SCHOOL OF PUBLIC HEALTH  

COLLEGE OF HEALTH SCIENCES 

UNIVERSITY OF GHANA 

 
 

MALARIA IN CHILDREN UNDER FIVE YEARS AND 

ASSOCIATED FACTORS IN ARTISANAL MINING AND NON-

MINING DISTRICTS IN THE UPPER EAST REGION, GHANA 

 

 

 

 

BY  

 

FRANCIS BRONI 

(10552275) 

 

 

 

THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, 

LEGON IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR 

THE AWARD OF MASTER OF PHILOSOPHY IN APPLIED 

EPIDEMIOLOGY AND DISEASE CONTROL DEGREE 

 

 

 

 
 

 

 

 

  

JULY, 2017



i 
 

DECLARATION 

I hereby declare that except for the references cited to other people’s work which has 

been duly acknowledged, this work is the result of my own research work done under 

supervision and has neither in part or whole been presented elsewhere for another degree 

 

 

 

…………………………………….                                  ……………………………. 

FRANCIS BRONI     DATE 

(10552275)  

 

 

 

…………………………………….                                  …………………………. 

 

DR. FREDERICK WURAPA                                      DATE 

(ACADEMIC SUPERVISOR) 

 

 

 

 

…………………………………….                                 …………………………. 

DR. REGINALD QUANSAH  DATE 

(CO-SUPERVISOR) 

 

 



ii 
 

DEDICATION 

I dedicate this work to Almighty God, my dear wife Margaret and my two lovely young 

stars Francis (Jnr) and Franpearl. 



iii 
 

ACKNOWLEDGEMENT 

I wish to express my sincere gratitude to my academic supervisor, Dr. Frederick Wurapa 

of the School of Public Health, University of Ghana, Legon,  

My sincere thanks to Prof. E Afari, Dr. S.O Sackey, Dr. Ernest Kenu, Dr. Donne Ameme 

and Dr. Kofi Mensah Nyarko all of the School of Public Health for their support. I also 

thank all lecturers of the School of Public Health for their guidance, support and also 

imparting knowledge to me. My heartfelt gratitude goes to Dr, Koku Awoonor Williams 

of Ministry of Health for releasing me for this programme, God richly bless you. My 

sincere appreciation to Mr. Martin Adjuik of University of Allied Health Science for 

taking time to review my questionnaire and data analysis. I thank Mr. Godfred Agongo of 

Navrongo Health Research Centre for his immense support and contribution during the 

development of the proposal and entire work. My warmest appreciation to all the Medical 

Superintendents of Bongo and Tongo district hospitals for their immense support. My 

appreciation also goes to Regional Director of Health Services and Deputy Director 

Clinical Cares, Upper East Region for granting me the permission to do the research. I 

wish to thank all the staff of Ghana Field Epidemiology and Laboratory training 

Programme (GFELTP) for their assistance. I wish to thank my wife for her dedication in 

the field. I thank the President Malaria Initiative (PMI) for their financial support. Finally, 

I sincerely thank all who in diverse ways helped me throughout the programme.  

University of Ghana http://ugspace.ug.edu.gh 



iv 
 

ABSTRACT 

Background: Malaria remains a leading public health problem in about 97 nations 

worldwide. Throughout the world, about 214 million new malaria cases are reported 

every year and over three billion persons are at risk of malaria. Approximately 90% of all 

malaria deaths occur in Africa. Africa continues to shoulder heaviest burden of malaria 

cases. Global demands for natural resources is fueling land use, saddled with 

unsatisfactory environmental burden in developing countries. We conducted a cross 

sectional study to determine proportion of malaria in children under five years in artisanal 

mining and non-mining areas and factors associated with malaria in the districts in the 

Upper East Region, Ghana. 

Methods: A cross-sectional study was conducted to compare proportion of malaria in 

children under five and associated factors in artisanal mining and non-mining districts. 

Data was abstracted from the facility records for children under five. A face to face 

interview was conducted for caregivers with children under five in the hospital. 

Categorical variables of the characteristics of the study participants were analysed into 

frequencies and proportions and presented in tables. The continuous variables such as age 

were analysed into means and standard deviations. 

Two samples proportion test was used to compare whether difference exist between the 

districts at 95% significant level. Chi square test and Odds ratio were used to examine an 

association between exposure variables and malaria. Malaria was the dependent variable 

and demography were independents variables. Univariate analysis was done to determine 

an association between exposure variables (age, sex, occupation, marital status, income 

level, educational status, and households’ number) and malaria. Logistic regression model 

was fitted to correctly predict factors that strongly associated with malaria infection in the 

districts Ethical clearance was obtained from Ethical Review Committee of Ghana Health 



v 
 

Service. Written permission was sought from Regional Health Director of Ghana Health 

Service, Upper East Region.  

Results: Data on 11380 children under five years was extracted from hospital records   

and 525 caregivers were interviewed. The proportion of malaria was 39.2 % (95%. CI: 

38.01%- 40.40%. p< 0.001) in children in the mining district as against 43.8% (95%, CI: 

42.41% – 45.19%. p< 0.001) in the non-mining. Proportion of severe malaria was 27.1% 

(95%, CI: 25.7% - 28.3%) in the mining district compared with 57.47% (95%, CI: 56.0% 

- 58.8%) in the non-mining district. The child age, district the child resides, educational 

status of caregiver, occupation of caregiver and bed net (ITN) possession significantly 

associated with malaria in children under five years in study areas. 

Conclusion: The findings suggested a relatively low proportion of malaria morbidity and 

severe malaria in children under five in the artisanal mining as against the non-mining 

district. Age of child, socioeconomic factors of caregiver and education status were 

associated with malaria in children in the study areas.  Efforts of controlling malaria in 

these districts have been intensified but could be enhanced with high coverage of ITN 

possession, health education and vector control activities at wetland and dam sites.  

 

 

 

 



vi 
 

TABLE OF CONTENTS 

DECLARATION .................................................................................................................. i 

DEDICATION ..................................................................................................................... ii 

ACKNOWLEDGEMENT ................................................................................................. iii 

ABSTRACT ........................................................................................................................ iv 

TABLE OF CONTENTS .................................................................................................... vi 

LIST OF TABLES .............................................................................................................. ix 

LIST OF FIGURES ............................................................................................................. x 

LIST OF ABBREVIATIONS ............................................................................................. xi 

 

CHAPTER ONE .................................................................................................................. 1 

INTRODUCTION ............................................................................................................... 1 

1.0 Background ................................................................................................................ 1 

1.1 Problem Statement ..................................................................................................... 3 

1.2 Justification ................................................................................................................ 4 

1.3 Hypotheses ................................................................................................................. 5 

1.4 Objectives ................................................................................................................... 5 

1.5 Conceptual Framework .............................................................................................. 6 

1.5.1 Determinants of infection .................................................................................... 6 

1.5.1.1 Individual level: biological and disease-related factors ................................... 7 

1.5.2 Household and community levels: social and economic factors ......................... 9 

1.5.3 Environmental level ........................................................................................... 12 

 

CHAPTER TWO ............................................................................................................... 13 

LITERATURE REVIEW .................................................................................................. 13 

2.0 General Overview of Mining ................................................................................... 13 

2.1 Gold Mining Process ................................................................................................ 15 

2.1.1 Placer mining ..................................................................................................... 15 

2.1.2 Hydraulic mining ............................................................................................... 15 

2.1.3 Lode Mining ...................................................................................................... 16 

2.2 Mining in Ghana....................................................................................................... 16 

2.2.1 Artisanal mining methods in Ghana .................................................................. 17 

2.3 Impact of mining on Environment ........................................................................... 18 

2.4 Impact of Mining on Human Health ........................................................................ 21 

2.5 Malaria Epidemiology .............................................................................................. 24 

2.5.1 Life cycle mosquito species ............................................................................... 26 

2.6 Global Malaria Burden ............................................................................................. 30 

2.6.1 Malaria burden in Ghana ................................................................................... 32 

2.7 Mining and Malaria .................................................................................................. 35 

2.8 Severe Malaria and Inpatients .................................................................................. 37 

2.9 Malaria Prevention ................................................................................................... 38 

2.9.1 Historical and Global Perspective ..................................................................... 38 

2.9.2 History of Malaria Control in Ghana ................................................................. 40 



vii 
 

2.9.3 Malaria Prevention Methods ............................................................................. 41 

2.9.3.1 Insecticides Treated Net ................................................................................. 41 

2.10 Factors Associated with malaria infection in children ........................................... 42 

2.10.1 Anemia in Children ......................................................................................... 46 

2.10.2 Parents/Caregivers Knowledge of Malaria ...................................................... 48 

 

CHAPTER THREE ........................................................................................................... 51 

METHODS ........................................................................................................................ 51 

3.1 Study Design ............................................................................................................ 51 

3.2 Study area ................................................................................................................. 51 

3.3 Facilities Selection and Setting ................................................................................ 55 

3.4 Study Population ...................................................................................................... 56 

3.5 Inclusion and Exclusion Criteria .............................................................................. 56 

3.6 Sample Size Determination ...................................................................................... 57 

3.7 Sampling Methods.................................................................................................... 57 

3.7.1 Data Collection Method and Tools .................................................................... 57 

3.7.2 Training of field workers ................................................................................... 58 

3.7.3 Management and Data Analysis ........................................................................ 58 

3.8 Ethical Considerations.............................................................................................. 59 

3.8.1 Participation ....................................................................................................... 59 

3.8.2 Risk and Benefits ............................................................................................... 59 

3.8.3 Confidentiality ................................................................................................... 60 

3.8.4 Consenting process ............................................................................................ 60 

3.9 Limitation of study ................................................................................................... 61 

 

CHAPTER FOUR .............................................................................................................. 62 

RESULTS .......................................................................................................................... 62 

4.1 General Overview .................................................................................................... 62 

4.2 Socio demographic Characteristics of the study participants (children under five 

years = 11380) ................................................................................................................ 62 

4.3 Clinical characteristics of the children under five years, Upper East Region .......... 66 

4.3.1 Age distribution of malaria infected children under five years, Tongo and 

Bongo District, Upper East Region ............................................................................ 67 

4.4 Demographic, socio economic and environmental factors affecting malaria in 

children under five years in Tongo and Bongo District, Upper East Region................. 68 

4.5 Multiple analysis of factors associate with malaria infection in children under five 

years in Tongo and Bongo district, Upper East Region ................................................. 70 

