Awalime et al. Health Economics Review  (2017) 7:45 
DOI 10.1186/s13561-017-0182-2
RESEARCH Open Access
Economic evaluation of 2014 cholera
outbreak in Ghana: a household cost
analysis
Dziedzom Kwesi Awalime1,2*, Bernard Bright K. Davies-Teye2, Linda A. Vanotoo2, Nkechi S. Owoo1
and Edward Nketiah-Amponsah1
Abstract
Introduction: Ghana experienced its worst cholera outbreak in three decades in 2014. Evidence of cholera economic
costs on affected households has been limited. This study aimed at determining economic costs on households
affected by the cholera outbreak in a Coastal Region of Ghana.
Methods: Two districts; High and Low Incidence Areas (HIA and LIA) were selected in comparative cost analysis and
disease impact on affected households assessed based on scientifically documented economic indicators. A total of
418 (282 HIA and 136 LIA) households that experienced at least one case of cholera infection were interviewed. Direct
and indirect costs were estimated. Correlates of household’s cholera infection were estimated using Tobit Regression
model in STATA 13.
Results: Average direct cost to households in HIA amounted to USD 106.88, almost 2 folds higher than LIA (USD
62.02). Potential cost saving of an episode of cholera is USD 99,201.28 in LIA and raises almost 8 folds in HIA (USD
782,611.60). Households in lowest income category had the highest incidence of cholera (0.073) compared to other
categories plus other factors were significant in explaining cholera incidence.
Conclusions: The study showed considerable differences in HIA and LIA costs with higher household economic
impact of cholera on the lowest income category. Results underscore the need for pragmatic policy interventions to
avert recurrent outbreaks and emphasis huge potential cost saving with reducing cholera cases.
Keywords: Cholera, HIA, LIA, Cost of illness, Household, Ghana
Background [2, 3]. These factors pose a great burden on households
Economic measurements of disease complement clinical which experience diseases such as cholera that presents
and epidemiological approaches in disease burden symptoms only after patient is acutely ill.
assessment. Economic analyses seek to address a number “Cholera represents an estimated burden of 1.3 to
of policy questions on consequences of disease or injury 4.0 million cases, and 21,000 to 143,000 deaths per year
[1]. Economic measurements ultimately translate into worldwide” [4]. However, there could be as much as
cost-savings with reduction of adverse health effects. 100,000 to 120,000 cholera deaths every year but coun-
Health ‘shocks’ such as unexpected health expenditures, tries normally fail to report actual numbers due to fear
reduced functional capacity and lost income and product- of external economic implications on sectors like trade
ivity are primary risk factors for health impoverishment and tourism [4]. These numbers are corroborated by Ali
et al. [5].
In parts of Ghana, cholera is now endemic and the
country experiences outbreaks about every 5 years. In
* Correspondence: dawalime@gmail.com
1 2014, Ghana together with Nigeria and DR Congo re-Economics Department, University of Ghana, Legon, P. O. Box LG 25, Accra,
Ghana ported 83% of all cases in Sub-Saharan Africa [6]. In that
2Ghana Health Service, Regional Health Directorate, P. O. Box 184, Accra,
Greater Accra Region, Ghana
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
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Awalime et al. Health Economics Review  (2017) 7:45 Page 2 of 8
same year, Ghana experienced its worst outbreak in three respectively. More specifically, households were ran-
decades reporting 28,944 cases including 243 deaths com- domly selected from patient population database using a
ing only second to Nigeria in infection rates [6, 7]. calculated sampling interval to help answer the research
Research on cholera in Ghana has focused more on epi- objectives of this study. Data collection was primary
demiology of outbreaks and little emphasis on economic through interviews. Patients who were untraceable
costs. Studies which identify socio-economic factors [8–10] where replaced by new ones who were sampled through
are not detailed but provide mostly socio-economic the same random selection process, traced and inter-
linkages. viewed. There was over 90% response rate and those
This study estimated comparative cholera costs in high who refuse to grant interview were also replaced. All
and low incidence areas (HIA & LIA) plus correlates questionnaires were retrieved and data entered for
among cholera affected households. These provide analysis.
