INSECTICIDE TREATED BEDNETS OWNERSHIP, USE AND MAINTENANCE
BEHAVIOUR IN KWALE, MSAMBWENI AND KINANGO DISTRICTS IN KENYA.
MAUREEN KHAMBIRA
REG NO: P57/10881/08
A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR
THE AWARD OF THE DEGREE OF MASTER OF PUBLIC HEALTH IN THE
SCHOOL OF PUBLIC HEALTH OF KENYATTA UNIVERSITY.
MARCH 2013 INSECTICIDE TREATED BEDNETS OWNERSHIP, USE AND MAINTENANCE
BEHAVIOUR IN KWALE, MSAMBWENI AND KINANGO DISTRICTS IN KENYA.
MAUREEN KHAMBIRA
REG NO: P57/10881/08
A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR
THE AWARD OF THE DEGREE OF MASTER OF PUBLIC HEALTH IN THE
SCHOOL OF PUBLIC HEALTH OF KENYATTA UNIVERSITY.
MARCH 2013 DECLARATION
This thesis is my original work and has not been presented for award of degree in any other university.
SIGNATURE: ………………………………….. Date: ……………………………..
MAUREEN KHAMBIRA
Department of Community Health
SUPERVISORS: This thesis has been submitted for examination with our approval as supervisors.
1. SIGNATURE…………………………………DATE:……………………………
DR. ISAAC MWANZO
Department of Community Health
Kenyatta University
2. SIGNATURE: …………………………………DATE: ……………………
DR. FRANCIS MUTUKU
Department of Environmental Health
Emory University
DEDICATION To my husband Samuel for his compassionate love and patience, my son Duanne Paul for being my enduring delight, my mom Sabina and my sister Darlene for their adamant support, and all those who encouraged me during this study.
ACKNOWLEDGEMENTS I acknowledge with gratitude Emory University for funding my research work. Special thanks goes to Prof. Uriel Kitron for ensuring that the research was uninterrupted.
My deepest appreciation goes to my other supervisors, Dr. Isaac Mwanzo and Dr. Francis
Mutuku for offering unlimited support, research coordination and facilitation, and for the commitment towards this work.
Many thanks to Dr. Eric Muchiri for facilitating the study and Dr. Dunstan Mukoko for guiding me through data analysis steps.
My sincere appreciation to Mr. Gichu Kihoro for offering me training in data base design, all the staff of Msambweni-Division of Vector Borne and Neglected Tropical Diseases especially Robin, Ng’ang’a, Christine, Grace, Joyce and Chisongo for their encouragement.
Special thanks to the hospital administration for providing valuable information, the field assistants for their cooperation and active participation in data collection and the entire local community for being receptive and kind.
TABLE OF CONTENTS
Title page………………………………………………………………………………………...i Declaration……………………………………………………………………………………….ii
Dedication………………………………………………………………………………………..iii
Acknowledgements……………………………………………………………………………...iv
Table of Contents………………………………………………………………………………...v
List of Tables…………………………………………………………………………...... x
List of figures……………………………………………………………………………………xii
Appendices……………………………………………………………………………………..xiii
Abbreviations and Acronyms ………………………………………………………...... xiv
Definition of Terms…………………………………………………………………...... xv
Abstract………………………………………………………………………………………..xvii
CHAPTER 1: INTRODUCTION
1.1 Background…………….………………………………………………………...... 1
1.2 Statement of the problem ………………………………………………………………...3
1.3 Justification………………………………………………………………………………..4
1.4 Research Questions………………………………………………………………………..5
1.5 Null Hypotheses……………………………………………………………………………6
1.6 General Objective…………………………………………………………………………6
1.7 Specific Objectives………………………………………………………………………...6
1.8 Significance of the study ………………………………………………………………….7
CHAPTER 2: LITERATURE REVIEW
2.1. Malaria Epidemiology in Kenya………………………………………………………...8
2.2. Malaria control………………………………………………………………………….9
2.2.1. InsecticideTreated Nets…………………………………………………………..11 2.2.1.1. Coverage of Insecticide Treated Nets……….……………………………13
2.2.1.2. Insecticide treated nets distribution channels and delivery
options………………………………………………………………………14
2.2.1.3. Long lasting Insecticide Nets ………..……………………………………17
2.2.1.4. Misuse of Insecticide Treated Nets……….………………………………18
2.2.2. Indoor Residual Spraying………………………………………………………19
CHAPTER 3: MATERIALS AND METHODS
3.1 Study area ……………………………………………………………………………….22
3.2 Study population….……………………………………………………………………..24
3.3 Exclusion criteria………………………………………………………...... 24
3.4 Inclusion criteria…………………………………………………………………………25
3.5 Study design……………………………………………………………………………...25
3.6 Variables…………………………………………………………………………………25
3.7 Sampling and sample size determination……………………………………………...25
3.8 Construction of research instruments and data collection…………………………...27
3.9 Data analysis……………………………………………………………………………..27
3.10 Ethical considerations………………………………………………………………….28
CHAPTER 4: RESULTS
4.1. Socio-demographic characteristics…………………………………………...... 29
4.1.1. Household size…………………………………………………………………..29
4.1.2 Sex………………………………………………………………………………...29
4.1.3 Marital status……………………………………………………………………30
4.1.4 Religion…………………………………………………………………………..31 4.1.5 Education level…………………………………………………………………..32
4.1.6 Occupational status of respondents……………………………………………33
4.1.7 Households monthly income…………………………………………………..34
4.2 Ownership and use of bed nets……………………………………………………….....35
4.2.1. Household possession of mosquito nets……………………………………….35
4.2.2. Universal coverage of bed nets within households owning at least one
Net………………………………………………………………………….36
4.2.3. Number of nets per household………………………………………………..36
4.2.4. Household net ownership by district...... 37
4.2.5. Insecticide treated nets / Long Lasting insecticide treated nets
Coverage……………………………………………………………………37
4.2.6. Reasons for not owning bed nets……………………………………………...38
4.2.7. Net hanging………………………………………………………………...... 39
4.2.8. Frequency of net use…………………………………………………………...39
4.2.9 Reasons for not using bed nets…………………………………………………40
4.2.10. Net ownership and use by category of owners……………………………..40
4.2.11. Net use by household……………………………………………………...... 41
4.2.12. Mean number of people sleeping under nets per household by district…..41
4.3 Quality and maintenance behaviour of mosquito bed nets…………………………….42
4.3.1 Physical condition of bed nets as determined by presence of holes………….43
4.3.2. Net condition…………………………………………………………………….43
4.3.3. Causes of holes……………………………………………………………...... 44
4.3.4. Association between net age and physical condition of nets………………...44 4.3.5. Association between net fabric and physical condition of nets……………...45
4.3.6. Mean number of intact nets per household by district………………………46
4.3.7 Maintenance behaviour of mosquito bed nets …………………………………47
4.3.7.1. Washing frequency last six months………………………………………47
4.3.7.2. Net retreatment…………………………………………………………….48
4.3.7.3. Association between net re-treatment and type of net…………………..48