4.6 Caregivers knowledge of malaria, treatment and prevention in Tongo and Bongo 

District, Upper East Region. .......................................................................................... 72 

4.6.1 Caregivers Knowledge on malaria treatment drugs in Tongo and Bongo, Upper 

East Region. ................................................................................................................ 73 

4.6.2 Knowledge of caregivers on malaria prevention methods in Tongo and Bongo 

District, Upper East Region ........................................................................................ 73 

 



viii 
 

CHAPTER FIVE ............................................................................................................... 75 

DISCUSSION .................................................................................................................... 75 

5.1 Caregivers’ knowledge, treatment and prevention of malaria in children under five 

years Tongo and Bongo District, Upper East Region. ................................................... 82 

5.2 Characteristic of Study Participants in Tongo and Bongo District, Upper East 

Region ............................................................................................................................ 83 

 

CHAPTER SIX .................................................................................................................. 85 

CONCLUSIONS AND RECOMMENDATIONS ............................................................ 85 

6.1 Conclusions .............................................................................................................. 85 

6.2 Recommendations .................................................................................................... 85 

 

REFERENCES .................................................................................................................. 87 

 

APPENDICES ................................................................................................................. 105 

 



ix 
 

LIST OF TABLES 

Table 1: Age and sex distribution of children under five years, Tongo and Bongo District, 

Upper East Region, 2016 .................................................................................... 63 

Table 2: Socio demographic characteristics of caregivers of children under five years in 

districts Health Facilities, Upper East Region, 2016 (n = 525) .......................... 65 

Table 3: Clinical Characteristics of children under five years in Tongo and Bongo   

District, Upper East Region, 2016 ...................................................................... 67 

Table 4: Univariate analysis of selected variables for Malaria infection, Children under 

five in Tongo and Bongo district, Upper East Region, 2016 .............................. 69 

Table 5: Multiple Logistic Regression Analysis of factors associated with Malaria in 

Children under five years in Tongo and Bongo District, Upper East Region, 

2016..................................................................................................................... 71 

Table 6: Knowledge of Caregivers on malaria infection in Tong and Bongo District, 

Upper East Region, 2016 .................................................................................... 72 

Table 7: Proportion of caregivers identified drug for malaria treatment, Upper East 

Region, 2016 ....................................................................................................... 73 

Table 8: Caregivers response in relation to malaria prevention method artisanal mining 

district and non-mining district, Upper East Region, 2016 ................................ 74 



x 
 

LIST OF FIGURES 

Figure 1: Conceptual Framework including factors influencing malaria transmission ....... 6 

Figure 2: Photograph showing women and children in artisanal mining processing ........ 14 

Figure 3: Distribution of ASM Activities around the World ............................................. 14 

Figure 4: wooden sluice box use by illegal gold miners .................................................... 18 

Figure 5: Impact of ASM on agriculture land .................................................................... 20 

Figure 6: Effect of ASM on water body in Amansie West District ................................... 21 

Figure 7: Life cycle of plasmodium species ...................................................................... 26 

Figure 8: Life cycle of mosquitoes .................................................................................... 28 

Figure 9: Global distribution of malaria, 2014 .................................................................. 31 

Figure 10: Ecological Zones of Ghana .............................................................................. 33 

Figure 11: Distribution malaria prevalence in 6-59 months old children, Ghana ............. 34 

Figure 12: Roles of global malaria control programme ..................................................... 40 

Figure 13: Concentration of anemia per region in children under five years .................... 47 

Figure 14: Map showing study sites in the Upper East Region with the red rectangle 

pointing to the two study districts in the regional map. ................................... 54 

Figure 15: Children under five malaria infection in different age group (95% CI), in 

Tongo and Bongo districts, Upper East Region, 2016..................................... 68 

 

  



xi 
 

LIST OF ABBREVIATIONS 

ANC  Antenatal Care    

ASM  Artisanal and Small Scale Mining    

CDC  Centres for Disease Control and Prevention    

CHPS  Community-based Health Planning and Services    

CWP  Workers Pneumoconiosis    

DDT  Dichloro-Diphenyl-Trichloroethane    

DFID  Department for International Development    

G6PD  Glucose 6 Phosphate Dehydrogenate  

GDP  Gross Domestic Product    

GFATM Global Fund to fight AIDs Tuberculosis and Malaria  

GHS  Ghana Health Service    

GSS  Ghana Statistical Service    

ICMM  International Council on Mining and Metals    

IPT  Intermittent Preventive Treatment    

IPTp  Intermittent Preventive Treatment during pregnancy    

IRS  Indoor Residue Spray    

ITNs  Insecticide Treated Nets    

LLINs  Long Lasting Insecticide Nets    

NMCP  National Malaria Control Programme    

OPD  Out Patient Department    

PAHO  Pan Africa Health Organization    

PMI  President's Malaria Initiative    

PNG  Paupa New Guinea    

RBM  Roll Back Malaria    

RDT  Rapid Diagnose Testing Kit    

TB  Tuberculosis    

USAID United State Agency for International Development    

W.H.O  World Health Organization 



1 
 

CHAPTER ONE 

INTRODUCTION 

1.0 Background 

Malaria is a leading public health concern in over 97 nations and regions in tropical 

regions worldwide. Throughout the world, about 214 million new malaria cases are 

reported every year and over three billion persons are at risk of malaria (Dawaki et al., 

2016; WHO, 2015). Almost 440,000 people died from malaria in 2015, most of the death 

were in Africa, where a projected 90% of all malaria deaths happened (WHO, 2015). In 

2007, the Millennium Development Goals six to reduce malaria burden 75% by 2015 was 

set by World Health Assembly (WHO, 2015). Since the tracking of malaria was initiated 

by WHO, the European regions recorded zero indigenous malaria cases for the first time. 

The developed countries such as America had also made an important improvement in 

reducing malaria. However,  Africa continues to lead in the burden of malaria cases 

(WHO, 2015), which is attributable to weak health systems and poor environmental 

management (Utzinger, Tozan, & Singer, 2001).  

Global demands for natural resources is gradually driving local resource extraction and 

land use.  As the world economy is strongly linked together, the demands for these 

natural resources are increasing the social and environmental problems in the developing 

nations compared to developed nations. As a result, evolving nations are burdened with 

unacceptable environmental problems relative to developed states or nations that are 

importing the unprocessed resources (Swenson, Carter, Domec, & Delgado, 2011). 

Although mining has shown to bring about significant improvement in the life of people, 

their settlement and the economy of mineral endowed nations, it also has resulted in the 



2 
 

upsurge of malaria spread in mining communities (Castellanos et al., 2016; Knoblauch et 

al., 2014). 

The technologies that are usually employed inevitably have a undesirable effect on the 

environment, hence, influencing the upsurge of malaria occurrence in places like northern 

Mato Grosso, Brazil (Sawyer, 2007; Barbieri, Sawyer, & Soares-Filho, 2005).  

In early 1990s, northern Mato Grosso recorded the greatest burden of malaria in Brazil, 

and this was greater than what was usually reported by known endemic places. In 1993, 

malaria survey was conducted in the mining communities in North Mato Grosso, average 

burden of malaria was 33.1% in the mining communities. Additionally, the Amazon sub-

region covered with the tropical forest of South America bordered with countries such as 

Bolivia, Brazil, Colombia, Ecuador, and others. The sub-region extends approximately 

7,200,000 square kilometers with about 30 million population (Stefani et al., 2013). This 

sub-region accounted for  about 89% of malaria diseases in all Americans which was 

recorded by the Pan American Health Organization, 2008 (Stefani et al., 2013) due to 

land use including small-scale mining, deforestation, water and wetland and among 

others. 

Asian and Africa regions of which Ghana, South Africa, and Papua New Guinea are 

included, had reported the considerable proportion of malaria diseases from gold mining 

communities. A survey carried out in Papua New Guinea (PNG) in 2006 in mining 

communities among 2,264 children indicated that prevalence of malaria was 33.6% 

(Mitjà et al., 2013). 

A household survey conducted between 2006 and 2007 in the Brong Ahafo Region, a 

forest and mining area of Ghana found the prevalence of malaria among children under 

five to be 22.8% (Asante et al., 2011).  When these results were compared to records from 



3 
 

other remotes areas in Ghana, the forest-savanna transition places of Kintampo reported 

58% prevalence of malaria in 2004 whereas, 55.5 to 69.3%  of the cases were reported in 

the savanna zone of northern Ghana from 2000 to 2002 (Asante et al., 2011; Malaria & 

Programme, 2013; Schueler & Kuemmerle, 2011).  

 
1.1 Problem Statement 

Malaria remains a public health concern in most countries. The parasites and the vectors 

are found in areas, almost half of the world population reside. Globally, malaria affects 

more than 300 million individuals per year (Ferreira et al, 2012). It severely affects the 

Africa regions. In Ghana, over 10 million individuals were affected in 2015 (National 

Malaria Control, 2015; Ferreira et al., 2012). Despite several interventions to stop malaria 

in the country as in other endemic nations, success has been very small. It accounts for 

over 45% of outpatient department visits and at least 20% child deaths (Tay, Badu, 

Mensah, & Gbedema, 2015). In 2015, nine out of the 10 regions in Ghana reported 

increase in OPD malaria cases with Central Region recording 44% increase compared to 

the 2014 (National Malaria Control Programme, 2015). 

In mining countries such as Brazil, mining activities have added to increasing number 

malaria cases of malaria. For instance, 99% cases of malaria are clustered in the Amazon 

(de Oliveira, 2011) due to unregulated mining activity that has led to intense land use and 

dramatic environmental change. Ghana is endowed with mineral deposits. These deposits 

have attracted both large international mining companies and small-scale artisanal miners. 

The artisanal mining activities that predominate across the country favor the creation of 

an environment conducive for malaria vector reproduction. Most of the activities result in 

creating holes which when left uncovered collect water, couples with a small area with 

high population density (Dery et al., 2015) which favors the production of mosquitoe. 



4 
 

However, most research activities have focused on economic perspective with very few 

studies examining diseases prevalence at district levels in the country. National Malaria 

Control Programme (NMCP) in its 2013 final report recommended that malaria 

prevalence by the districts should be carried out. This would provide vital information 

such as stratification data in the country for decision making. The essence is that the 

National Malaria Strategic Plan 2020 to reduced malaria burden by 75% may be defeated 

since little or no information regarding data on stratified malaria prevalence and 

associated factors at the districts level is available. This study would focus on children 

under five years in artisanal mining and non-mining districts because they are mostly at 

risk of malaria morbidity. According to NMCP, (2013) the prevalence of malaria in 

children under five years in the Upper East Region was 44%. This figure is relatively 

high, hence district level data would be appropriate in supporting decision making. 