empirical evidence to a lean literature on economic eval-
uations of cholera. Cost estimation
Direct costs
Methods Direct costs included; first aid, cost of transportation for
The study used Cost-of-Illness approach by Rice [11] in- patient and caregiver, consultation fees, drugs purchased,
cluding WHO guidelines [1] for estimating economic laboratory cost, facility admission cost (hoteling cost),
consequences of disease and injury. This guided the as- under-the-table payments (unofficial payments), feeding
sessment of household costs. Data on direct and indirect costs (special diet and water) and burial costs (super-
cost implications were collected using structured vised burial) in the event of death. An accounting
questionnaires. process was followed where all costs attributing to
various components were summed to obtain the disease
Study sites cost. Costs were separated based on low and high inci-
The study was conducted in La-Dadekotopon and dence area costs.
Shai-Osudoku districts within the Greater Accra Region.
Historically, the region has become the epicenter for Indirect costs
cholera outbreaks in the country. At the end of 2014, The method adopted for measuring indirect cost (op-
La-Dadekotopon and Shai-Osudoku documented 1907 portunity cost of ailment) was similar to that adopted
and 315 cholera cases respectively. These districts by Sarker et al. [12]. This was done by computing the
ranked second and eighth respectively among the top average household earnings as the base for determin-
ten districts that reported cases and where selected as ing the opportunity cost for the household. This
high and low incidence districts respectively. Distinctive average was then multiplied by the time component
feature of these areas are that one is urban, highly pol- spent by the patient or caregiver for the time spent
luted indigenes with mostly poor communities whilst in travelling to and fro health facility, on admission
the other is rural sparely populated mixed communities. and recovery after discharge. The time components
These inherent differences help to understand the inci- include; travel time to facility, time spent at facility
dence and costs implications within these areas. till discharge and work or school days lost after
discharge. Waiting time with cholera treatment is re-
Data and sampling duced to zero because all cases brought into facilities
Patient data was obtained from the Ghana Health are treated as emergencies and hence are not signifi-
Service line list for cholera outbreak. This contained cant to this study. To ensure time loss estimates are
names, place of residence, sex, age, laboratory test re- not overweighed, during data collection only actively
sult, outcome of treatment and the telephone contact employed patients and caregivers were assumed to be
of patient. GHS used this database in contact tracing losing productive hours and unemployed patients and
of cases and this same tool was used in tracing pa- caregivers time loss assumed to be zero.
tients to their households. For the purposes of this
study, population was defined as all positive cases of Cholera correlates
cholera reported from a particular district. These The study further examined relationship between
formed the basis of inclusion criteria with all other cholera affected households using Tobit Regression
households excluded for no documented cases at the model by observing the relevance of income categor-
health facilities. ies and other household characteristics in relation to
Random sampling procedure was adopted in selecting the proportion of household infection. Household’s
418 households; 282 and 136 from a HIA and LIA characteristics were examined within this framework,
Awalime et al. Health Economics Review  (2017) 7:45 Page 3 of 8
testing which income groupings bore the greatest cholera treatment was declared free but this outcome
burden of the outbreak. shows the contrary. In the HIA, direct cost compos-
The empirical model is specified as: ition showed treatment cost (49.49%) as the largest
component of the direct cost, followed by admission
iC ¼ β0 þ β1INC þ β2SEX þ β3MS þ β4RHH cost (23.47%), transportation for both patient and
þ β AGE þ β EDU þ β HI þ β DWS caregiver (12.63%), feeding (12.09%) then first aid5 6 7 8
(2.32%) (see Table 1).
iC = proportion of Household members Infected From Table 2 on average it cost a household in a
(number of infected persons divided by total household HIA GH¢342.00 (USD 106.88) and GH¢198.47 (USD
size). 62.02) in a LIA to seek treatment. When compared
INC= income category (categorical dummy; base: in- to average costs reported by Sarker et al. [12] in
come above GH¢750; USD 234.38). Bangladesh (USD 30.40) average costs are two folds
SEX= sex (dummy variable; base: male). higher in the LIA and more than three folds higher
MS= marital status (dummy variable; base: married). in the HIA.