4.3.7.4. Retreatment insecticide…………………………………………………….49
4.3.7.5. Cost of retreatment insecticide…………………………………………….49
4.3.7.6 Reasons for non-retreatment of bednets…………………………………...50
4.3.7.7. Association between net maintenance behavior and the condition of the
net…………………………………………………………………………………...51
4.4 Extent of insecticide treated nets misuse activities …………………………………….52
4.4.1 Proportion of households with net misuses stratified by district……………….55
4.4.2 Coverage of reserve nets and the reasons for accumulation
of extra nets……………………………………………...... 55
4.4.3. Comparison of presence of reserve nets in households using or not using
nets……………………………………………………………………………………56
CHAPTER 5: DISCUSSION
5.1 Socio-demographic characteristics ……………………………………………………..58
5.2.1 Ownership of bed nets…………………………………………………………………61
5.2.2 Bed net use……………………………………………………………………………...63
5.3.1. Physical condition of bed nets as determined by presence of holes…………………65
5.3.2. Maintenance behaviour of mosquito bed nets………………………………………..66 5.3.3. Association between net maintenance behaviors and the condition of the
net…………………………………………………………………………………...68
5.4. Extent of ITN misuse ……………………………..……………………………………..69
CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS
6.1 Conclusions………………………………………………………………………………72
6.2 Recommendations for policy making and planning…………………………………..74
REFERENCES………………………………………………………………………………….76
APPENDICES ………………………………………………………………………………….83
APPENDIX I: Questionnaire…………………………………………………………………..83
APPENDIX II: Consent form………………………………………………………………….93
LIST OF TABLES
TITLE PAGE Table 4.1: Distribution of household residents ………………………………………………29
Table 4.2: Distribution of respondents by sex ………………………………………………..29
Table 4.3: Distribution of respondents by marital status…………………………………….31
Table 4.4: Distribution of respondents by religion…………………………………………...32
Table 4.5 Distribution of respondents by level of education…………………………………33
Table 4.6: Distribution of respondents by type of occupation……………………………….34
Table 4.7: Distribution of households by average monthly income ……………………...... 35
Table 4.8: Household net ownership…………………………………………………………..36
Table 4.9: Average number of nets per person………………..……………………...………36 Table 4.10. Distribution of households by number of nets owned..…………………………37 Table 4.11. Net ownership by district………………………………………………………….37
Table 4.12. Net coverage by type….…………………………………………………………...38
Table 4.13. Reasons for not owning bed nets…………………………………………………38
Table 4.14. Presence of net hanging over sleeping space………………………………….....39
Table 4.15. Net use frequency….………………………………………………………………39
Table 4.16: Reasons for not using bed nets…………………………………………………...40
Table 4.17: Net ownership and use by category of owners…………………………………..41
Table 4.18. Use of nets by household members………………………………………………41
Table 4.19: Net use by district ………………………………………………………………...42
Table 4.20. Presence of holes…………………………………………………………………...43
Table 4.21: Condition of nets …………………………………………………………………44
Table 4.22. Causes of holes on bed nets……………………………………………………….44
Table 4.23. Net condition stratified by age……………………………………………………45
Table 4.24. Net condition stratified by type of net fabric……………………...……………46 Table 4.25. Distribution of households with intact nets per district ………………………..47
Table 4.26. Proportion of re-treated nets ……………………………………………………48
Table 4.27. Net re-treatment by type of net…………………………………………………...49
Table 4.28. Type of re-treatment insecticide..………………………………………………...49
Table 4.29. Cost of insecticide………………………………………………………………….50
Table 4.30. Reasons for non-retreatment of bed nets………………………………………..50
Table 4.31. Association between net maintenance behaviors and the condition of the
net…………………………………………………………………………………….51
Table 4.32 Rate of misuse of nets and types of net misuses…………………………………..53
Table 4.33. Types of nets preferred for misuse……………………………………………….54
Table 4.34. Extend of net misuse by district ………………………………………………….55
Table 4.35. Coverage of extra bed nets………………………………………………………..56
Table 4.36 Comparison of presence of reserve nets in households using or not using
nets…………………………………………………………………………………..57
LIST OF FIGURES
TITLE PAGE
Figure 3.1: Map of Kenya showing location of the study sites………………………………23 Figure 4.1: Frequency of washing bed nets in six months…………………………………...48
APPENDICES
Appendix I: Questionnaire…………………………………………………………………83
Appendix II: Consent form………………………………………………………………….93
ABBREVIATIONS AND ACRONYMS
ACT- Artemisinin Combination Therapy
AL- Artemether Lumefantrine AQ- Amodiaquine
CL- Chloroquine
HH- Household
ITNs- Insecticide Treated Nets
KEMRI- Kenya Medical Research Institute
LLITNs- Long Lasting Insecticide Treated Nets
NLLITNs- Non Long Lasting Insecticide Treated Nets
PHI- Proportionate Hole Index
RBM- Roll Back Malaria
SP- Sulphurdoxine Pyrimethamine
SPSS- Statistical Package for Social Sciences
SSA- Sub- Saharan Africa
TBAs- Traditional Birth Attendants
WHO- World Health Organization
DEFINITION OF TERMS
Net coverage: The fraction of households that owned at least one bed net (treated or untreated).
Can also be variably referred to as net ownership or net possession. Any net: A bed net that was either treated or untreated.
Insecticide Treated Net: Referred to a Long Lasting Insecticide Treated Net or any
conventional net that had been re-treated with an insecticide within the
last six months.
Conventional net: It is a mosquito net that has been treated by dipping in a WHO-recommended
insecticide. To ensure its continued insecticidal effect, the net should be re-
treated after three washes, or after every six months.
Long lasting insecticidal net: It is a factory-treated mosquito net made with netting material
that has insecticide incorporated within or bound around the
fibres. The net must retain its effective biological activity
without re-treatment for at least 20 WHO standard washes under
laboratory conditions and three years of recommended use under
field conditions.
Net use: The percentage of household members who slept under any net or an ITN during the
night preceding the survey
Net distribution: It is about how nets and insecticides are transported to their distribution point.
Net delivery: It is about how nets and insecticides reach the population or target groups.
Net condition: Referred to the number, size and distribution of holes on the nets.
Damaged net: Any net with >5 holes of ≥2.7cm in diameter.
Intact net: Any net with no holes or ≤5 holes of ≥2.7cm in diameter.
Net maintenance behaviours: Referred to net re-treatment, frequency of washing and net
repair.