 

1.2 Justification 

Almost every Ghanaian is vulnerable to malaria and a sizeable proportion of Ghanaians 

spend huge sums of income on malaria prevention products such as coils, sprays, and 

insecticide treated nets, mosquito repellent among others. Nearly, all families pay for 

malaria treatment in Ghana. The cost of treatment for malaria is equal to the benefits to be 

derived by the country if malaria is successfully controlled. This study will stratify the 

proportionate malaria and associated factors at the district level in the artisanal mining 

and non-mining districts in the Upper East Region.  Continuous evaluation or provision of 

baseline data, would enable the region to successfully plan, implement and appraise 

malaria control programmes. If malaria control initiatives are to be successful in Upper 

East Region, there is the need for empirical data on malaria morbidity and the factors 

influencing the disease in children under five years, therefore this study is timely. More 



5 
 

importantly, very little information is available on this subject in the Upper East Region. 

On basis of testable fact, it has become important to providing people in authority and 

other stakeholders with important information on the factors influencing the burden of 

malaria in the Upper East Region for policy formulation and interventions. In addition, 

the study aims at contributing to knowledge, the proportion of malaria morbidity by 

stratifying data to mining and non-mining areas. 

 

1.3 Hypotheses 

The null hypothesis tested in this study was: 

1. Proportion of malaria in children under five years in the artisanal mining (Tongo) 

district is the same in the non-mining (Bongo) district. 

 

1.4 Objectives 

General objective: To determine the proportion of malaria in children under-five years in 

artisanal mining and non-mining districts in the Upper East Region. 

Specific objectives 

1. To determine the proportionate malaria morbidity in children under-five years in 

artisanal mining and non-mining areas in the Upper East region 

2. To determine the proportion of under-five severe malaria in the mining and non-

mining areas in the Upper East region. 

3. To assess factors associated with malaria infection in children under five years in 

the districts in the Upper East region 



6 
 

1.5 Conceptual Framework 

 

Independent variables Dependent variable 

Individual level 

 

 

 

 
 

Household level 

 

 

 

 

 

Environmental level 

 
 
 
 
 
 
 
 
 
Figure 1: Conceptual Framework including factors influencing malaria transmission 

 

 
1.5.1 Determinants of infection 

There is evidence that many interrelated factors influence a person susceptibility to 

diseases of malaria. The factors include individual, households and environmental level 

risk factors (Bate et al., 2004). 

 

 Climatic 

condition 

 sanitation 

 water 

bodies 

 Land use 

 Poverty 

 Education 

 Occupatio

n 

 Life style  

 Domestic 

activities 

 

 Age 

 Gender 

 Nutrition

al status 

 Genetic 

 Immunity 

 

 Malaria 



7 
 

1.5.1.1 Individual level: biological and disease-related factors 

Human beings are disposed to disease as results of factors such as biological, hereditary, 

immunological, and pathophysiological mechanisms. Humans have different levels of 

susceptibility to malaria infection, severity of the illness and responses to treatment. 

An individual immune status is essential in responding to malaria infection. Immunity to 

clinical malaria is acquired by constant exposure to malaria infection. In places where the 

spread of malaria is constant, children and babies died frequently because of poor system 

defense. Places with low spread of malaria, everybody risk infection of malaria (Snow & 

Marsh, 2002). In high transmission areas of malaria, adults are increasingly infected with 

malaria but are usually not complicated. The association of human immune system with 

disease and vice versa has consequences on health policies. In areas with surge in malaria 

transmission, adults are the main reservoirs because of asymptomatic infections. As such, 

interventions that target only people presenting with signs and symptoms may reduce 

deaths resulting from the disease but may not impact on the  spread of malaria, specially, 

if done in isolation from other control interventions (DFID, 2010). Symptoms of malaria 

is easily presented in malaria immune naïve patients and therefore treatment of such cases 

mighty impact significantly on malaria transmission. 

A group of people with some genetic mutation, have protection to malaria. These group 

are made up of people with abnormal haemoglobin (alpha and beta thalasaemia, sickle 

cell) enzyme deficiency (G6PD), and persons of Duffy-negative phenotype blood group. 

(Weekley & Smith, 2013; Jr & Bordin, 2006). Duffy negative blood group persons were 

found to be protected from P. vivax. However, a new research conducted in Madagascar 

found that P. vivax could cause malaria disease in Duffy-antigen blood group individuals 

(Chuks J. Mba and Irene K. Aboh, 2006; DFID, 2010). 



8 
 

In stable malaria transmission areas, coupled with normal or overweight, malaria 

infection in babies and children changes with changed in age. Younger children suffer 

anaemia and as the children grow older, they are prone to cerebral and severe malaria 

(DFID, 2010) and the pattern may vary from place to place. In both stable and unstable 

malaria transmission area, age effect of anaemia is observed. However, complicated 

malaria is highly pronounced particularly in adults. Adults are of greater odds of renal 

disease and serious lung disease compared to children. The observed variances are 

important public health consequences. Working to curtail the spread of malaria and its 

effect would move the effect of the illness to older and children above five years 

population. If these population get infected with malaria they would become symptomatic 

and pursue for remedy.  

The risk of malaria infection is low in the initial stage of life. This could be due to the 

movement of maternal antibodies across the placenta, Haemoglobin-f, breast-feeding and 

non-exposure to malaria parasites. (Weekley & Smith, 2013).The defensive effect of 

mother’s antibodies would be lowered, if effective malaria control is realized and there is 

drastic reduction in malaria infection.  

In low malaria areas, malaria disease is observed in all age groups, as such work-related 

problems might become very significant to consider than age. Indeed, this is true when 

people are infected through the bites of the vectors away from their homes. (P. M. De 

Silva & Marshall, 2012). 

There is lack of enough evidence concerning biological difference of gender and malaria 

acquisition or infection. The information on gender difference with respect to malaria 

addresses in pregnancy, occupational risks, and care-seeking behaviors. Occupational and 



9 
 

cultural dynamics affect malaria transmission. Access to health service differ 

considerable from one place to another and across culture and geographical states.   

The few reports on gender differences with respect to malaria risk is largely centered in 

females. But, there are evidences that also suggested that men are more at risk for malaria 

in some countries because of male dominate life styles. For instance, places where 

agricultural is male dominated activity and farming activities are extended into the night 

or even people choose to sleeping in the farms for other reasons could make then more 

vulnerable for malaria disease (Chuks J. Mba and Irene K. Aboh, 2006; DFID, 2010; P. 

M. De Silva & Marshall, 2012).
 

It is a fact that malnutrition compromises the human immunity and therefore increases 

chance of new malaria diseases. Malnutrition predisposes children to severe malaria and 

malaria mortality. Chronic malnourished children have 50% more the chances of malaria 

mortality compared to counterparts who are normal. (Bhan, Bhandari, & Bahl, 2003; 

DFID, 2010; Kandala et al., 2011). Acute malnourished children are about 50% to 75% at 

risk of death from malaria infection. The deficiency in Vitamin A supplementary and zinc 

in the body, play significant role in malaria morbidity and mortality. This is because of 

importance of these molecules in building the immune system. Children with zinc 

deficiency have high risk of illness of malaria and death from malaria compared to those 

with accurate zinc status. However, this evidence need more proofs (Bhan et al., 2003). 

1.5.2 Household and community levels: social and economic factors 

Family and community levels factors have shown a connection between cases of malaria 

and lack of money. But it may also be strongly contested because of the strength and 

direction of the association. Many people would accept that relationships exist between 

malaria and poverty but which influences which one may need more information to 



10 
 

conclude. Treatment seeking behavior may be influenced by wealth level. People with 

inadequate incomes benefits just little from malaria control and prevention interventions 

compared to rich people. People who cannot afford to pay medical bills only seek health 

care at very critical time. Malaria disease comes heavy burden on families with financial 

inadequacy (Baral et al., 2004; Onwujekwe et al., 2009) and as such huge malaria 

treatment cost would indeed leads to later reporting to the hospital. The malaria 

prevalence is highly pronounced in poorer households, which in turn imposing substantial 

cost on people and their families, ensuring that the circle of malaria disease and poverty 

continues. Poorer families are mostly affected by malaria and could lead to this families 

selling their properties and food stuffs so as to cater for treatment fees. However, families 

that are rich could cope with spending more on malaria prevention and treatment. 

Indeed, prompt health care seeking behavior ensures good outcomes. However, due to 

financial inadequacies poor families bear the consequences of malaria such as death, as 

the ultimate. Poor families would self-treat than to access private or public health 

providers. Households with lower income are mostly susceptible to malaria during the 

raining period. During this period the malaria prevalence is highest but cash flows is 

lower. (DFID, 2010). 

Education may influence malaria transmission in either direction. Educated person with 

vest knowledge in malaria would seek protection against malaria for family members and 

himself/herself. Also, education would provide him job that in turn earned income with 

which can provide good home which would be well screened against mosquitoes, and 

thereby highly protected against malaria. Also educated person have the propensity to 

easily understand the various preventions, control methods and thereby utilizing them to 

his benefit. However, non-educated person, would need long time to understand the 



11 
 

consequences of malaria and to accept the various preventive and control methods. Also, 

behavior may be influenced as result of no education and therefore indulging in life style 

that exposes to mosquitoes. Lack of education may impact on income and though 

preventive and control methods might be available, affordability becomes major issue. 

Occupations such as farming, fishing, animal rearing, mining, stone quarrying, and petty 

trading, have effect on the spread of malaria illness due to contact with infected mosquito 

vectors bits. Type of employment of people could also determine the environment and 

exposure to mosquito bites. If you work late to the night outdoor in mosquito infested 

environment, the episodes of malaria cases compared to someone whose work is limited 

to day would be different. Furthermore, work remuneration depends on factors like level 

of education, job demands, and risk involved. If one works outdoors until late night but 

not considered essential worker, though exposure to mosquitoes is high, one’s 

remuneration is low and thereby affordability for preventive measure may be 

compromised. 

In addition, life style and domestic activities could affect malaria. People who stay 

outside or rest late night without protection end up with episodes of malaria. People who 

are outdoor types or stay outside for purpose of work could end up expose to the 

exophilic Plasmodium sp. People who are involved in house chores that keep them 

outside longer into the night are exposed to malaria. For instance, women who cook 

outside late at night are exposed to malaria vector and have increased risk compare to 

those doing same in closed screened kitchen. 