RHH = relationship with household head (categorical The average daily wage for households in the LIA
dummy; base: Other dependents); head of household, was GH¢26.90, higher than in the HIA (GH¢22.80).
spouse, daughter or son. On the other hand the average household size in LIA
AG = age (continuous variable). (3.6) is marginally smaller compared to HIA (3.7).
EDU = education (categorical dummy; base: highest These statistics have important bearings on the esti-
education (above Secondary); none, basic, secondary/ mation of indirect costs within these two districts.
technical/vocational. Higher wages mean greater opportunity cost for lost
HI = health insurance status (dummy variable; base: man hours and household size influences the average
not insured). household income; larger households mean lower per
DWS = drinking water source (categorical dummy; capita income and greater burden of the disease on
base: Inside Plumbing/Inside Standpipe); water vendor, that household.
neighbouring house, public standpipe and others. In both districts, days missed by patients during re-
covery formed the largest composition of indirect
Results and discussion costs but was 1% higher in HIA. Indirect costs associ-
The total direct cost incurred by households in the ated with travel time were insignificant for both dis-
HIA and LIA amounted to GH¢96,444.30 (USD tricts and is explained by existence of fairly easier
30,138.84) and GH¢26,991.30 (USD 8434.78) respect- access to transportation means in both districts (see
ively (see Fig. 1 and Table 1). Treatment costs in both Fig. 2). Average admission days was the same for both
high and low incidence districts formed the highest districts (3 days) but admission days formed a larger
cost driver for households. When admissions costs proportion of total indirect cost in the LIA (25%)
were added, facility costs formed over 70% of all dir- than the HIA (19%) and in consonance, patients from
ect costs. These costs have important implications for LIA spent 2 days lesser away from normal daily activ-
the health system because during the outbreak, ities than in the HIA (7 days). These suggest that
complete recovery was faster and better in the LIA
than the HIA.
From Table 3 an average of 25 days were missed in
Total Costs in High and Low Incidence area total by patients and caregivers away from their normal
600,000.00 economic activities in the LIA but almost doubled in the
500,000.00 HIA (48 days). This translated into GH¢1055.07 (USD
329.71) and GH¢831.52 (USD 259.85) average indirect
400,000.00
cost for selected sample in the HIA and LIA respectively.
300,000.00 Indirect costs in HIA were greater for all components
200,000.00 than in LIA with the exception of productive days
missed by caregivers. Total productivity loss by pa-
100,000.00
tients was GH¢ 141, 656.40 (USD 44,287.63) and GH
0.00
La-Dadekotopon Shai-Osudoku Total ¢ 52,858.50 (USD 16,518.28) in HIA and LIA respect-
Total Direct Cost (GH¢) 96,444.30 26,991.30 123,435.60 ively. That of caregivers was GH¢56,293.20 (USD
Total Indirect Cost (GH¢) 297,529.03 113,087.21 410,616.24 17,591.63) (HIA) and GH¢28,809.90 (USD 9003.09)
Sample Total Cost GH¢ 393,973.33 140,078.51 534,051.84
(HIA). Together these costs formed over 70% of in-
Fig. 1 Total Costs in High and Low cholera incidence areas
direct cost composition.