ITN misuse activities: The deployment of ITNs for other activities other than prevention of malaria
Reserve nets: Extra nets that were not used
Mortality: Death
Morbidity: Illness
Epidemiology: The study of the distribution and determinants of health-related states or events
in specified populations, and the application of this study to the control of health
problems
ABSTRACT
Malaria is associated with more than 216 million episodes and an estimated 655,000 deaths annually world-wide. In Africa, it remains the leading cause of childhood and maternal morbidity and mortality, accounting for more than two-thirds (81%) of reported cases of disease, as well as approximately 91% of the deaths. Out of the five species of Plasmodium (P falciparum, P vivax, P ovale, P malariae, and P knowlesi) that cause malaria in humans, Plasmodium falciparum is the most dangerous in Africa. In Kenya, a third of out-patient attendance to health facilities are due to malaria and 26, 000 children die annually from it. In recent years following a massive introduction and campaign for the use of insecticide-treated bed nets (ITNs), morbidity and mortality particularly of pregnant women and children has declined significantly. However, many challenges regarding ITN distribution, acceptance, consistent and appropriate use persist, and there has also been lack of follow-up studies on insecticide treated bed nets especially after free mass distribution campaigns. To address this gap, a cross-sectional survey on ITNs was conducted in southern coastal Kenya after the 2006 mass distribution campaign. The study was conducted in Msambweni, Kwale and Kinango districts where malaria is endemic. The objective of this study was to determine insecticide treated bed nets ownership, use and maintenance behavior in Kwale, Msambweni and Kinango districts in Kenya. A total of 1176 households were selected, and quantitative data was collected using a questionnaire and inspection of nets. All data were entered into a database and analyzed for patterns and associations. The results have shown high (80%) coverage of bed nets (treated or untreated) and moderate use (64%). Cost and lack of money were the main barriers to net ownership. Household ownership of any net varied by district (χ2 = 104.225, p=001), Kinango District (94%) had the highest proportion of households that own bed nets. Discrepancies in use of nets were also noted among the three districts (p=0.001, F=37.050). Kinango District had the highest (3.86) mean number of people sleeping under net per household, followed by Msambweni District (3.3) and Kwale District (2.24). Sixty nine percent of the total nets inspected had more than 5 holes of >=2.7cm in diameter and were classified as damaged. Presence of intact (not damaged) nets varied by district (p=0.001, F=16.000). Kinango District had the highest (1.19) mean number of nets that were still intact per household followed by Kwale District (0.73) and Msambweni District (0.72). Appearance of holes diminished the useful life of 53% of nets by the end of one year of net use (χ2 = 7.9468, p=0.0188). Only a small percentage (21%) of the nets with holes were repaired (χ2 = 99.7408, P=0.001). The owners of a substantial (31%) number of nets did not adhere to the recommended washing frequency and this was not significantly associated with the condition of the net (χ2 =1.9097, p=3849). Sixty nine (69%) of the retreated nets were LLITNs (χ2 = 38.0734, P=0.001) indicating lack of knowledge as to which nets should be retreated. Eighteen percent of the total households surveyed misused their nets. Presence of net misuse was significantly associated with district of residence (χ2 =10.047, P=0.018). Majority (42%) of the misused nets were used as chicken shed. This study provides valuable information for the Ministry of Public Health and Sanitation and other Government units, NGO‘s and community groups in planning, execution and assessment of ITNs programmes. In view of the foregoing, it is recommended that universal distribution of LLITNs should be conducted at much shorter intervals. Evidence from this study demonstrates that physical deterioration of the nets seems to occur at a faster rate.
CHAPTER 1: INTRODUCTION
1.1 Background
Malaria is a co-factor to poverty and underdevelopment (WHO, 2006a: 2009a) and affects populations in tropical and subtropical areas world-wide, including an increasing number of travelers visiting these areas. It causes an estimated 216 million episodes and 655,000 deaths annually, majority (86%) of the deaths are recorded in children under five years (WHO, 2011). In Africa, it is still the leading cause of ill health and death, accounting for more than two-thirds (81%) of total reported cases of disease, as well as approximately 91% of total deaths (WHO, 2011). This problem has been compounded by the presence of fragile economies, ideal climatic conditions for the breeding of Anopheles gambiae mosquito vector, lack of commitment from governments and communities (Okech et al., 2008), and evolution of parasite resistance against chloroquine and sulphadoxine-pyrimethamine (SP) treatment regimens (WHO, 2009b; Sachs and Malaney, 2002).
Out of the five species of Plasmodium (P falciparum, P vivax, P ovale, P malariae, and P knowlesi) that cause malaria in humans (WHO, 2009a), Plasmodium falciparum is the most dangerous in Africa (Hyde, 2002). Malaria has a potentially large economic impact limiting the productivity of a country‘s major assets, its people (Mills, 1991). It contributes to loss of economic growth by 1.3% annually (WHO, 2009a) and households spend US $ 5-7 per episode of malaria (DOMC, 2009a). In Kenya, a third of out-patient attendance in health facilities is due to malaria and 26,000 children die annually from the disease (Watsierah et al., 2010). In Kwale county for example, malaria morbidity was found to range between 30-40% of outpatient and inpatient attendants respectively in most health facilities. Mortality due to malaria ranges between 10-15% in Kwale county (KRCS, 2007). Therefore the importance of successful control measures on human health and in extension the national economy cannot be overemphasized
(KMIS, 2007; Okiro et al., 2007).
Studies in Sub-Saharan Africa have shown that insecticide-treated nets significantly reduce the risk of morbidity and mortality in childhood (Philip-Howard et al., 2003; Lengeler, 2004;
Lindblade, 2004). It has been established that ITNs provide protection both to individuals sleeping under them and to surrounding community members (Hawley et al., 2003). The effect of ITNs on reducing morbidity and mortality and providing community-wide protection is highly significant, making ITNs one of the most promising and cost-effective malaria prevention measures (WHO2009a; Lengeler, 2004). The effectiveness of ITNs as a malaria control tool is dependent on coverage (Noor et al., 2007; Fegan et al., 2007), acceptability and affordability by the population at risk (Breman et al., 2006). The efficacy of ITN is contingent on the habits, biology and susceptibility of the mosquito vector, the compliance of the human population and the concentration of insecticide on or in the fibre (Breman et al., 2006).
Considering the importance of bed nets in malaria control therefore, a study had to be conducted in Kwale, Msambweni and Kinango districts to determine ownership and usage of ITNs 3-4 years after mass distribution of free ITNs. The study also aimed at determining the condition and maintenance of bed nets in the study area. This descriptive study was part of a bigger study on
Eco-epidemiology of Schistosomiasis, Malaria and Polyparasitism in Kwale, Msambweni and
Kinango districts in Coastal Kenya.
1.2 Statement of the problem Despite evidence demonstrating that the use of insecticide treated nets decreases malaria-related morbidity and mortality (Okiro et al., 2007; Fegan et al., 2007), there have been many challenges to ITN distribution, acceptance, consistent and appropriate use (Alaii et al., 2003a). In
Kwale County a substantial number (42%) of households do not own ITNs (KMIS, 2007) and as a consequence malaria morbidity ranges between 30-40% of outpatient and inpatient attendants respectively in most health facilities. Mortality due to malaria ranges between 10-15% in Kwale county (KRCS, 2007).
A recent study in Western Kenya has shown that 60% of all adults and children can achieve equitable community-wide benefits of protection against malaria transmission (Killeen et al.,
2007a). Nevertheless the question is, should the reported bed net coverage (58%) in malaria endemic areas immediately after the mass distribution of free ITNs be construed to mean the nets are being used properly? Other studies have reported that possession and appropriate use of ITNs do not automatically go hand-in-hand (Gerstl et al., 2010 and Githinji et al., 2010).