 



12 
 

1.5.3 Environmental level 

Environmental factors largely affect the spread of malaria. It primarily influences the 

proliferation and existence of the malaria vector, exposure of persons and other animals. 

The environmental factors that favors the transmission of malaria parasites are the factors 

that increased proliferation of Anopheles mosquito. These conditions may include water 

which the mosquito lives and breed, temperatures and humidity which enable the vector 

to live long so that the vector phase of the life cycle of the parasite can be completed. 

These factors are also affected by climate change, landscape, soil types, soil drainage, 

vegetation types, land use and water. These are factors differ greatly from place to place 

because of differences in the weather with respect to different geographical areas and land 

use. Land use in this case includes water usage, farming, mining, urbanization, and 

cutting down of trees can significantly influence the spread of malaria. 

 



13 
 

CHAPTER TWO 

LITERATURE REVIEW 

2.0 General Overview of Mining 

The mining and metals production companies spans a complex interdependent web which 

includes a formal and non-formal component. The formal companies are categorized to 

public-trade and state owned. They engaged over two million people globally and about 

half the people are engaged by very big companies (ICMM, 2012). The formal mining 

industry works within the legal and fiscal context linked together by other nationals, 

regionals and commodity-focused associations devoted to representing the industry, 

protecting its interests and improving work performance (ICMM, 2012). In contrast, 

small scale mining and artisanal mining formed the informal component. There is 

however, no legal frameworks governing the sector, though it is changing from countries 

to countries (ICMM, 2012; World Bank Group, 2014; World Bank, 2008). 

For many people, the term “mining” is related to large-scale processes with sophisticated 

equipment and technology. However, artisanal or  small-scale mining activities (ASM), 

which use methods that have changed little since ancient times, continues to offer 

employment to people  directly or indirectly for not less than 20 to 30 million and over 

100 million people depend on it for livelihood (Hentschel Thomas,; Hruschka Felix, 

2003; World Bank, 2008). The World Bank report and Hinton (2005), indicates that about 

55 countries of which majority are in poorest countries are engaged in ASM. About 10 – 

50 percent of women and between 1-1.5 million children of age less than18 are involved 

in ASM (World Bank Group, 2014). 



14 
 

 

Figure 2: Photograph showing women and children in artisanal mining processing 

Curtesy: World Bank Group, 2014 

 

With the prices for commodities on the world market go high couples with population 

growth, the demands for mineral resources cum escalating poverty in many nations is 

increasing number of miners at faster rate (Hinton, 2005).  

 

Figure 3: Distribution of ASM Activities around the World 

Source: www.casmsite.org 



15 
 

Trends in artisanal and small-scale mining employment and decline were observed, with 

increase in ASM employment through Africa and Asia and declines in Latin America. 

The ASM activities across the regions of the world is shown in Figure 3. 

There is no doubt that ASM has a legitimate and significant role to play in the social and 

economic development of many countries , particularly in Africa (Collins & Lawson, 

2014). The report of Collins and Lawson, further explained the fact that artisanal and 

small-scale mining (ASM) comes with some benefits, it has also contributed several 

social menaces, and also has negatively affected the environmental and health of the 

population through the activities of artisanal and small mining. 

 

2.1 Gold Mining Process 

2.1.1 Placer mining 

Placer mining was method that was used first to mine gold from river banks, streams and 

lakes surrounding the Sierra Nevada Mountains. The technique involves the weight of the 

gold and gravitational force to separate the gold ores from other alluvial deposits (M. 

Silva, 1986). In the United States of America, most gold mined were from placer deposits 

(Butterman, 2005). Though, placer mining can employ simple tools such as gold pans, 

very sophisticated methods have been developed.  

2.1.2 Hydraulic mining 

After the initial amount of gold found started depleting, prospectors started to look far for 

golds that were deposited within bedrocks of mountains and gravel. To reach this mineral, 

the sand beds and rocks must be extracted first. Therefore, miners employed high-

powered streams of water to flash out these rocks to reach the gold inside them 

(Butterman 2005). Though hydraulic mining seems a simple process, it needs various 

tools and skills to reach the right form of the gold ore. Very large amount of water is 



16 
 

usually needed to generate hydraulic power. As such very big projects were embarked on 

to provide miners with large quantity of that water that were needed to perform 

hydrological mining (Hill 1999).  

2.1.3 Lode Mining 

When it was later known that gold that were in water bodies were not initially there, 

miners started looking beyond for the main source of the deposits. Lode gold deposits 

were as a results of hydrothermal activity below the Earth’s surface (Hill, 2006). These 

types of deposits required deeper mining and digging than hydraulic and placer mines. 

The deposited golds are concealed in mountains in a several quartz veins. Lobe gold 

extraction is difficult because of the quartz vein and thus making the process of lode gold 

extraction difficult. Most of the time, lodes mining required explosion and very deep 

drilling underground in order to reach the lodes (Butterman, 2005).  Shallow lode 

deposits can be reached to by surface mining. This type of mining method is referred to as 

open-pit technique which involves the abstraction of the upper layer of bedrock on top of 

the deposit. 

 

2.2 Mining in Ghana 

Ghana is found in West African situated on the Gulf of Guinea, it is blessed with many 

natural resources including gold, diamond bauxite and others. The country has land area 

of 238,555 square kilometers. Ghana’s population is about 26 million, and bordered to 

Togo, Cote D’Ivoire and Burkina Faso. Ghana was colonized by British, at the time the 

region was named Gold Coast because of the gold reserves (Yelpaala & Ali, 2005) 

 



17 
 

2.2.1 Artisanal mining methods in Ghana 

History has it that artisanal mining has been operating in Ghana as illegal (galamsey) 

venture and legalized entity. However, it was limited to Birimian and Tarkwaian and the 

alluvial areas on the boundary through Offin, Pra, Ankobra and Tano rivers and their 

tributaries. ASM gained worldwide recognitions because it has significantly affected the 

livelihoods of mineral endowed economies positively. However, it has come with many 

work-related health hazards which is not limited to those directly engaged in the mining 

activities, but to the communities they carry out the activities and the surrounding 

communities. It is projected that Ghana has employed almost one million  persons in 

ASM (Hilson, G & Garforth, 2013) . The types of small and artisanal miners that operate 

in Ghana including licensed and supervised and those mining and processing  without 

required license and usually on concessions of companies  (Nyame, FK & Grant, 2014). 

In Ghana there is no clear distinction between artisanal and small scale mining in law 

(Aubynn, 2009).  However illegal small-scale gold miners are referred to as galamsey in 

our local parlance, which means “gather them and sell” (Collins & Lawson, 2014; Hilson, 

G & Garforth, 2013). Though, many people could not distinguish between legal and 

illegal small-scale mining when the term galamsey is used. Furthermore, the difference 

that exist between the groups are not very clear even on the ground, therefore several 

small scale legalized miners go beyond the concessions allocated to them and often 

entered on concessions of large-scale mines (Friends of the Nation, 2010; Nyame, FK, 

Andrew Grant, J & Yakovleva, 2009). A study reported three types of  methods of gold 

mining by artisanal and small scale miners (Aryee, BNA, Ntibery, BK & Atorkui, 2003). 

Shallow alluvial mining: this method is used to mine shallow alluvial deposits which are 

usually found in valleys or low-lying areas. The mineral barring ores are removed and 



18 
 

carried to close by waterbodies or river for washing so that the gold can be recovered. 

Illegal miner mostly employed this type of method. 

 

Figure 4: wooden sluice box use by illegal gold miners    

Source: Googleimage.org 

 

Deep alluvial exploration method is used to access alluvial that are imbedded on the 

banks of rivers. This method requires digging deep to reach the gold bearing gravel, 

which mostly located at 7 to 12 metres deep. Terraces are usually build around the sides 

of pits to avoid collapse. 

Hard rock (lode) mining involves ridges that bear the gold ores, usually located either to 

the surface or deeper in the reefs. It involves sinking of holes to meet the ridges bearing 

the gold ore or situations where ridges are too hard, explosives are commonly employed 

(Aryee, BNA, Ntibery, BK & Atorkui, 2003; Lynas, 2014). 

 

2.3 Impact of mining on Environment 

Adverse effect of mining operations on the environment have been largely reported by 

Funoh, (2014) and Lynas, (2014). However, specific attentions have been focused on 

large and small-scale mining operations in the environment. Though destruction of land 

as a result of mining is very marked, chemical pollution from the recovering activities 

have imposed twofold of burden on the environment, the health of mining communities 



19 
 

and the people living to close sites (Yelpaala & Ali, 2005). For example, owing to illegal 

nature of gold mining in certain countries in Africa and Latin America, researchers focus 

largely  on environmental contamination and mercury exposure suffered in the mining 

and during sluicing of the ores (Hentschel Thomas,; Hruschka Felix, 2003; Hota & 

Behera, 2015). A study used a pair-wise ranking of problems, to find out natives views on 

the problems experienced in mining communities, found that the most pronounced 

problems in mining communities were pollution of water sources from mercury and 

cyanide, dust, mine pits, cracking and the collapse of buildings (Kitula, 2006). According 

to Kitula, (2006), since the establishment of Geita Gold Mine in June 2000, near the Geita 

village, almost 52 cases of housing collapse were as a result of explosion from the mine.  

Series of research have shown trends of mercury exposures from gold amalgamation 

phase (Stephens & Ahern, 2002; Drasch et al., 2001).  However, greater number of these 

works were limited to small sample size, hence were prone to biases. Although small 

numbers were used, some attempt more rigorous study designs. Study carried out in 

mining area in Philippines with a sample size of 102 workers 63 other inhabitants who 

were exposed, 100 persons living downstream of the mine, and 42 inhabitants of serving 

as controls were recruited into the study. Bio-data and hospital records reviewed for both 

workers and the inhabitants in the surrounding communities. They reported that 0% of the 

controls, 38% downstream, 27% from Mt. Diwata non-occupational exposed and 71.6% 

of the workers were found to be Hg poisoned (Drasch, G., Bose-O’Reilly, S., Beinhoff, 

C., Roider, G., Maydl, 2001).  However, others studies in Tanzania and Ecuador with a 

like study design reported lower levels of intoxication in adults but high mercury level in 

children (Stephens & Ahern, 2002). Another study conducted in Venezuela did not find 

any mercury poison, regardless of occupational and community exposures (Drake et al., 

2001) 



20 
 

In Ghana, number of studies conducted in mining area have shown that land destruction, 

environmental pollution and others were associated with mining processes. A study by 

Awatey, (2014) reported that land degradation was a major effect of small-scale mining. 