Costs (GH¢)
Awalime et al. Health Economics Review  (2017) 7:45 Page 4 of 8
Table 1 Direct costs in high and low cholera incidence area
Direct Cost La-Dadekotopon Shai-Osudoku Total
GH¢ USD$ GH¢ USD$ GH¢ USD$
First Aid 2236.60 698.94 283.80 88.69 3219.34 1006.04
(2.32) (1.05) (2.10)
Treatment at Facility 47,729.00 14,915.31 12,885.00 4026.56 75,529.31 23,602.91
(49.49) (47.74) (49.18)
Feeding 11,658.00 3643.13 3684.00 1151.25 18,985.13 5932.85
(12.09) (13.65) (12.36)
Admission 22,637.00 7074.06 6470.00 2021.88 36,181.06 11,306.58
(23.47) (23.97) (23.56)
Transportation (Patient) 5912.00 1847.50 1410.00 440.63 9169.50 2865.47
(6.13) (5.22) (5.97)
Transportation (Caregiver) 6271.70 1959.91 2258.50 705.78 10,490.11 3278.16
(6.50) (8.37) (6.83)
Total 96,444.30 30,138.84 26,991.30 8434.78 123,435.60 38,573.63
Bracket figures are percentages
Exchange rate: 1USD = GH¢3.20 (Exchange rate as at December 31, 2014)
From Fig. 1 total cost to households were GH¢ Per capita costs within these areas amounts to GH¢
393,973.33 (USD 123,116.67) and GH¢140,078.51 1313.24 (USD 410.39) in the HIA and falls to GH¢
(USD 43,774.53) for sample selected in HIA and LIA 1007.76 (USD 314.93) in the LIA (see Fig. 4).
districts respectively. In HIA indirect costs was The regression result from Table 4 supports the fact
markedly greater (above GH¢200,000 (USD 62,500) that the impact of cholera is felt largest by the lower in-
more) but in LIA just slightly above GH¢100,000 come categories. Compared to the highest income
(USD 31,250). bracket, households in the least income bracket are 7%
In total, 2222 cholera cases were reported in health points more likely to experience a higher cholera inci-
facilities; HIA (1907) and LIA (315). When costs are dence. For households within income brackets 3 and 4,
projected for the total number of cases reported for there is a 6% points higher likely of infection compared
both districts, the total cost of the 2014 cholera out- with those in the highest income bracket. All are statisti-
break in a high incidence situation is GH¢ cally significant at 10%. These results corroborate the
2,504,357.12 (USD 782,611.60) and GH¢317,444.10 percentages in the cross-tabulation on the infection rates
(USD 99,201.28) for lower incidence (see Fig. 3). among these income categories. Both Borroto &
Hence, if high incidence cases are reduced to levels Martinez-Piedra [13] and Talavera & Pérez [14] studies
of a lower incidence scenario, cost saving will be GH support impacts of cholera being heaviest on the least
¢2,186,913.02 (USD 683,410.32). income people.
Table 2 Individual and household direct average costs
Individual Average Direct Cost HH Average Direct Cost
La-Dadekotopon Shai-Osudoku La-Dadekotopon Shai-Osudoku
GH¢ USD GH¢ USD GH¢ USD GH¢ USD
First Aid 7.46 2.33 2.04 0.64 7.93 2.48 2.09 0.65
Treatment 159.10 49.72 92.70 28.97 169.25 52.89 94.74 29.61
Feeding 38.86 12.14 26.50 8.28 41.34 12.92 27.09 8.47
Admission 75.46 23.58 46.55 14.55 80.27 25.09 47.57 14.87
Transportation (Patient) 19.71 6.16 10.14 3.17 20.96 6.55 10.37 3.24
Transportation (Caregiver) 20.91 6.53 16.25 5.08 22.24 6.95 16.61 5.19
Total 321.48 100.46 194.18 60.68 342.00 106.88 198.47 62.02
*Exchange rate: 1USD = GH¢3.20 (Exchange rate as at December 31, 2014)
Source: Survey Data; Author’s computation from Excel
Awalime et al. Health Economics Review  (2017) 7:45 Page 5 of 8
La-Dadekotopon Shai-Osudoku
a b
Days missed Days missed
0% (Patient)
19% 0%
(Patient)
Days missed 25% Days missed
(Caregiver) (Caregiver)
48% 47%
Admission Admission
33% Days Days28%
Travel Time - Travel Time -
Days Days
Fig. 2 a and b Indirect Cost Composition in high and low incidence areas
Households with unmarried persons have 14% be some contextual underpinnings accounting for
likely incidence than their married counterparts. In these mixed results from these two different studies.