Even with high coverage and adherence, ITNs do not provide personal protection unless they are in good condition and all holes fully repaired (Malima et al., 2008), since hole formation is concurrent with insecticide loss (Smith et al., 2007). This underscored the need to conduct a study to investigate the condition of the nets after a period of 3-4 years since the mass distribution campaign in 2006. Furthermore the number of ITNs that have been lost through net misuse activities such as fishing and drying fish as reported in western Kenya (Minakawa et al.,
2008) had not been determined in the study area. Other than the Kenya malaria indicator survey which was conducted immediately after the mass distribution of free ITNs, there was a need for follow-up studies to assess ownership, proper use, condition and maintenance of the ITNs after a mass distribution campaign in a malaria endemic area.
1.3 Justification
Studies have shown that ITNs, as a malaria prevention tool, are highly cost-effective and affordable. However, their usefulness is vastly a function of coverage and adherence (Korenromp et al., 2003; Lengeler, 2004; Fegan et al., 2007; Okiro et al., 2007), acceptability and affordability by the population at risk (Belay and Deressa, 2008; Kolaczinski and Hanson, 2006;
Yukich et al., 2009) and net maintenance and retreatment (Fraser and Lyimo, 1998; Smith et al.,
2010; Gerstl et al., 2010). Currently there are efforts to increase and sustain high net coverage nationwide in Kenya through multiple net distribution and delivery strategies and thus the coverage problem in most parts of the country may be negligible in the near future. If successful, the current efforts to encourage greater use of the newly-available permanently treated net, that is, long lasting insecticide treated nets may also address the issue of net retreatment. However, there is a discrepancy between owners and users of ITNs.
With the nationwide goal to achieve 80% coverage not only to the vulnerable groups but to the rest of the community (DOMC 2009), the need to monitor use, condition and maintenance of nets is growing. Such studies will provide valuable information that could be utilized in inculcating ―net culture‖. To address this gap and provide key information, this study collected data from over 1,000 households to evaluate ownership, use, condition and maintenance of mosquito nets in communities from eight villages spanning over three districts in southern coast of Kenya.
1.4. Research questions
a. What percentage of people living in Kwale, Msambweni and Kinango districts own and
use insecticide treated nets
b. What is the condition of bed nets and the maintenance behaviour of net users in Kwale,
Msambweni and Kinango districts
c. What is the extent of insecticide treated nets misuse in Kwale, Msambweni and Kinango
districts
1.5. Null hypotheses.
a. There is no association between ITN ownership and use
b. Bed net maintenance behaviour has no effect on net condition
c. District of residence does not influence ITN misuse
1.6 General objective
To determine the insecticide treated bed nets ownership, use and maintenance behavior in
Kwale, Msambweni and Kinango districts in Kenya
1.7 Specific objectives
a. To determine ownership and use of ITNs in Kwale, Msambweni and Kinango districts b. To determine the condition of bed nets and maintenance behavior among net users in
Kwale, Msambweni and Kinango districts
c. To determine the extent of ITN misuse in Kwale, Msambweni and Kinango districts
1.8 Significance of the study
The results of this study provide valuable information for the ministry of Public Health and
Sanitation and for other Government units, NGO‘s and community groups in the planning, execution and assessment of ITN campaigns as well as inform on frequency of net distributions.
Results will also direct future net distribution strategies for maximum net utilization in preventing malaria infections.
CHAPTER 2: LITERATURE REVIEW
2.1. Malaria Epidemiology in Kenya
Malaria infection is caused by a protozoan parasite of the genus Plasmodium. There are five different species of Plasmodium that cause malaria. They include Plasmodium falciparum, P vivax, P ovale, P malariae, and P knowlesi (WHO 2009a; Nordberg, 1999). Transmission of malaria infection is caused by the bite from an infected female Anopheles mosquito, which injects sporozoites into the blood stream of the human host. The patient experiences clinical symptoms which include headaches, pain in the joints, chills and fever, vomiting and mild diarrhoea. Treatment requires timely administration of an effective antimalarial drug regimen that clears the acute symptoms and prevents the reappearance of the parasites (Nordberg, 1999;
MOH, 2006).
In Kenya, malaria is the most important infectious cause of morbidity and mortality and accounts for a third of out-patient attendance in health facilities and 26, 000 children die annually as a result of malaria (Watsierah et al., 2010). The level of malaria endemicity in Kenya can be distinguished through five major regions namely: the arid/seasonal regions of the country and these areas include North Eastern, North Western and the Southern lowland areas; the coastal region which resembles the lakeside zone only that it exhibits stronger seasonality; the highland region which experiences a low disease risk although variations in rainfall and temperatures between the years could lead to epidemics affecting all populations; the lakeside region around lake Victoria which experiences malaria transmission throughout the year and the low risk regions like the central area of the country (KMIS, 2007).
People who are especially at risk from malaria and its consequences are; children under five years of age, women in their first pregnancy, travelers from non-malarious areas, splenectomised patients and those not protected (Nordberg, 1999) due to their low immunity. Malaria also contributes to other child deaths by reducing immunity to other diseases (Schellenberg et al.,
2001). The benefit from malaria control should be a motivating factor for the government and development partners to inject additional resources in malaria control.
2.2. Malaria Control
The malaria control methods recommended by the Global Malaria Programme (WHO/GMP) include; use of insecticide treated nets, indoor residual spraying and diagnosis and prompt treatment of the cases with effective medicines.
Early diagnosis and prompt treatment of malaria remains a cornerstone of the global malaria control strategy (WHO, 1993) but this depends on correct recognition of malaria signs and symptoms, presentation at a medical establishment with trained staff. Malaria control is economically beneficial to agricultural output by increasing the quantity and quality of labour
(Kioko, 2009). Poverty reduction programmes geared at improving incomes of people living in malaria prone areas will reduce the economic burden of malaria and enable them to reach a higher standard of living. The WHO (2008a) Global Malaria Programme (WHO/GMP) recommends the following three primary interventions for effective malaria control:
a) Diagnosis of malaria cases and treatment with effective medicines
b) Distribution of insecticide-treated nets (ITNs), more specifically long-lasting insecticidal
nets (LLINs), to achieve full coverage of populations at risk of malaria
c) Indoor residual spraying (IRS) to reduce and eliminate malaria transmission.
Drug administration reduces the probabilities of transmission by reducing the load of parasite available to the vector mosquito (WHO, 2009a; Winstanley and Ward, 2006). The basis of proper treatment lies on proper diagnosis (WHO, 2009b). The wide spread of P. falciparum resistance to chloroquine and sulfadoxine-pyrimethamine prompted the search for alternative drugs (Wernsdorfer and Payne, 1991). The use of Artemether- Lumefantrine (AL) in Kenya was introduced in December 2006 (Amin et al., 2007) and has been associated with a proportional decline in pediatric malaria admissions on the Kenyan coast by 63% in Kilifi, 53% in Kwale and
28% in Malindi when combined with use of ITNs ( Okiro et al., 2007).