In that study 70% of residents sampled alluded that small scale mining destroys their 

lands while 30% said small scale did not destroy their lands. A further retrospective 

analysis was embarked upon to ascertain the residents in the small-scale mining 

community’s perceptions of actual causes of land degradation, 20 to 30 percent of them 

attribute it to heavy machinery and toxic materials uses (Awatey, 2014) 

The extent of damage caused by small scale mining regards to land degradation is an 

exhibit in figure 5. 

 

Figure 5: Impact of ASM on agriculture land       

Source: Awatey, (2014) 

 

Furthermore, large number (60%) of household heads sampled from the small-scale 

mining communities in the Amansie West District attested to the fact that the small-scale 

mining activities pollute their water bodies. As high as 70 percent of the above strongly 



21 
 

agreed that small-scale mining activities affects their household in terms of water 

resources. The study revealed that small-scale mining activities have been a major source 

of both surface and underground water pollution (Awatey, 2014). The degree of pollution 

of water bodies as a result of ASM in the Amansie West District is shown in figure 6. 

Another study in Prestea, Ghana revealed that ASM miner resort to water bodies as only 

means of dumping their toxic waste. They further explained that these toxic chemicals 

dumped in the water bodies pose a great threat to the safety of drinking water (Adu-

Gyamfi, 2016) and the effects are huge to cause damage to the human health, vegetation 

cover and aquatic lives. 

 

Figure 6: Effect of ASM on water body in Amansie West District 

Source: Awatey, 2014 

 

2.4 Impact of Mining on Human Health 

Health is defined as a state of complete physical, mental, and social well-being of an 

individual, and not merely the absence of diseases (WHO, 2009).  Environmental 



22 
 

pollution affects human in many ways. Although a clean environment is considered 

essential for human health and well-being, economic development has resulted in a 

considerable deterioration in environmental quality across the globe. Air pollution lead to 

serious public health problems, including acute respiratory illness and chronic bronchitis, 

and possibly premature death for more vulnerable populations (Zhang et al., 2010). 

According to WHO, air pollution is considered the world's largest single environmental 

health risk (WHO, 2014b). Globally, most of premature deaths and morbidity occur 

because of both ambient and indoor air pollution. A recent study by the WHO (2014) 

reports that about 7 million people died in 2012 because of air pollution. The populations 

of developing countries suffer more health problems associated with environmental 

degradation, compared with residents of developed nations (Hota & Behera, 2015). 

Environmental hazards, including water pollution by chemicals, air pollution and 

unhygienic conditions are largely responsible for both diseases and deaths in developing 

countries. Indoor air pollution is also an important contributor to the global burden of 

disease. Globally, 4.3 million deaths were attributable to household air pollution in 2012, 

most of which occurred in developing countries (Hota & Behera, 2015; WHO, 2014b).  

Many studies to link pollution and health-related social costs in developed countries have 

been conducted. However, the shortage of original studies in developing countries, 

researchers tend to deduce concentration-response functions estimated in the similar of 

the United States to the levels of pollution in the target country (Ostro, 1994). This 

approach faced criticism because of the different cultural, behavioral, institutional 

circumstances, couples with the difficulty of finding places with matching environmental 

conditions from which predictions can be made for the target country and, therefore, may 

yield misleading results (Gupta, 2011). Sources of air pollution in mining areas generally 

include drilling, blasting, overburden loading and unloading (CMRI, 1998). Work related 



23 
 

health issues in the mining industry differ from one mineral type to the other, and to the 

skills employed, category of mines, and the size of the concession. A study by Saha et al, 

(2011) indicated that high number of particulates suspend in the air at mining areas, and 

therefore lung diseases are very prevalent in these communities. Another study reported 

that no difference in health hazards suffered by people living near to underground mining 

site as compared with those close to opencast mining sites, because of transportation of 

ores across and related activities (Mishra, 2010). Stephen et al (2002) stated that 

mechanization of mining operations has resulted in very fine particles in the atmosphere, 

which has shown to be dangerous to the health of man. Mining residues are one of the 

important work-related hazards globally, both as short-term hurts and long term human 

health issues such as cancer and lungs conditions (Stephens and Ahern, 2002). There are 

evidences to the effect that persons close to coal mining areas were at high risk of heart 

and lungs diseases, cancer, hypertensions, and kidney disorders. Deaths are higher in 

residential areas sited close to coal mines and coal fired power stations (Hendryx, M., 

Ahern, M.M., 2008; Hendryx, M., Donnel, O.H., Kimberley, 2008). Moreover, persons 

closer to mining communities are most likely to drink water contaminated with chemical 

and remains from the mining operations. Work-related diseases like silicosis and coal 

workers pneumoconiosis (CWP) was reported in underground coal miners caused by 

breathing in dust from the mine (Schatlez, S.J., Stewart, 2012). Another study carried out 

in Jharsuguda district, Odisha, found that majority of the people suffered from various 

diseases as a result of air and water contamination. They noticed that most of people had 

airborne diseases such as respiratory diseases, tuberculosis, pneumonia, gastric disorders, 

and eye complications (Hota & Behera, 2015). 

 



24 
 

2.5 Malaria Epidemiology 

Malaria is caused by protozoa of the genus Plasmodium, transmitted to humans from 

infected female Anopheles mosquitoes. Though, over 120 plasmodium species existed, 

only four (P. falciparum, P. vivax, P. malariae, P. ovale) were known to cause disease in 

human until recently when it was discovered that a fifth specie (P. knowlesi) also causes 

disease in human (Weekley & Smith, 2013).  Over one million deaths are caused by P. 

falciparum in African where it is found in large number (Sitali et al., 2015). P. vivax is 

largely found in Asia, Latin America, and parts of Africa. This parasite is highly 

associated with Asia and therefore the most predominant malaria parasite in the world 

(Feng et al., 2015; Weekley & Smith, 2013). P. ovale, have similar morphology as 

compared with P. vivax, widely distributed West Africa, and causes more disease than P. 

vivax in Africa (Kang, Y. and Yang, 2013). The only known species to have longest 

asexual cycle is the P. malariae. It  is found globally with 24 hours asexual longer than 

other species that occur with 48 hours (CDC, 2012b).  P. knowlesi is found throughout 

South East Asia and it has recently been discovered to cause human and zoonotic malaria 

in the region. P. knowlesi has 24hours replication cycle and therefore rapidly progress 

from uncomplicated malaria to severe infection (CDC, 2012b; McCutchan, T.F., Piper, 

R.C. and Makler, 2008). 

All plasmodium species go through similar life cycle and this is complex in nature. It 

involves two different hosts of an insect vector (mosquito) and human (Figure 7). They 

exhibit both sexual cycle and asexual cycle. The sexual cycle takes place in the gut and 

abdominal wall of the female Anopheles mosquitoes while the asexual cycle takes place 

in the liver and red blood cells in human and this causes the symptoms of the disease 

(Leera S.; Hyacinth C. O. and Victoria D., 2014). During the sexual cycle, the female 

mosquito picks the microgamete (male gametocyte) during blood meal from infected 



25 
 

person to fertilize the macrogamete (female gametocyte) which then form an egg, or 

oocyst. The oocyst matures into several sporozoites that swim to the mosquito's salivary 

glands to be injected into another human at the next bite (Morrow, 2007). The malaria 

parasite mostly alternate sexual cycles with asexual cycles (alternation of generation) in 

order to continue to exist (Sacci et al., 2006). 

Malaria parasites are transmitted by female anopheles mosquitoes in humans (Bousema & 

Drakeley, 2011). Over 70 species of Anopheles mosquitoes that spread malaria across the 

globe, but less five than species could found in one region (Malaria Consortium, 2007; 

Sinka et al., 2012). In sub-Saharan Africa, the species of anopheles mosquitoes that 

spread diseases include, A. gambiae and A. funestus  (Sinka et al., 2010, 2012). A. 

funestus and two other species of the A. gambiaesensulato (s.l.) species complex (i.e., A. 

gambiae and A. arabiensis) are primary vectors of P. falciparum malaria in sub-Saharan 

Africa and A. stephensi plays a prominent role in urban malaria transmission in Indo-

Pakistan (Fontaine et al., 2012). Furthermore, A. albimanus and A. darlingi are primary 

vectors of malaria in Central America and various areas of South America (Fontaine et 

al., 2012; Lwetoijera et al., 2014) 

 

 



26 
 

 

 

Figure 7: Life cycle of plasmodium species 
Source: Morrow, 2007 
 

2.5.1 Life cycle mosquito species 

The Plasmodium species are of great health concerns both locally and at the international 

level. This is because they are found almost every in the globe. (CDC, 2014b). The two 

most important groups of the vectors are anophelines and culcines. The Anopheles 

vectors  are accountable for spreading malaria disease and the Culex parasites spread   

diseases including lymphatic filariasis, Japanese encephalitis, and West Nile virus 

(Webber, 2009; WHO, 2014a). The aedesaegypti vectors infect human with dengue virus, 

yellow fever, chikungunya and Zika virus. In all the diseases transmitted by Plasmodium 



27 
 

sp. malaria remains a serious public health issues especially in African of which Ghana is 

included (WHO, 2014a).  The Aedesaegypti mosquitoes is more of public health nuisance 

than risk in Ghana (Opoku & Amoako, 2002). 

The life cycle of mosquito has four distinctive phases which include the egg, larvae, 

pupae, and adult stage (Figure 7). The female Anopheles mosquito lays eggs in clean 

water usually at night which then hatch after a day to three days. A. gambiae is the most 

active plasmodium vector in Africa, eggs are usually laid in low standing clean water 

which seldom dries up (Jackman & Olson, 2006). In some regions of Africa, A. gambiae 

larvae were found in foot prints of heavy animals and potholes of water by the roads 

(Musoke, 2015). In America and Asia, A. darling and A. stephensi larvae are found in 

streams and ponds with clear water and muddy bottoms, with emergent or floating 

vegetation  and man-made cisterns (Williams Jacob; Joao Pinto, 2012). Within two to 

three days of right temperature and other factors, the eggs developed to larvae which are 

usually seen swimming on the surface of the water. The larvae of Anopheles rest on top 

of water because they lack air tubes and this discriminates it from Culex which position at 

an angle on the water. Mosquito larvae feed on microorganism like bacteria, algae and 

others, and changes through four larvae instar to become pupae within four to ten days 

(Jackman & Olson, 2006; Opoku & Amoako, 2002). The pupa transitional stage from 

larvae which live in water and adult mosquitoes which live on land. Mosquito pupae do 

not eat, spend most time on water surface and only move if disturbed, hence refer to as 

tumblers (Jackman & Olson, 2006). The pupae are crescent in nature, comprise of a fused 

head, thorax and a pair of breathing tubes called trumpet. This phase could remain up to 

ten days and more, depending on temperature and species of mosquito involved. The 

pupae avoid trouble by swimming deep the water using the jerky actions. After the pipa 

stage elapsed the pupa splits out at the anterior end and the adult mosquito comes out.  



