the street/outside 
kitchen and washings? 
3.Thrown into gutter 
4.Thrown onto the compound 
5.Others (specify) 
 
-------------------------------------- 
48. How does your 1.Through the sewage system  DISLIQB 
household dispose of 
2.Through drainage into a pit (e.g soak 
the liquid waste from 
away) 
the bath? 
3.Thrown onto the street/outside 
 
4.Thrown into gutter 
 
5.Thrown onto the compound 
 
6.Others (specify) 
 
 
-------------------------------------- 
 
     
Environmental 
related factors 
 
49. Is there any water body 1.Yes  AQR 
(sea, river, lagoon, 
2. No Skip to 52 
stream, pond,lake etc) 
located near your 
neighbourhood? 
 
50. What type of water 1.Stream  TYAQR 
body is located near 
2.Lagoon 
your neighbourhood? 
3.Pond 
 
4.Lake 
(Multiple response 
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possible) 5.River 
 6.Sea 
7.Others (specify) 
 
------------------------------------------ 
 
51. How long does it take    TAQR 
you to walk from home 
  
to the water body site 
 
and back?  
 
(in minutes) 
 
52. Do you have a market 1.Yes  MARKET 
near your 
2.No Skip to 56 
neighbourhood? 
 
 
If yes, what is the name of the market? 
 
 
 
_____________________________ 
 
 
 
 
 
53. How long does it take   TMARKET 
you to walk from home 
  
to the market and back? 
 
 
 
 (in minutes) 
 
 
 
 
 
54. Do you buy your food 1.Yes  BFSTUFF 
stuff from that market? 
2.No Skip to 56 
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55. Do vendors screen their 1.Yes, always  VENSFISH 
smoked or fried fish 
2.Yes, often 
from flies and dust in 
that market? 3. Yes, sometimes 
 4. No, never 
 
56. Do you have an 1.Yes  ABATT 
abattoir/slaughter house 
2.No Skip to 59 
near your 
neighbourhood?  
 
57. How long does it take    TABATT 
you to walk from home 
  
to the abattoir/slaughter 
 
house and back?  
 
(in minutes) 
 
58. Do butchers screen or 1.Yes, always  BUTCS 
protect the meat from 
2.Yes, often  
flies and dust? 
3. Yes, sometimes 
4. No, never 
 
     
Behavioural Factors  
 
 Food safety    
59. What is the food eating 1.Only eat food cooked at home  EATHAB 
habit of your 
2.Eat food cooked from home and  
household? 
outside home 
 
 
3.Only eat food from outside home 
Skip to 62 
(choose only one) 
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60. Does your household 1.Yes, always  COOK 
usually cook food at 
2.Yes, often  
home? 
3. Yes, sometimes  
 
4. No, never Skip to 63 
 
  
 
 
 
61. Where is the cooking 1.Inside the house/dwelling  WCOOK 
done in your 
2.In a separate building 
household? 
3.Outdoors (in the yard) 
 
4.Others (specify) 
 
 
 
--------------------------------- 
 
 
 
62. How does your 1.washed in water only  RAWVEG 
household mostly treat 
2.washed in water and heat steam 
raw vegetables such as 
cabbage, lettuce, 3.washed in salt water 
cucumber, carrot, 
4.washed in salt water and heat steam 
spring onions etc before 
eating it at home? 5.heat steam or parboiled only 
 6.washed in vinegar 
(choose only one) 7.washed in vinegar and heat steam 
 8.other (specify) 
 
--------------------------------------- 
9.Does nothing to it 
 
63. Does your household 1.Yes  LEFTOV 
eat left over foods? 
2.No   Skip to 66 
 
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64. How does your 1.left uncovered in the room/kitchen  STOLEFT 
household always store 
2.Covered and left in the room/kitchen 
the left-over foods? 
3.Put in the refrigerator/fridge 
 
4.Put in a freezer 
(choose only one) 
5. Others (specify) 
 
-------------------------------------------- 
 
65. How is left over foods 1.Eaten cold in the next meal  TRELEFT 
usually treated before 
2.Reheated to boil before eating 
eating in your 
household? 3.Warmed in the microwave before eaten 
 4.Others (specify) 
(choose only one)  
 ------------------------------------------- 
  
 
 
 
 
 
 
66. How does your 1.Wash hands in a bowl of water   HAWASH 
household member 
2.Wash hands with soap in a bowl of 
wash their hands before 
water  
meals at home? 
3.Wash hands under running water (from 
 
tap or poured)  
(choose one common 
4. Wash hands with soap under running 
hand washing 
water (from tap or poured) 
procedure often used at 
home) 5.Wash hands with water and ashes 
 6.Other (specify) 
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----------------------------------------- 
67. What does your 1.They are washed with soap under safe  FRUIT 
household mostly do running water  
before eating fruits e.g 
2.They are washed with safe running 
mangoes, oranges, 
water 
water melon, apple etc 
in your home? 3.They are washed with water and soap 
in a bowl 
 
4.They are washed with water in a bowl  
(choose only one) 
5.They are not washed 
 