2.2.1. Insecticide-Treated Nets The development of the technology of insecticide-treated mosquito nets (ITNs) is one of the major innovations in the field of malariology (Lengeler, 2004; Takken, 2002; Curtis and
Mnzava, 2000b). With the inception of the global partnership to Roll Back Malaria (RBM) in
October 1998 (Nahlen et al., 2003), ITNs were adopted as one of the key tools for reducing the burden of malaria in areas of stable malaria transmission in Africa. Before then, people in many countries were already using conventional nets, mainly to protect themselves against biting insects (MacCormack and Snow, 1986; Robert and Carnevale, 1991; Alkins et al., 1994).
The use of ITNs has been established as an effective intervention against malaria (Lengeler,
2004), especially in areas where parasites have become increasingly resistant to anti-malarial drugs, such as chloroquine and where access to health services is limited and medication often inappropriate (Vijayakumar et al., 2009). ITNs protect individuals either by diverting host- seeking vectors to search for a blood meal elsewhere or by killing those that attempt to feed on that person (Killeen and Smith, 2007b). This means that treated nets not only prevent malaria in a protected individual but can also reduce malaria risk in unprotected individuals by suppressing the density, survival human blood indices and feeding frequency of vector populations.
Several randomized and non-randomized controlled trials of bed nets efficaciousness in Africa and Asia have demonstrated more than 50% protective efficacy in reducing malaria episodes,
29% protection against severe malaria disease and substantial protection against malaria
(Lengeler, 2004). Controlled trials on the use of ITNs by pregnant women in malaria endemic areas demonstrated that ITNs are associated with an increased mean birth weight, reduced low birth weight and reduced miscarriages and stillbirths in the first four pregnancies (Gamble et al., 2006). ITNs have also been shown to have a ‗mass effect‘ on malaria morbidity and child mortality in villages neighbouring areas with high ITN coverage (Hawley et al., 2003). This community-wide effect has been observed in Ghana, Coastal and Western Kenya, Papua New
Guinea and the United Republic of Tanzania (Binka et al., 2002; Diallo et al., 2004; Lindblade et al., 2004). Such studies suggest that community-wide distribution of ITNs will be a cost- effective way of controlling malaria in an area.
Increasing ITN coverage is seen as a valuable means of achieving the Millennium Development
Goal number 6 which aims at reducing child mortality by 2015 (Noor et al., 2008 and Hanson et al., 2008). African governments at Abuja committed to increase ITN coverage among vulnerable groups to 60%. By preventing malaria, ITNs reduce the need for treatment and the pressure on health services (Onwujekwe et al., 2005). There remains considerable debate about how best to deliver nets and target subsidies, in order to achieve an appropriate balance among the objectives of equity, efficiency and sustainability (Hanson et al., 2008).
Some of the major concerns regarding ITN use include, fear of the insecticide that is thought by some people to be a toxic family planning aid (Alaii et al., 2003a). Other concerns involve the effects of ITNs on acquisition and maintenance of immunity to malaria, which develops slowly and requires frequent contact with parasites in order to be maintained. It has been hypothesized that transmission reduction due to the use of ITNs could lead to a delay on the development of immunity, which would in turn lead to a shift in morbidity and mortality to older age groups in high transmission areas (Snow et al., 1997). However several epidemiological studies conducted in Ghana (Binka et al., 2002), United Republic of Tanzania (Maxwell et al., 2006), Burkina Faso (Diallo et al., 2004) and Western Kenya (Lindblade et al., 2004) on the long term effects of ITNs on morbidity and mortality patterns in young children have demonstrated that there is no shift in malaria morbidity and mortality patterns to older age groups.
2.2.1.1 Coverage of Insecticide Treated Nets
Net coverage is typically used to describe the proportion of the population possessing nets. Net coverage can also be variably referred to as net ownership or net possession. Randomized, controlled trials of insecticide treated bed nets in Africa south of the Sahara have shown that their use at high coverage in rural communities significantly improves the health of children and reduces child mortality (Lengeler, 2004). Other studies have demonstrated that use of nets increases with ownership (Korenromp et al, 2003). Thus attaining and sustaining high net coverage especially in pregnant women and children under 5 years of age has been a priority of most countries where malaria is of public health concern. Achieving high net coverage is currently vigorously being championed by three malaria initiatives, Millennium Development
Goals (MDGs), the Roll Back Malaria Partnership, and the US President‘s Malaria Initiative
(Millennium Project 2005; RBM, 2005; PMI, 2006). Scaling up coverage to at least 80% use by young children and pregnant women by 2010 was a consensus target of the three malaria initiatives.
In Msambweni, Kwale and Kinango districts like elsewhere in Kenya, bed net ownership and use was negligible before 2001 (Fegan et al., 2007). Net distribution efforts which started modestly from 2001 were boosted by the initiation of the retail programme in 2003. In 2004 subsidized distribution of bed nets to pregnant women and children through health clinics in Kenya commenced making significant contribution to net ownership. The most successful effort to scale up net usage in Kenya was seen in 2006 when 3.4 million nets were distributed at no cost during the mass distribution of free nets campaign (Okiro et al, 2007). Current estimates show that overall, 63% of households in Kenya own at least one net and 34% of households own more than one net (KMIS, 2007).
2.2.1.2. Insecticide treated nets distribution channels and delivery options
One of the challenges in the promotion of the use of ITNs for malaria control has been making them affordable and accessible to the resource poor communities, the group bearing the greatest malaria burden (Magesa et al., 2005). Distribution is about how nets and insecticides are transported to their point of delivery. Delivery is about how nets and insecticides reach the population or target groups (WHO, 2003b). The determination of distribution mechanisms and delivery options that will assure high coverage with the ITNs, especially in rural areas, remains a topical issue in many sub-Saharan African countries (Onwujekwe et al., 2005). It has been argued that the distribution of ITNs and the delivery options chosen must depend primarily on local epidemiological circumstances (WHO, 2008a; Armstrong-Schellenberg, 1999).
Distribution of ITNs and insecticides can be carried out either by the public sector, NGOs or other organizations, assisted by the private sector or unassisted private sector (WHO, 2003b).
The distribution through the public sector can be accomplished by either using existing systems, establishing new systems for example through the Community Health Workers or ‗on an ad hoc basis‘ which ensures supply as needed. Use of existing systems (for example Government hospitals) reduces costs, however this strategy is dependent upon the existing distribution schedule and transport may not be adequate. Distribution on an ad hoc basis may be unreliable, expensive and is dependent upon good stock control. Distributions carried out by NGOs and other organizations may be undertaken as part of an ITN programme although this may not be sustainable, especially if dependent upon donor funding and is also expensive. Assisted private sector combines public or NGO, and private sector efforts and this has an advantage of allowing partners to carry out the activities relevant to their skills and resource capacity. Furthermore, subsidizing distribution reduces prices for the consumer and may increase coverage in the short term. The only shortcoming of assisted private sector is that it may ‗crowd in‘ the commercial sector. Unassisted private sector uses existing private sector systems and this has a higher chance of ensuring sustainability. However, this strategy is dependent upon sales and, therefore, upon demand creation (WHO, 2003b).