28 
 

 

Figure 8: Life cycle of mosquitoes 

Source: Jackman & Olson, 2006 

 

The adult spends a few hours on top of the water and flies. The head carries the eyes, 

antennae, proboscis and two sensors (Pitts & Zwiebel, 2006). The antennae have sensors 

that detect sounds and guide the female anopheles mosquito to the host whereas it feeds 

through the proboscis (CDC, 2012b). The adult mosquito is the one human beings often 

come to closure with. When the Anopheles mosquitoes are feeding they position to an 

angle on the surface, and this behavior distinguished them from the Culex which stands 

parallel in the surface (Webber, 2009). Indeed, environmental factors influences 

distribution and transmission of malaria in large extent. A study in Nigeria indicates that 

rain provides breeding site for mosquitoes and increased humidity enhances the survival 

of the vector. It further stated that temperature affects transmission cycle of malaria. At 

below 22oC, determining number of mosquitoes surviving the parasite incubation period 

of 55 days at 18oC and stops at 16oC (Akande T.M & Musa I.O, 2005). 



29 
 

Mosquito breeds every time of the year in tropical countries, however, they increased 

number during the raining season (World Health Organization, 2006). The adult 

mosquitoes survive maximum of two weeks and this hinges on the conditions such as 

temperature, humidity and type of species (Beck-johnson et al., 2013; CDC, 2012a). The 

breeding of mosquitoes is favored if the relative humidity is above 60% and temperature 

maintains within 16.0 C to 40.0 C (Beck-johnson et al., 2013; Yamana & Eltahir, 2013). 

The female Anopheles frequently needs blood meals to develop its eggs. It is during this 

process that plasmodium parasites is deposited to human (Shililu, 2001). Anopheles 

mosquitoes detects the humans using stimuli to pick respired carbon dioxide and smells. 

It is these stimuli that lead the mosquitoes to humans for blood meals resulting in the 

transfer of the plasmodium species to human (Braack et al., 2015; Shililu, 2001). How far 

Anopheles mosquitoes could go from their habitats depends on the type of species, 

landscape, the prevailing environmental conditions like temperature and wind speed and 

among others. Though mosquitoes are usually found approximately to two to three 

kilometers away from their habitats (Thomas et al., 2013), it was established that wind 

could move the vectors beyond these limits (Lindsay et al., 1995; Midega et al., 2012). 

Interventions at small unit levels to reduce the habitants and places of reproduction have 

positive impacts of reducing the parasites population and the disease (White et al., 2011). 

In designing a control method, it is important to factor in time and place of mosquito 

dwellings. Mostly, the female anopheles mosquitoes forage at the evening and at dawn 

with only small number feeding in the day (Ndoen et al., 2011). Research conducted in 

Africa, indicated that the female vectors take blood meal during night and inside room 

(Gatton et al., 2013; Hubo et al., 2013; Killeen et al., 2013; Seyoum et al., 2012). When 

the female anopheles finished taken blood meal, it rests to help the eggs grow. Though 



30 
 

some mosquitoes stay inside rooms after feeding, others rest in places like vegetation 

(Cottrell et al., 2012; Malaria Consortium, 2007; Warrel & Giles, 2002). 

 

2.6 Global Malaria Burden 

Malaria can be found in every region of WHO, however, biggest problem is found in 

African continent. Some countries in West Africa shoulders more than 100 cases of 

confirmed malaria in 1,000 population (Figure 9). Malaria kills more compared to all 

other diseases in sub-Saharan Africa. Children below five years are mostly affected 

(Abdul-Aziz A.R.;, 2012; Cibulskis et al., 2016). The WHO African region 47, including 

Ghana, Nigeria, Democratic Republic of the Congo, Uganda, Mozambique, Burkina Faso, 

Mali, Guinea, Niger, Malawi, Côte d’Ivoire, Cameroon, Ethiopia, Kenya, United 

Republic of Tanzania, Benin, Togo and Sierra Leone mostly affected with malaria. There 

are 11 South-East Asia, 21 Eastern Mediterranean, 27 Western Pacific, 53 European and 

35 America countries formed World Health Organization (WHO, 2015a). Whiles Africa 

regions accounted for about 82% of all malaria cases, South-East Asia responsible for 

15% whist 5% for Eastern Mediterranean region (WHO, 2014c). Recent estimate show 

that many as 3.3 billion population were risked of malaria, most of these were in poorer 

Africa countries (Roll Back Malaria, 2008). In 2015, it was estimated 214 million people 

globally were infected with malaria and 88% of the cases occurred in Africa (Cibulskis et 

al., 2016). In 2012 Ghana was among top most five countries in  Sub-Sahara Africa 

region to report malaria cases (WHO, 2014c). 



31 
 

 

Figure 9: Global distribution of malaria, 2014                     

Curtesy: World malaria report, 2014 

 

Malaria causes serious illness and deaths and it has affected most endemic nations of 

which Ghana includes. Malaria could cause terminal disabilities including neurological 

disabilities, and damage to cognitive advancement in children (Sicuri, Vieta, Lindner, 

Constenla, & Sauboin, 2013). Malaria disease comes with huge economic burden and this 

is highly shouldered by poor nations (CDC, 2014; Sicuri et al., 2013). Total costs of a 

malaria incident based on severity of disease, complication and co-morbidities ranged 

from dollars $8.0 to $229 in Ghana, $5 to $137 in Tanzania, and $11 to $ 288 in Kenya 

(Sicuri et al., 2013). A study carried out in Ghana showed that, on the average three 

workdays is lost per fever episode by the patient and two workdays by the caretaker. The 



32 
 

value of these days lost to the management and treatment of fever per episode cost 

approximately $7.0 and this amounted to about 79 % of the cost of seeking treatment 

(National malaria Control Programme, 2013). Families in rural areas of evolving nations 

can hardly access malaria prevention interventions like insecticides treated nets. 

Furthermore, the negative impacts on the economic as a results of malaria in Africa is 

more than one percent of Gross Domestic Product (VPWA Ghana, 2011; WHO, 2014d). 

The burden of malaria is not only limited to the individuals but also to the health systems 

endemic nations, especially among these is sub-Sahara Africa. 

 

2.6.1 Malaria burden in Ghana 

Malaria found to be the number cause of illness and death in pregnant women and 

children below the age of five and is responsible for most hospital attendance in the 

country (GSS/GHS, 2009). Malaria is hyper endemic in Ghana, about all the 26 million 

population at risk of malaria infection (National malaria Control Programme, 2013). 

Environmental determinants like land cover of vegetation (savannah, tropical forest, and 

mangrove), swampy areas, rainfall patterns and average annual temperatures of 26 degree 

centigrade (26oC) all affect risk of disease transmission. The rain fall ranging from 

100mm to 2800mm and altitude 0-750m above sea level create conducive environment 

for the mosquito vectors to breed which significantly increase the malaria risk in Ghana 

(National malaria Control Programme, 2013) 



33 
 

 

Figure 10: Ecological Zones of Ghana   

Source: National malaria control programme, 2013 

 
P. falciparum accounted for about 90% to 98% of malaria morbidity in Ghana, while P. 

malariae and P. ovale represent 2%-9% and 1% respectively (Afudego, 2011). In 2009, 

Ghana recorded 3.7 million malaria cases with 26% confirmed (VPWA Ghana, 2011), 



34 
 

while in 2012 cases per 1000 population was 300 cases per 1000 population (National 

malaria Control Programme, 2013; VPWA Ghana, 2011). According to NMCP (2010) 

report, total OPD cases (approx. 10 million) in the country, 4 million (38.2%) were 

attributed to malaria. The most affected people were pregnant women and children 

(NMCP, 2010). Indeed, malaria prevalence in Ghana among children 6-59 months old is 

shown in figure 11. 

 

 

 

 

 

 

 

 

Figure 11: Distribution malaria prevalence in 6-59 months old children, Ghana  

Source: National Malaria Control Programme, 2013  

 

Northern 

48% 

Volta 

17% 

Ashant
i 22% 

Brong Ahafo 

37% 

Western 

36% 

Eastern 

22% 

Upper  
West 
51% 

Central 
32% 

Upper East 
44% 

Greater 
Accra 4% 



35 
 

2.7 Mining and Malaria 

Mining plays very fundamental role in the livelihoods of human and their settlements. It 

also affects the national economy positively but at the same time has contributed to the 

spread of  malaria in the mining settlements (Castellanos et al., 2016, Knoblauch et al., 

2014). 

Gold and diamond are the most exploitable natural resource globally. Approximately, 9 

million artisanal miners are actively working in the mining sectors. Though mineral 

exploration has contributed to the livelihoods of many people, to large extend it leaves a 

negative effect on the environment, which eventually detrimental to livelihoods (Chupezi, 

Ingram, & Schure, 2009).  

The Amazonian study shows that annual incidence of malaria in Brazil went beyond 10 

times since 1970, because of human movement, agricultural and open or surface mining 

areas in the Amazonian rainforest (da Silva-Nunesa et al., 2012). Approximately 315,000 

malaria smear positives confirmed in 2008 of which 99.9% were confirmed in the 

Amazon Basin. These cases represent over 56.1% of all confirmed malaria diagnosed in 

Caribbean and Americas in 2008 (da Silva-Nunesea et al., 2012; PAHO, 2009). 

According to Sibergeld et al, (2002), last decade has seen re-emergent of malaria in South 

America (Loreto and Peru) where no reported of malaria. According to the study, in 1999, 

there were 54290 confirmed slide cases of P. falciparum malaria reported such that 

majority of the cases came  from mining areas of the Amazon (Silbergeld et al., 2002). 