2013, an Oxfam research report on gender and vul- This can however be understood through future
nerability to cholera in Sierra Leone showed higher investigation.
infection among unmarried males compared to mar- Within household composition, cholera impact was
ried males [15]. greatest among household heads’ dependents. A 15%
Within the household composition, the impact of higher proportion of cholera incidence was among
cholera was highest among dependents of household this group in compared to household head. Spouses
heads in the sample. There was 15% higher cholera inci- however had 4% less incidence of the disease during
dence among this group in relation to the head of the outbreak.
household. Spouses however had 4% less likely incidence The incidence of cholera and sources of water can-
of the disease. not be exaggerated and studies such as Crooks &
Among adults is a higher tendency to eat away Hailegiorgis [17] support this fact. The safest source
from home and mostly from unregulated commercial of drinking water as stipulated by the WHO is piped
food vender around their places of work. The regres- water on premises. Nketiah-Amponsah et al.’s [18]
sion shows that with an additional year in age of a study’s the socioeconomic determinants of drinking
household member, there is 0.2% points higher likeli- water source in Ghana and found that income in-
hood of cholera infection at 1% significance level. creases access to piped water in residence by 29 per-
However, Deen et al. [16] in a study of three cholera centage points. Asante [19] also found a significant
endemic areas (Jakarta, Kolkata and Biera) found statistical relationship between income and access to
that in all three areas, the impact of the disease was safe or portable water. Based on these, inside plumb-
highest among children under five. There seems to ing and inside standpipe was set as the reference
Table 3 Days missed by patients and caregivers with indirect costs in high and low incidence areas
Days missed (Patient) Days missed (Caregiver) Admission Days Travel Time (Days) Total Missed Days
La-Dadekopon 2071 1451 823 5 14,409
Average 6.90 4.84 2.74 0.02 48.03
Shai-Osudoku 655 388 357 1 6816
Average 4.71 1.41 2.57 0.00 24.79
Total 2726 1839 1180 6 5751
GH¢ GH¢ GH¢ GH¢ GH¢
La-Dadekopon HH Total Indirect Cost 141,656.40 56,293.20 99,248.40 331.03 297,529.03
Shai-Osudoku HH Total Indirect Cost 52,858.50 28,809.90 31,311.60 107.21 113,087.21
La-Dadekopon HH Average Indirect Cost 502.33 199.62 351.94 1.17 1055.07
Shai-Osudoku HH Average Indirect Cost 388.67 211.84 230.23 0.79 831.52
Difference 113.66 −12.22 121.71 0.39 223.54
Source: Survey Data; Author’s computation from Excel
Awalime et al. Health Economics Review  (2017) 7:45 Page 6 of 8
government intervention of free treatment of cholera.
HIA showed four times higher direct cost to house-
holds (GH¢96,444.30; USD 30,138.84) compared to
La-Dadekotopon, LIA (GH¢26,991.30 or USD 8434.78), representing
GH¢2,504,357.12 four folds increased cost when incidence rises from
low to high incidence scenario. Average costs in
La-Dadekotopon, these scenarios saw a 25% increase of costs in HIA
Total, USD$782,611.60 households mostly resulting from increased out-of-
GH¢2,821,801.22
Total, pocket payments due to medical supply shortages in
USD$881,812.88 health facilities within HIA. In both districts, indirect
costs were important and higher than direct costs. It
Shai-Osudoku, was over 50% higher for both districts (51.0% and
USD$99,201.28 61.4% higher in HIA and LIA respectively). In HIA,
Shai-Osudoku, patients spent an additional 7 days in recovery after
GH¢317,444.10 discharge from hospital but reduced to 5 days in the
Fig. 3 Total Cost of 2014’s Cholera Outbreak in High and Low LIA. Total cost saving in averting an episode of chol-
Incidence Area era amounts to GH¢2,504,357.12 (USD 782,611.60) in
HIA but rises 8 folds in a LIA scenario GH¢
base for which other sources were compared. In the 317,444.10 (USD 99,201.28). Factors such as income
sample for this study, close to 70% of the households quintile, marital status, age and some drinking water
get their drinking water from a piped source, that is, sources were significant correlates with the incidence
an inside plumbing or in-house stand pipe (27.5%), of cholera.