There are many potential outlets for delivery of nets namely; mission or NGO clinics, Antenatal and Mother and Child Health clinics, door-to-door sale agents and retail outlets. The choice of the outlet will be determined by the overall strategy, target groups, ease of access, and availability of resources available. Delivery through mission or NGO clinics emphasizes the role of nets as a health care product by targeting clinic attendees (outpatients). This strategy adds to the workload of the already overstretched clinics and is dependent upon level of access to health facilities (WHO, 2003b). Delivery of LLINs through antenatal care services and immunization programmes is accomplished by either giving a free or subsidized LLIN or giving a voucher or coupon that can be exchanged for a LLIN at a distribution point such as a commercial outlet.
This allows one to take advantage of the existing health services to reach both pregnant women and children under the age of five years. The distribution of vouchers/coupons to the target population stimulates local trade by building and maintaining a countrywide network of outlets.
This strategy requires the participation of the private sector retail outlets which are often absent in rural areas, and additional management and monitoring systems to maximize penetration
(WHO, 2008a; 2003b).
Delivery through door-to-door sales agents is convenient for the customer as it targets a particular geographic community. However, this strategy only covers a small area and requires supervision for accountability. Retail outlets target the general population. This strategy is convenient for the customer, incurs no costs to the public sector, a potential for wider coverage and competition between retailers lead to price reductions. However, this only covers those who can afford to buy from the private sector and has a potential for price fixing by retailers (WHO,
2003b).
2.6. Long lasting Insecticide Nets
One of the primary objectives of the Roll Back Malaria (RBM) program launched in 1998 was to increase insecticide-treated net (ITN) use, specifically long-lasting insecticidal nets (LLINs) coverage among vulnerable groups (WHO, 2008a). Insecticide-treated nets (ITNs) are a well- established tool for controlling malaria, however, they require regular insecticide re-treatment, at least once or twice a year, and some malaria control programmes have reported difficulties in maintaining a regular re-treatment service (Shirayama et al., 2007). As a result of this, a new type of ITN, the long-lasting ITN (LLITN), has been developed in order to make this re- treatment service unnecessary (WHO, 2008a). The use of LLITNs has been expected to lead to an important advance in the fight against malaria (WHO, 2009b).
Long lasting Insecticide Nets are designed to maintain their biological efficacy against vector mosquitoes for at least three years in the field (WHO, 2008a) depending on models and conditions of use (WHO, 2009b). The insecticide used in LLITNs (2% permethrin) is incorporated into the netting fibre during the manufacture of the thread, while that of conventional ITNs just superficially coats the nets (WHO, 2008a).
The WHO/GMP calls upon national malaria control programmes and their partners involved in insecticide-treated net interventions to purchase only long-lasting insecticidal nets (LLINs)
(WHO, 2008a). In keeping with the WHO guidelines, finances received from the Global Fund to fight Aids, Tuberculosis and Malaria (GFATM), are supposed to be used to buy and distribute
LLINs to malaria-endemic areas free of charge (WHO, 2008a).
2.7. Misuse of Insecticide Treated Nets
The effectiveness of ITNs is not only measured by the coverage but also includes proper adherence to net use. Many people in the rural areas are not yet fully convinced of the effectiveness of ITNs for malaria prevention. The non-adherence to use of ITNs has been associated with disruption of sleeping patterns due to visitors, funerals, house constructions and other events and the perception that malaria has multiple causes (Alaii et al., 2003a, 2003b).
Non-adherence issues aside, there are reported cases of net misuse with nets being diverted to economic uses such as fishing, drying fish, protecting the nursery (cabbages and other crops) as well as for making wedding dresses (Minakawa et al., 2008, Atkinson et al., 2009). Another study in south western Kenya, found unpacked new nets reserved for visitors or diverted to other uses such as table clothes, wall hanging and curtains (Githinji et al., 2010). The misuse of mosquito nets necessitate more studies to find out how the nets are being used and develop ways of increasing their efficient use.
2.8 Indoor Residual Spraying
Indoor Residual Spraying involves the application of long- acting chemical insecticides on the walls and roofs of houses and domestic animal shelters in a given area in order to kill adult mosquitoes that land or rest on these surfaces. The primary effects of IRS towards curtailing malaria transmission are to reduce the lifespan and density of mosquitoes (Walker, 2000). The insecticides used during IRS repel mosquitoes thereby reducing the number of mosquitoes entering the sprayed room thus resulting in low human-vector contact. According to WHO, 2006,
IRS can lead to the elimination of locally important malaria vectors and also some insecticides repel mosquitoes and this reduces the number of mosquitoes entering the sprayed room.
Scientific evidence of IRS efficacy in reducing or interrupting malaria transmission in different epidemiological settings has been available since the 1940s and 1950s. This evidence formed the rationale for the introduction of IRS as a primary intervention for malaria control and eradication in 1980s (WHO, 2006a). Spraying the inside surfaces of houses with a residual insecticide, principally dichlorophenyltrichloroethane (DDT), was the main means by which the incidence of malaria was reduced to zero, or near zero, in regions where malaria was endemic in 1980s
(Curtis and Lines, 2000a). DDT has been shown to be a hormone-disrupting chemical that can affect the reproductive and nervous systems and compromises the immune system.
Different malaria eradication pilot projects were initiated in Africa from the 1950s to the 1980s with various degrees of success. These projects demonstrated that malaria was highly responsive to control by IRS with significant reduction of anopheline vector mosquitoes and malaria, although in most cases, transmission could not be interrupted (Beales et al., 1989) and IRS was not taken to scale in large parts of sub-Saharan Africa. The application of IRS consistently over time in large areas has altered the vector distribution and subsequently the epidemiological pattern of malaria in in Botswana, Namibia, South Africa, Swaziland, and Zimbabwe (Smith and
Hove-Musekwa, 2008). Anopheles funestus and Anopheles gambiae species have been eliminated or reduced to negligible levels in Benin, Bukina Faso, Burundi, Cameroon, Kenya,
Liberia, Madagascar, Nigeria, Rwanda, Senegal, Uganda, and the United Republic of Tanzania while Anopheles arabiensis is less affected by IRS because it does not rest indoors (Sharp et al.,
1990; SAMC, 2000).
Currently 12 insecticides for IRS have been evaluated and recommended by WHO Pesticide
Evaluation Scheme (WHO, 2009c). They belong to four chemical groups and include; one organochlorine (DDT), six pyrethroids (Alpha-cypermethrin, Bifenthrin, Cyfluthrin,
Deltamethrin, Etofenprox, Lambda-cyhalothrin) three organophosphates (Malathion,
Fenitrothion, Pirimiphos-methyl) and two carbamates (Bendiocarb, Propoxur). The use of IRS is on the decline (WHO, 2006a) due to lack of government commitment and financing to sustain these efforts, concerns about insecticide resistance, community acceptance and possible long term effects on environment, human and animal health (WHO,2005).