The negative influence on the environment due to activities of miners, affect miners, their 

families, and their communities. The open pits that fill with water during the rainy season 

may serve as a breeding ground for  mosquitoes or other parasites (Smith, Ali, Bo, & 

Collins, 2016). There are studies that revealed that gold mining contributes to spread of 

malaria through changes in the ecosystem. There were reasons cited for this happened 



36 
 

including immunologically naïve persons come into direct contact of malaria vector, the 

techniques employed in mining provide conducive environment for malaria vectors to 

breed, the activities create pools of water which aid the mosquito to propagate and 

survival. The mining activities increase human contacts with the mosquito vector and 

miners inhabit in areas that are hard to reach for surveillance activities, diagnosis and 

treatment. Lastly gold mining involves constant movement from place to place, this 

creates a mobile reservoir of human to spread the disease locally and across other 

settlement, both in in and outside the area. (Silbergeld et al., 2002; Smith et al., 2016). A 

study carryout on abandon pits from granite, quarries and agriculture revealed challenges 

in total eradication of malaria, because of water bodies that are sheltering numerous 

species of malaria organisms (Fernando, Jayakody, Wijenayake, & Galappaththy, 2016), 

which serves as reservoir for recurrent of malaria in places malaria have been eradicated. 

Another study in the French Guiana among illegal miners indicated high malaria 

prevalence of which P. falciparum accounted for majority of cases. In the same study 

asymptomatic malaria infections was 48% of the cases (Santi et al., 2016). Lihir Gold 

Limited (LGL; Newcrest Mining ltd), a mining company in Papua New Guinea, 

recognizes that malaria was a major issue affecting employee health and surrounding 

communities conducted study. Overall, 33.3% of the study participants had malaria 

parasites. Species distribution included P. vivax (57.0%), P. falciparum (40.4%) and P. 

malariae less common (2.6%) (Mitjà et al., 2013). Ghana recognizing the effects of 

mining on malaria transmission, conducted a baseline survey prior to start of mining 

activities of New-mont Ghana Gold limited in 2006/2007. The study was conducted in 

four districts in Brong Ahafo region. The prevalence of malaria among children below 

five years was 22.8% (Asante et al., 2011). P. falciparum constituted 98.1 % of the cases, 

P. malariae was less common 1.9%, there was no case of P. vivax, P. ovale detected and 



37 
 

was no mixed infection (Asante et al., 2011). A study by Nartey et al (2012), at Lower 

Manya Krobo District to assess the effect of quarry mining activities on disease 

transmission has revealed about 8-folds increased in malaria transmission after inception 

of the quarry activities. The prevalence of malaria before quarry mining was 5%, but this 

increased to 40% after work has started in the communities (Nartey, Nanor, & Klake, 

2012a). Indeed, mining activities challenge the success of malaria control programmes. 

However, a study conducted in 47 endemic municipalities including gold mining areas in 

Colombia, between 2010 to 2013 found that the national prevalence of malaria was 

89.3% (Castellanos et al., 2016). Of this, mining areas reported 36% of the malaria cases. 

This figure might probably be under recorded due to movement of illegal miners. The 

study further indicated that cases of malaria were low at alluvial (artisanal) mining areas 

(Castellanos et al., 2016). 

 

2.8 Severe Malaria and Inpatients 

The National Malaria Control Programme (NMCP) (2013), annual report, shows 

increasing trend from 2005 to 2012 of children under five inpatient malaria (severe 

malaria) cases as opposed to the non- malaria inpatients cases in 83 hospitals in Ghana. 

However, in the 2014 annual report of Ghana Health Service, cases that went on 

admission which were attributed to malaria had decreased from 38.8% in 2012 to 27.3% 

in 2014 (Ghana Health Service, 2015). A cross sectional study conducted in Burkina-Faso 

between July to September, 2012 found that of the 510 participants recruited on 

admission, 201(39.41%) were severe malaria cases (Zoungrana, Chou, & Pu, 2014). In 

this study the mean age of severe malaria cases was 19.7 months (SD=11.5). Majority of 

the severe cases 114(56.7%) were male and about 173(86.1%) lived in rural settlement. 

Indeed Greenwood et al., (1991) found that about 2% of clinical malaria cases in Africa 



38 
 

were severe malaria. In a retrospective cross sectional study conducted for the period 

2000 to 2010 in Singapore reported that of the 214 cases malaria recruited 43(20.09%)  of 

the cases were severe malaria (Chung, Guek, Low, & Wijaya, 2014). These findings were 

however limited in information regarding age and sex distribution. 

 

2.9 Malaria Prevention 

2.9.1 Historical and Global Perspective 

An intervention programmes to stop malaria in widespread regions worldwide started in 

the nineteenth century when the malaria was widespread in most continents (WHO, 

2008). In 1955, the Global Programme to eradicate malaria was launched by WHO. This 

programme used dichloro-diphenyl-trichloroethane (DDT) for Indoor Residual Spray in 

countries that were heavily infected with the plasmodium vectors (Sadasivaiah & 

Breman, 2007). Though, application of DDT was seen to be effective against the 

mosquitoes, the benefits was for only short period (Anto et al., 2009).  In 1978, World 

Health Organisation shifted from eradication to controlling which involved reduction in 

malaria to lowest bearable which would no long be public health threat. The effort to 

control malaria went beyond the use of DDT, as such environmental management 

programmes were instituted as alternative (Walker, 2000). This involved desilting 

drainages to allow water flows freely, clearing bushes around houses, refilling of dugout 

or pits and using living organisms to feed on the larvae of the mosquitoes (Musoke, 

2015).  By the year 1982, as much as 24 countries in Europe were free freom malaria 

(WHO, 1999; WHO, 2008a). Subsequently, other nations like Maldives, United Arab 

Emirates, Turkmenistan and America were declared malaria free countries in 1984, 2007, 

2010, and 2011 respectively (Meleigy, 2007).  Kyrgyzstan was the most current country 

to be certified malaria free nation by WHO in 2014 (WHO, 2014e). Malaria Control 



39 
 

Programmes are managed by WHO globally (WHO, 2014e). It has among other things 

responsible for leading the course of malaria control. In addition, the Global Malaria 

Programme provides guidelines based on established research for malaria control. Before 

2000, World Health Organisation rolled out the Roll Back Malaria (RBM) crusade and 

was prioritized on the international agenda. Indeed, huge sums of money was invested in 

the programme by many allies United State President’s Malaria Initiative as Global Fund 

United Nations Children's Fund (UNICEF), and among others (Roll Back Malaria, 2014). 

Most of the money were used to finance interventions projects like Insecticide treated 

Nets, Indoor Residual Spray and treatment cost for pregnant women and children under 

five years. (WHO, 2011). There are two main interventions WHO recommends, such as 

treated bed-nets and indoor residual spraying. Insecticide Treated Nets usage as well as 

Indoor Residual Spray has been accepted across the world in very recent (WHO, 2014). 

Certainly, several endemic countries have formulated policies which has ensured these 

interventions through mass crusade. Though, the crusade on ITNs usage has largely 

promoted, only 29% of households have adequate ITNs for all households member 

(WHO, 2014e). Furthermore, less than 4% of the world population that were at  risk of 

malaria infection used IRS in 2013, in spite of  WHO recommended 80% of houses  

coverage (WHO, 2014e). The ITNs and IRS usage is threaten by vectors developing  

resistance to the insecticides used in treating the nets and spraying (Anto et al., 2009). 

The alternative method to malaria control would involve good environmental 

management such refilling of diches, clearing of bushes around houses desilting gutters, 

proper management of landfilled  sites and biological control using larvivorous fish in 

pond (Mabaso, Sharp, & Lengeler, 2004). Though, ITNs and IRS usage have proven to 

reduction in malaria in countries like Ghana, Uganda, Mozambique , Zambia and Kenya 

(Anto et al., 2009; Eisele & Steketee, 2011; Kim, Fedak, & Kramer, 2012). Other 



40 
 

researchers have attributed the non-patronage among rural communities to high cost of 

ITNs (Willey,Paintain, Mangham, Armstrong, & Willey, 2012). However, free insecticide 

nets were used for finishing in countries such as Zambia, Tanzania, and Rwanda (Ingabire 

et al., 2015; Mclean et al., 2014). 

 

Figure 12: Roles of global malaria control programme 

Source: http://www.who.int/malaria/about_us/en/ (access 24/07/2016. 00:04) 

 

2.9.2 History of Malaria Control in Ghana 

The attempt to control malaria in Ghana began in the 1950s with the aim of reducing the 

malaria disease burden till no longer of public health significance. It was further 

identified that malaria controlled may fail if handle by the health sector only, therefore 

multifaceted policies were formulated to include other sectors. In view of this series of 

interventions were instituted to help in the control of malaria disease. Some of the 

interventions include residual insecticide application against adult mosquitoes, mass 

chemoprophylaxis with Pyrimethamine medicated salt and improvement of drainage 

http://www.who.int/malaria/about_us/en/


41 
 

system (www.ghanahealthservice.org/ghs-subcategory.php?cid=4&scid=41,24/07/2016, 

6:47am). After the WHO had launched the Roll Back Malaria Policies in 1998, Ghana 

adopted it in 2000 and the same year signed the Abuja Declaration to halve burden of 

malaria (Cruz et al., 2006; Ghana Statistical Service, 2011) through: 

 Distribution of insecticide-treated nets (ITNs) to cover populations at risk 

(especially children under the age of five and pregnant women) 

 Indoor residual spraying (IRS) to reduce transmission 

 Prevention of malaria among pregnant women through intermittent preventive 

treatment during pregnancy (IPTp)  

 Prompt diagnosis and treatment with effective medicine 

There are two major approaches of preventing malaria in Ghana. The first is integrated 

vector control which primarily aims at reducing man-vector contact through the use of 

Insecticide Treated Nets (ITNs), larviciding and Indoor Residual Spraying (IRS).  

The second preventive measure is Intermittent Preventive Treatment (IPT) that targets 

pregnant women (Ghana Statistical Service, 2011; MOH/NMCP, 2010). 