tab water in neighbouring house (18.1) or public One limitation of this study is its assumption of un-
stand pipe (42.0%). These together formed 87.6% of employed patients or caregivers having zero indirect
drinking water sources that qualified as portable costs, but since illness and caring for the sick can pre-
sources. The only water source that showed signifi- vent job hunting or accepting offers of work this is a
cance in relation to infection of cholera was water limitation.
from neighbouring house. There was 5.8% higher Also, not all sampled cases could be traced and inter-
cholera incidence in households that had their water viewed so had to be replaced. This formed about 10% of
sources from a neighbouring house as compared to all selected cases.
household having inside plumbing as source of drink-
ing water. Significance for public health
Cholera is a disease of poverty and continues to
Conclusion cause much strain on the resources of the health
Facility costs incurred by households formed the system as well as poor homes. The ease of spread
highest cost drivers (forming over 70% of all direct and resulting costs cannot be downplayed. Cost ana-
costs in both HIA and LIA) regardless of the lysis of cholera provides a key indicator of the
Per capita Cost within two districts
Percapita Total Direct Cost GH¢
Percapita Total Indirect Cost GH¢
Percapita Total Cost GH¢
2,321.00
1,805.34
1,313.24
991.76 1,007.76
813.58
515.66
321.48
194.18
La-Dadekotopon Shai-Osudoku Total
Fig. 4 Per capita cost in High and Low incidence area
Awalime et al. Health Economics Review  (2017) 7:45 Page 7 of 8
Table 4 Tobit regression output showing coefficients, marginal effects for censored sample, standard errors and p-values
Tobit Regression Censored Sample
Proportion of HH Coef. Std. Err. P > t dy/dx Std. Err. P > z
Income Grouping (Above GH¢750)
C1: No Income 0.073** 0.032 0.022 0.019** 0.009 0.036
C2: Less than GH¢100 0.002 0.033 0.960 0.000 0.009 0.960
C3: >GH¢100 < GH¢350 0.059** 0.030 0.050 0.019** 0.009 0.037
C4: >GH¢350 < GH¢750 0.061** 0.030 0.042 0.019** 0.009 0.031
Sex (Male)
Female 0.004 0.012 0.760 0.001 0.003 0.760
Marital Status (Married)
Not married 0.137*** 0.015 0.000 0.035*** 0.004 0.000
Relationship with HH Head (Other Dependents)
Head of HH 0.002 0.018 0.925 0.001 0.006 0.925
Spouse −0.043* 0.022 0.054 −0.015* 0.008 0.059
Son/Daughter 0.146*** 0.016 0.000 0.038*** 0.004 0.000
Age 0.002*** 0.000 0.000 0.001*** 0.000 0.000
Education (Higher)
None 0.008 0.036 0.820 0.002 0.009 0.822
Basic 0.017 0.034 0.619 0.005 0.009 0.610
Sec/Tec/Voc. 0.038 0.035 0.283 0.010 0.009 0.260
NHIS Enrolled (Yes)
No −0.015 0.011 0.167 −0.004 0.003 0.168
Drinking Water Source (Inside Plumbing/Standpipe)
Water vendor 0.015 0.021 0.486 0.004 0.006 0.492
Neighbouring hse pipe 0.058*** 0.016 0.000 0.016*** 0.005 0.000
Public Standpipe 0.019 0.013 0.143 0.005 0.003 0.140
Other sources 0.004 0.027 0.879 0.001 0.007 0.880
Tobit regression Number of obs = 1543
LR chi2(18) = 315.16
Prob > chi2 = 0.0000
Log likelihood = −3801.5065 Pseudo R2 = 0.0398
Significance levels = ***p < 0.01, **p < 0.05, *p < 0.1
financial strain on poor families when dealing with Statistical Social and Economic Research; LIA: Low incidence area;
such menace. WHO: World Health Organization
 GHS must ensure the full and continuous Acknowledgements
implementation of its free cholera treatment. We are much grateful to Noguchi Memorial Institute for Medical
 Need for social intervention policies such as free Research for financial support through the Post-doctoral office that aided
the facilitation this study. We also thank Ghana Health Service (GHS),
feeding or income compensations to mitigate impact. Greater Accra Regional Health Directorate for providing initial household
 Importance of education on symptoms, first aid and data and other useful resources for the study. As well as the La-
need for early treatment by Information Services Dadekotopong and Shai-Osudoku District Hospitals and the Dodowa
Health Research Institute (DHRI) for use of their facility.