In general use of ITNs has been preferred over IRS because of the following reasons: most anophelines bite indoors late at night (Oyewole et al., 2007) and bednets thus intercept mosquitoes as they approach sleeping people in search of blood. In contrast, when walls and ceilings are sprayed, some Anopheles species may not rest there long enough to pick up a lethal dose of insecticide. In addition, irritant insecticides, such as DDT, may even shorten the resting time on the sprayed surface. Also, in many countries there is a tendency to re-plaster mud walls as soon as they have been sprayed (Mnzava, 1998; WHO, 2001), thus covering up the insecticide deposit. It is against this background that insecticide treated bednets (ITNs) were introduced‘.
CHAPTER 3: MATERIALS AND METHODS
3.1 Study area
The survey was conducted in south coastal Kenya in Msambweni District, Kwale District and
Kinango District, all located in Kwale County (Figure 3.1). The districts border Tanzania to the south-west and Indian Ocean to the east. The area is hot and humid all year round with annual mean temperatures ranging between 23 ◦C and 34 ◦C and the average relative humidity ranging between 60% and 80%. The altitude ranges from 0 to 462 meters above sea level. There are two rainy seasons, April to June and October to November, but a month hardly passes without some rains especially in areas nearer to the coastline. The total precipitation varies from 900mm to
1500mm per annum in Msambweni and Kwale districts to 500–600mm in Kinango district.
Malaria is endemic in the study area and the primary malaria vectors include An. funestus and
An. arabiensis with An. gambiae s. s. playing a secondary role (Mutuku et al., 2011).
This study was part of a bigger study on Eco-epidemiology of schistosomiasis, Malaria and polyparasitism in coastal Kenya. The data was collected from 8 villages that had been grouped into 4 ecological settings (2 in coastal estuarine ecological setting, 2 in coastal plain ecological setting, 3 in coastal slope ecological setting and 1 in inland semi-arid ecological setting) defined by elevation, temperature, rainfall, relief, location relative to Indian Ocean and land cover type.
Kwale district is on the ridge overlooking the sea line, Kinango district is on the leeward side which is dry and hot, and Msambweni district is on the windward side with constant showers.
Jego and Kidomaya are two villages located in Msambweni district and they represented the coastal estuarine environmental setting. Nganja and Milalani villages are also located in
Msambweni district and represented the coastal plain setting. Magodzoni, Vuga and Golini villages represented the coastal slope setting within Kwale district (Figure 3.1). Kinango village represented the inland semi-arid environmental setting within Kinango district.
KENY Kwale district
AAAA
A Tanzania
a
Kinan Kinango Golini Vuga gogog district Magodzo
o ni
Milalan Nganja Kidomay i aaMsambweni District Jego
Figure 3.1: Map of Kenya showing location of the study sites
3.2 Study population
The study population included all the residents of Msambweni, Kwale and Kinango districts. The estimated population for Msambweni, Kwale and Kinango districts was 288,393, 151,978 and
209,560 respectively (CBS, 2008). Msambweni and Kwale districts are predominantly inhabited by the Digo community with small proportions of Kambas and other communities especially in urban areas. Inhabitants of Kinango district are mainly from the Duruma community. Both communities are mainly subsistence farmers, growing cassava, cashew nuts, coconut, mangoes, and maize. Communities living further inland in Kinango do maintain a substantial number of cattle, goats and sheep. House construction mainly consists of framed poles with mud supporting the upper structure and palm leaves as the roofing material.
3.3 Exclusion criteria
The following were excluded from the study: All households that were not randomly sampled, respondents in sampled households who failed to consent to participate in the study, those aged below 18 years and those residing outside the study area (Kinango, Msambweni and Kwale districts). The respondents were the household heads preferably the female household head.
3.4 Inclusion criteria
The following were included in the study: All randomly sampled households within Kinango,
Msambweni and Kwale districts; respondents who consented to participate in the study from the sampled households and those aged above 18 years.
3.5 Study design
The study was a community-based cross-sectional survey of 8 villages in three districts in Kwale county, south coastal Kenya (Figure 3.1). It was part of a large project under the auspice of Case
Western Reserve University and KEMRI. The study was a purposeful cohort targeting the households under the main study on eco-epidemiology of malaria, schistosomiasis and polyparasitism. Respondents were household heads, preferably female household heads.
Quantitative data was collected using questionnaires (appendix 1), and qualitative data was collected through inspection of nets.
3.6 Variables
The dependent variables for the study included: net coverage, ITN use and net condition while the independent variables were: Socio-demographic characteristics, district, net re-treatment, washing frequency and net repair.
3.7 Sampling and sample size determination
Households in the eight villages were mapped, with the number of households per village ranging from 175 in Jego village to 513 in Milalani village and a total of 3168 households.
Sample size estimation was based on the proportion of households in malaria endemic areas in
Kenya who had at least one insecticide treated mosquito net (57.9%) rounded to 58.0% (p =
0.58), according to the 2007 Kenya malaria indicator survey (KMIS, 2007).
The following formula by Fisher et al., (1998) was used: n= Z2pqD/ d2 where:
n = Desired sample size (when population was more than 10,000)
Z- Standard normal deviation =1.96 at 95% confidence interval
p = The proportion of households with at least one insecticide treated mosquito net
q = 1 – p
D- Design effect= 8
d- degree of accuracy
n=1.96 2 X 0.58 X 0.42 x 8 0.05 2
=2994.6 approximated to 2995 households
For a population less than 10,000 the following formula by Fisher et al. (1998) was used;
nf = n______
1+ (n/N) where
nf was the desired sample when the population was less than 10,000
n was the sample when the total population was more than 10,000
N was the estimated population of the households in the 8 study villages (3168).
nf = 2995______
1+ (2995/3168)
nf = 1539.5 approximated to 1540 households
The structured questionnaire was administered to 1176 households out of a target of 1540 randomly selected households in the study area.
3.8 Construction of research instruments and Data collection
A structured interview questionnaire was developed in English (Appendix 1). The questionnaire was pre-tested in a similar village within a malaria endemic region outside the study area to clear minor ambiguities in translation and inconsistencies in interpretation so that it was simple and understandable both to interviewers and respondents. The questionnaire was administered by four trained health workers in each village under the supervision of the researcher. The interviewers were familiar with their respective study villages; the local language and the culture of the study community.
3.9 Data analysis
Data was entered into Epi Info software. Data cleaning was performed to check for inconsistencies in data entry and responses. Quantitative data was analyzed using SAS release
8.1 (SAS Institute, Cary, NC) and SPSS version 17 for Windows (SPSS, Chicago, IL, USA) statistical software package. Means, frequencies and proportions were used for the descriptive analysis of the data. Chi-square and ANOVA were used to compare dependent and independent variables
3.10 Ethical considerations
This was a sub-study of polyparasitism project which was cleared by the National Ethical
Review Committee. Further clearance was sought from graduate school- Kenyatta University.
Verbal informed consent was obtained from all respondents and the study purpose was explained to them. Confidentiality of the data was ensured by creating pass words on the computer and keeping the questionnaires under lock and key to limit access by non-users.
CHAPTER 4: RESULTS
4.1 Socio-demographic characteristics
This section presents results on the characteristics of the respondents including the households in which they resided. The socio-demographic information collected included: Sex of respondents, household size, religion, tribe, marital status, education level, occupation and household monthly income. These results are summarized in Tables 4.1-3.