 

2.9.3 Malaria Prevention Methods 

2.9.3.1 Insecticides Treated Net 

The Insecticide Treated Nets use stems from the recommendation of Sir Ronald Ross in 

1910 (Passmore, 2010). During the second world war , Russian, German, and US armies 

treated bed nets and combat fatigues with residual insecticide to protect soldiers against 

vector-borne diseases (Lengeler, 2009). In the late 1970s, entomologists used synthetic 

pyrethroids for vector controls.  The significantly high insecticidal activity of these 

chemicals and low human toxicity has made them ideal for this purpose. 

http://www.ghanahealthservice.org/ghs-subcategory.php?cid=4&scid=41


42 
 

Studies conducted 1980s on ITNs and pyrethroids showed that pyrethroids were safe and 

ITNs had an effects on several measures of mosquito biting (Lengeler, 2009). ITNs 

distributed free in 97 malaria endemic regions across the globe. Eight five (85) regions, 

distributed ITNs or Long Lasting Insecticide Nets (LLINs) to all age groups and in 69 

countries, ITNs were distributed to all age groups through mass campaigns. In the WHO 

African Region with high risk of malaria, ITNs mass campaigns were supplemented by 

distribution of ITNs to pregnant women at antenatal care (ANC) clinics in 37 countries, 

and to infants through expanded programme on immunization (EPI) clinics in 29 

countries (WHO, 2014e). Ghana Health Service (GHS) in 2006 distributed over 20% of 

ITNs to children under five and pregnant women in Upper East, Upper West and 

Northern region. The use of ITNs had increased from 3.5 to 21.8 by 2006 (UNICEF, 

2007). Studies have shown that use of ITNs could prevent up to 7% of global under five 

mortality and 48% to 50% episodes of malaria (Cruz et al., 2006). A number of such 

studies was conducted by Haji et al (2015) who found that household possession of 

mosquito treated net in Ethiopia was 51%. Among the households that owned ITN, 34.7% 

had one net, 48.5% two and 17% possessed three or more insecticide treated nets.  Of the 

participants who possessed insecticide treated nets, 58% said they slept under nets each 

night in the past 15days and 76% slept in insecticide treated nets on the previous night. 

The proportion of children who slept under nets each night in the past15 days were 62% 

and 75% reported sleeping under insecticide treated nets the previous night before the 

study. 

 

2.10 Factors Associated with malaria infection in children 

There were many studies conducted across the globe which showed that various factors 

including socio-economic, demographic, environmental and others factors, associated 



43 
 

with malaria infection (Roberts & Matthews, 2016). For instance, Roberts & Matthews 

conducted study in Uganda which involved 4939 children under five, of which 974 

(19.7%) tested positive for malaria. There was vast difference in the disease burden of 

malaria across the regions and health facilities (Haji, Fogarty, & Deressa, 2016a; Roberts 

& Matthews, 2016). The ratio of male to female prevalence of malaria in children under 

five was about 1 (19.6%: 19.6 %). This suggested that gender was not significantly 

associated with malaria infection in children (Roberts & Matthews, 2016). Other studies 

indicated that age of child in months, parents/caregivers education, and place of 

residence, housing type and ITNs possession significantly influences child malaria status. 

A study by Wanzirah et al, (2015), revealed that modern housing was associated with low 

malaria infection in children. In this study 6816 children were recruited and examine for 

malaria, 1061 tested positive. Link of housing type and malaria infection varied 

significantly by site (p < 0.001). The likelihood of malaria infection was low in children 

who live in modern houses compare to those who live in traditional houses (Walukuba) 

(OR) 0.35, 95%CI 0.13 0.92, p = 0.03), Kihihi (OR = 0.27, 95%CI 0.10–0.71, p = 0.008) 

and Nagongera (OR 0.59, 95%CI 0.38–0.90, p = 0.01). In the study, after adjusting for 

age, gender, site and house wealth, the odds of malaria infection have been reduced by 

56% in children living in modern houses (OR 0.44, 95%CI 0.30–0.65, p<0.001). A 

similar study was conducted by (Tusting et al., 2015) found similar result that people who 

live in modern houses had low chances of malaria compared to those in traditional houses 

(OR: 0.46, 95 % CI 0.33–0.62, p <0.001). According to Haji et al, (2015), household that 

possessed ITNs has reduced odds of malaria infection. The adjusted odd ratio (aOR) was 

found to be 0.69 (95% CI; 0.56-0.85). However, the finding was contrary to work done by 

Roberts & Matthew (2016) found that use of insecticide treated bed nets or untreated nets, 

the number of nets possess by household and child sleeping in the net night prior to the 



44 
 

study was not significantly associated with malaria in children. This study sampled 

insecticide treated bed nets from the households. The mean net possessed per household 

was 2.9 and the median was 3 nets ranges (1 to 7) nets. About 96% of the households 

possessed a single mosquito treated net, whereas 76% of the study population in selected 

households slept in long lasting insecticide treated net (LLIN) night prior to the survey. 

The study of Haji et al (2015) and Roberts and Matthews (2016), further found that odds 

of malaria infection was high as child grows older (aOR, 2.19, 95% CI: 1.25-3.83) 

compared to very young children (under two years). However, gender of the study 

participants, household income level, seeking advice before visiting the current health 

facility, intervals between onset of disease and treatment, and knowledge of the causes of 

malaria by the caregivers were not significantly related to malaria infection in the 

children (Haji et al., 2016a). 

Furthermore, effect of mother’s level of educational was found to be significantly 

associated with odds of a child having malaria. For instance, a child whose mother’s level 

of education was Secondary or Higher had lower relationship of malaria compared with 

the counterparts with Primary education or no formal education (Adebayo, Gayawan, 

Heumann, & Seiler, 2016). When children of parents with a secondary education were 

compared with children of mothers who could not indicate their level of education, 

children of mothers without indication for educational level had at higher chances of 

malaria (OR 1.97, 95 % CI, 1.35–2.87). Their chances were almost the same compared to 

the children whose caregivers had no education (OR 1.961, 95 % CI, 1.345–2.858). This 

indeed, confirmed the thought that caretakers who do not indicate their educational levels 

mighty be said to have no formal education or dropout of school. In addition, children of 

caregivers who had only primary education were 59% more the chances of malaria (OR 

1.59, 95 % CI, 1.13–2.24). Though, chances of malaria in children of caregivers with a 



45 
 

higher education was 0.40 times compared with children of caretakers with a secondary 

education only, statistically there was on difference between the group (p = 0.2463). 

Finding further suggested that household wealth, number of sleeping rooms and ethnicity 

is significantly associated with child malaria. There was high odds of child having 

malaria if coming from poorer household compared with children from rich households. 

Another study by Graves et al., (2009) found household possessing of at least a single 

LLIN [(OR) = 0.66, 95% CI 0.43—0.96, P = 0.03], number of LLINs per household [OR 

= 0.76 (95% CI 0.60 - 0.95) and the asset index (OR = 0.80, 95% CI 0.67- 0.95, P = 0.01) 

to be associated with reduction in malaria. 

People who were rich had lower malaria prevalence (OR = 0.44, 95% CI 0.25- 0.77, P = 

0.004). Although, sleeping in any type of net previous night before survey reduces 

prevalence of malaria, this association was not statistically significant. Furtherance to the 

universal analysis was multivariate logistic regression with stepwise elimination showed 

that increase wealth index significantly reduces malaria prevalence (OR = 0.79, 95% CI 

0.66 - 0.94, p= 0.009). Thus, children whose parent have high incomes were 31% (95% 

C.I. = 6% - 54%) less likely of malaria infection than children who were from poor 

parents. 

The number of long lasting insecticide nets in a house was found to be associated with 

lower malaria prevalence (OR = 0.60, 95% CI 0.40 - 0.89, p= 0.012). It also revealed 

contrary to the univariate analysis, the variable ‘slept under LLIN last night’ was 

associated with increased chances of malaria after adjusting for other factors, although 

this was not statistically significant (p= 0.070). According to the Ghana Urban Malaria 

Study, (2012) made vital findings regarding some important determinants of prevalence 

of malaria in Ghana. For instance, children living in Accra were 86% (96% C.I. = 66% – 

94%) less likely to be infected with malaria compared to children in rural settlements of 



46 
 

the coastal zone. Children in the Kumasi were 85% (95% C.I. = 66% - 93%) less likely to 

be infected with malaria as opposed to children in the rural areas of the forest zone. 

Finally, children in Tamale were 68% (95% C.I. = 37% - 84%) less risk of malaria 

infection compared to their counterparts in the rural area of savannah zone. 

 

2.10.1 Anemia in Children 

An estimated burden of anemia in developing countries was 3.2 billion, of which Africa 

shouldered 64.6% and about 50% and 60% more compared to Europe (16.4%) and North 

America (3.4%) respectively (Ewusie, Ahiadeke, Beyene, & Hamid, 2014). In West 

Africa the prevalence of anemia as results of malaria ranges from 17 – 54% (Sowunmi, 

Gbotosho, Happi, & Fateye, 2010). Plasmodium falciparum (Pf) largely invades red 

blood cells (RBCs) that cause acute hemolysis and interferes with the development of the 

RBCs leading to severe anemia (Adebayo et al., 2016).Anemia is defined as children 

under 5 years of age with hemoglobin level less than11.0 g/dl are considered anemic 

(WHO. 2008). The cut-off values for the various levels of severity were: < 7 · 0 g/dl for 

severe anemia, 7·0 g/dl - 9·9 g/dl for moderate anemia and 10·0 g/dl - 10·9 g/dl for mild 

anemia. Ewusie et al, (2014) in the study of anemia among children under five in Ghana 

found the prevalence of anemia in children under five to be 78.4% (95% CI; 76.7 – 

80.2%), of this 7.8% (95% CI: 6.63-8.91) of the children were diagnosed of severe 

anemia, 48% (95% CI: 45.9-50.2) moderate and 22·6% (95% CI: 20.8-24.4) had mild 

anemia. The prevalence of anemia was high among younger (< 2 years) compared to 

older children that is 85.1% (95% CI: 81.9-88.2) and 70.5% (95% CI: 66.2-74.4) 

respectively. Similar study conducted in Accra and Kumasi found that anemia prevalence 

decreases with increasing age. The study found high above 60% of the younger children 

(6 – 24 months) to be  anemic (Klinkenberg et al., 2006). With Ewusie et al, (2014) there 

was no different in gender regarding anemia in children. However, the prevalence of 



47 
 

anemia was lower 81.2% (95% CI: 75.7-86.9) in urban children under five compared to 

rural children 90.1% (95% CI: 85.5-94.8). Furthermore, the distribution of anemia across 

the country saw Upper East and Upper West region having the highest prevalence of 

anemia. It was further reported that 9 children out of 10 children in these two regions 

were anemic with the estimated prevalence of 88.9% (95% CI: 80.9-94.0) and 88.1% 

(95% CI: 76.4-94.6), respectively. The lowest anemia prevalence was reported in the 

Greater Accra region, 62.3% (95% CI: 56.0-68.3). It is interesting to note that Eastern 

region with only 32% urban area contributed less to anemia prevalence compared to 

Ash