Department.
 Disparities of infection rates among different income
groups plus other demographic variables highlights Funding
A grant was won by the lead author from the Noguchi Memorial Institute
issues of discrimination and inequitable distribution for Medical Research, Legon Ghana. This grant was to aid data collection and
of resources. was not conditioned to influence the design, collection of data, analysis,
interpretation and writing of manuscript.
Abbreviations This funding was provided under the Post-Doctoral Office of Sponsored
DHRC: Dodowa Health Research Centre; GHS: Ghana Health Service; Research which gives an annual grant to master students to support and aid
GSS: Ghana Statistical Service; HIA: High incidence area; ISSER: Institute of quality research and mitigate financial constraints.
Awalime et al. Health Economics Review  (2017) 7:45 Page 8 of 8
Availability of data and materials 13. Borroto RJ, Martinez-Piedra R. Geographical patterns of cholera in Mexico,
All datasets on which the conclusions of the manuscript rely are deposited 1991–1996. Int J Epidemiol. 2000;29(4):764–72.
in publicly available repositories and in the additional supporting files 14. Talavera A, Perez EM. Is cholera disease associated with poverty? J Infect
session of the submission. Dev Ctries. 2009;3(06):408–11.
15. Rancourt N. Gender and Vulnerability to Cholera in Sierra Leone: Gender
Sponsorship analysis of the 2012 cholera outbreak and an assessment of Oxfam's
Noguchi Memorial Institute for Medical Research; Post-Doctoral Office. response. 2013.
16. Deen JL, Von Seidlein L, Sur D, Agtini M, Lucas ME, Lopez AL, Kim DR, Ali M,
Publication of results Clemens JD. The high burden of cholera in children: comparison of incidence
The publication of study results was not contingent on the sponsor’s from endemic areas in Asia and Africa. PLoS Negl Trop Dis. 2008;2(2):e173.
approval or censorship of the manuscript. 17. Crooks AT, Hailegiorgis AB. An agent-based modeling approach applied to
the spread of cholera. Environ Model Softw. 2014;62:164–77.
Authors’ contributions 18. Nketiah-Amponsah E, Aidam PW, Senadza B. Socio-economic determinants
Dziedzom Awalime identified the topic to research. Dziedzom Awalime, of sources of drinking water: some insight from Ghana. Conference on
Nkechi Owoo and Edward Nketiah-Amponsah planned the study, executed International Research on Food Security, Natural Resource Management and
the study and analyzed the data. Bright Davies-Teye & Vanotoo critically Rural Development, University of Hamburg; 2009.
reviewed the paper and provided certain sections of the data required. All 19. Asante FA. Economic analysis of decentralisation in rural Ghana. Peter Lang;
authors wrote the paper. Frankfurt am Main. 2003.
Ethics approval and consent to participate
The Institutional Review Boards of the Institute of Statistical Social and Economic
Research (ISSER); clearance number - ECH 033/14-15) and the Dodowa Health
Research Centre (DHRC) clearance number - DHRC/IRB/15//03) reviewed and
approved the study.
Consent for publication
The authors of this paper give consent for publication to the Health
Economics Review.
Competing interests
All data collected for use in the study was proprietary work from authors. All
models and methodology adopted from other sources are duly recognized
and cited. The authors declare that they have no competing interests.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Received: 14 March 2017 Accepted: 15 November 2017
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