6.Other (specify) 
 
-------------------------------------------- 
 
 Cholera infection in    
the households and 
neighbourhood in the 
past 
 
68. Have you heard about 1.Yes   
cholera (profuse 
2.No 
painless diarrhoea with 
or without vomiting? 
 
69. Has any member of 1.Yes   CHOL 
your household 
 2.No Skip to 74 
suffered from cholera 
 before? 
 
 
 
 
 
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70. What treatment did you 1.Nothing  CHOLTRE 
immediately give to the 
2.Traditional herbs 
household member to 
stop the diarrhoea?  3.Home prepared salt solution 
 4.ORS 
3.Others (specify) 
 
--------------------------------------------- 
 
71. Where was the 1.Hospital/Polyclinic  HELSEEK 
household member 
2.CHPs 
taken to for health care?  
3.Pharmacies/Drug chemical shop 
4.Traditional healer 
5.Stayed at home 
6.Others (specify) 
 
--------------------------------------------- 
 
72. How long did it take   TSEEHEL 
you to decide to send 
1.≤ 2 days 
the house member to 
clinic/hospital/CHPs  
when he/she started 
2.>2 days 
showing signs of 
cholera?  
   
(report in days) 
 
73. How long did it take   TTHF 
you to reach the health 
1.<5 hours 
facility 
(hospital/clinic)?  
 2.≥5 hours 
(report in hours) 
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74. Has any person 1.Yes END HISCHOL 
suffered from cholera 
2.No 
in your neigbourhood 
before? 3.Don’t know 
 
 
  
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Appendix G: Environmental Health Inspection Guide 
FORM NUMBER 
   
  
ID       
 
Community location/zone  
 
Name of community  
 
Name of Sub Metro  
 
Name of Metro/Municipal/District  
 
Date of Environmental Assessment         
 
 
 No.       Ask and Observe in households and community Sanitation  
 Water Supply Pipelines  
1. Are there exposed water pipelines? 1. Yes 
2. No 
2. Are pipelines laid through open drains or gutters? 1. Yes 
2. No 
3. Are there any broken or leaking pipelines? 1. Yes 
2. No 
4. Does water accumulate around the pipelines? 1. Yes 
2. No 
 Take photographs of these exposed or broken pipelines  
and geopoints of these. 
 Refuse Disposal  
5. Is there a refuse (rubbish) dumping site or landfill site in 1. Yes 
the neighbourhood? 
2. No 
 
6. Is the refuse dump containers overflowing? 1. Yes 
2. No 
7. Are there flies around the refuse dumpsite or landfill site? 1. Yes 
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2. No 
8. Is the refuse dumpsite or landfill site near a water source? 1. Yes 
2. No 
 Take photographs of these and geopoints of refuse  
disposal site 
 
 Sewage Disposal  
9. Are the gutters or drains choked with waste/refuse/human 1. Yes 
excreta and impedes free flow of storm and waste water?  
2. No 
10. Are there over growth of weeds providing cover for 1. Yes 
indiscriminate disposal of sewage? 
2. No 
11. Are there evidence of liquid waste or sewage (effluent) 1. Yes 
discharge into a water body (e.g sea, river etc) in the 
2. No 
community? 
 Take photographs of these and geopoints of public toilets  
 
 Excreta Disposal  
12. Are there public toilets in the community? 1. Yes 
2. No 
13. Does the public toilet facility attract house flies? 1. Yes 
2. No 
14. Is there any evidence of open defecation in the 1. Yes  
community? 
2. No 
 Take photographs of these and geopoints of public toilets  
 
   
 
 
 
 
 
 
 
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Appendix H: Consenting Process 
Volunteer Agreement 
I have read the foregoing information or it has been read to me on ‘Identification and 
mapping of risk factors associated with cholera in endemic communities in the 
Greater Accra Region’. I had the opportunity to ask questions and was told my 
confidentiality will be assured by not linking my name to any data, participation was 
voluntary and I could stop at any stage of the study, there was no direct benefit to me and 
no unforeseen risk associated. I was also told there was no compensation for participating 
in the study and that I will be given a copy of the consent form. My questions were 
answered to my satisfaction and I agree to participate as a volunteer. 
________________________                                _____________________________ 
Date                                                                         Signature or thump print of volunteer 
If a volunteer does not understand the English language, a translator will translate in the 
volunteer native dialect and sign. 
________________________                              ______________________________ 
Date                                                                       Signature or thump print of translator 
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If a volunteer cannot read the form themselves, a witness must sign here: 
I was present while the benefits, risks and procedures were read to the volunteer. All 
questions were answered and the volunteer has agreed to take part in the research. 
_______________________                                     _______________________________ 
Date                                                                             Signature of Witness 
I certify that the nature and purpose, the potential benefits, and possible risks associated 
with participating in this research have been explained to the above individual. 
______________________                                 _______________________________ 
Date                                                                      signature of Person who obtained consent 
 
  
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Appendix I: Ethical Clearance 
 
 
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