4.1.1. Household size
A total of 5482 individuals were counted in the surveyed households, with a mean of 4.7 residents per household (Table 4.1).
Table 4.1: Distribution of household residents
Statistics Infants 1-5 year 6-18 year Expectant Adults Total
(<1 year) olds olds mothers (> 18 years) Total 192 845 1993 47 2405 5482
Mean 1 0.7 1.7 0.04 2.0 4.7 number per household
4.1.2 Sex
Of the 1176 respondents interviewed, the majority (72.1%) were female while 27.9% were male.
Table 4.2 shows the distribution of the respondents by sex. There was a strong significant association between sex of the respondent and household ownership of at least one any net (χ2= 19.169, df= 1, P=0.001). Net ownership was highest in households where respondents were females (84.3%) than where they were males (73.2%).
Table 4.2: Distribution of respondents by sex
Sex N % Ownership of at least one any p-value
net
Yes No
Male 328 27.9 73.2 26.8 χ2= 19.169
Female 848 72.1 84.3 15.7 df= 1
Total 1176 100 81.2 18.8 p=0.001
4.1.3 Marital status
Seventy-five percent of the respondents were married, 15% were female single parents and the rest were either separated (5%) or divorced (5%). Marital status of the respondent was significantly associated with household ownership of a bed net (Chi=24.905, df=3, P=0.001).
Bed net ownership was highest (84.3%) in households where the respondent was married, followed by divorced (80.4%) and separated (71.2%). Ownership was least (30.2%) in households where the respondents were single (Table 4.3).
Table 4.3 Distribution of respondents by marital status Marital N % Ownership of at least one p-value status any net
Yes No
Married 878 74.7 84.3 15.7 χ2= 24.905
Single 182 15.5 30.2 69.8 df= 3
Separated 59 5 71.2 28.8 p=0.001
Divorced 57 4.8 80.4 19.6
Total 1176 100 81.2 18.8
4.1.4 Religion
Islam (80.0%) and Christianity (19.9%) were the main religious denominations with other denominations accounting for 0.1%. There was a high significant association between the respondent‘s religion and ownership of bed nets (Chi=39.776, df=2, P=0.001). Bed net ownership was highest among Christians (94.9%) as compared to muslims (77.9%) (Table 4.4).
Table 4.4. Distribution of respondents by religion
Religion N % Ownership of at least one p-value
any net Yes No
Christian 234 19.9 94.9 5.1 χ2= 39.776
Muslim 941 80 77.9 22.1 df= 2
Others 1 0.1 0 100 p=0.001
Total 1176 100 81.2 18.8
4.1.5 Education level
The highest level of education attained by most respondents was primary (51.3%), with 11% having secondary level, 2.1% college level, 35.6% had no formal education. Respondents education level was significantly associated with ownership of a bed net (Chi=6.882, df=3,
P<0.076). Ownership of a bed net increased with the increasing level of education attained.
Eighty eight percent of those who had attained college level education owned bed nets, this was followed by those who had attained secondary level education (85.5%) and primary level education (82.7%). Bed net ownership was least (77.3%) in households where the respondent had no formal education (Table 4.5).
Table 4.5. Distribution of respondents by level of education
Education N % Ownership of at least one any p-value level net
Yes No Primary 601 51.3 82.7 17.3 χ2= 6.882
Secondary 131 11.2 85.5 14.5 df= 3
College 25 2.1 88 12 p=0.076
No formal 418 35.4 77.3 22.7
Total 1176 100 81.2 18.8
4.1.6 Occupational status of respondents
The majority of the participants were housewives (36.6%), followed by farmers (27.6%) small- scale traders (19.2%), employed (6.1%), fishermen (0.5%). The remaining 10% were unemployed. Respondent‘s type of occupation was significantly associated with ownership of a bed net (Chi=17.168, df=5, P=0.004). Ownership of bed nets was highest (86.1%) in households where the respondents were employed as compared to other types of occupation (Table 4.6).
Table 4.6: Distribution of respondents by type of occupation
Occupation N % Ownership of at least one p-value
any net
Yes No
Housewives 431 36.6 84.2 15.8 χ2= 17.168
Farmers 324 27.6 83 17 df= 5 Small scale 225 19.1 77.3 22.7 p=0.004 traders Employed 72 6.1 86.1 13.9
Fishing 6 0.5 83.3 16.7
Others 118 10 69.5 30.5
Total 1176 100 81.2 18.8
4.1.7 Households monthly income
Majority (75.9%) of the households had a monthly income of between Kshs 0 to 1000, while a considerable proportion (18.8%) had income ranging between Kshs 1000 to 5000. Almost 3% had income ranging between Kshs 6000 to 10000 whilst 2.1% had income ranging between Kshs
11000 to 20000. Those with income above Kshs 20000 represented 0.6% (Table 4.7).
Table 4.7: Distribution of households by average monthly income
Income level No. of households Percent Kshs 0-1000 713 75.9 Kshs 1,000-5,000 177 18.8 Kshs 6,000-10,000 25 2.7 Kshs 11,000-20,000 20 2.1 Kshs >20,000 6 0.6 Total 940 100
4.2 Ownership and use of bed nets
This chapter presents results from the analysis of various variables related to ownership and use of bed nets. Information analyzed includes; Household possession of mosquito nets, universal coverage of bed nets within households owning at least one net, number of nets per household, reasons for not owning bed nets, net hanging, frequency of net use, net ownership and use by category of owners, net use by household. Associations between various variables were further investigated including: household net ownership by district; Mean number of people sleeping under nets per household by district (Tables 4.8-19).
4.2.1. Household possession of mosquito nets
Overall, 80.1% of the households owned at least one net (treated or untreated) while 19.9% did not. The mean number of nets owned per household was 1.6. Majority (76%) of the surveyed households owned ITNs while 14.7% of the households owned conventional nets only. Nine percent of households owned both ITNs and conventional nets (Table 4.8).
Table 4.8: Household net ownership
Ownership of any net by household N (%) Yes 80.1 No 19.9 Total 100
Ownership of ITNs Percent households Households owning ITNs 76 Households owning conventional nets 14.7 Households owning both ITNs and 9.3 conventional nets Total 100
4.2.2. Universal coverage of bed nets within households owning at least one net
More than half (55%) of the households owning at least one net had too few nets (less than a net for every 2 household members); 17% had just enough nets for each member while 28%
(264/942) had excess nets (Table 4.9).
Table 4.9: Average number of nets per person
Nets per person per household Percent households < 0.5 nets per person 55 0.5 nets per person 17 > 0.5 nets per person 28 Total 100
4.2.3. Number of nets per household
Majority (34%) of the households owned one net, followed by 2 nets (26%), 3 nets (13%), 4 nets
(5%). Households which owned more than 5 nets were only 2% while 20% of the total households surveyed did not own any net (Table 4.10).
Table 4.10. Distribution of households by number of nets owned
Number of nets per household Percent households 0 20 1 34 2 26 3 13 4 5 5+ 2 Total 100
4.2.4. Household net ownership by district
Household ownership of any net varied by district, with any net ownership ranging from 66% in
Kwale district to 94% in Kinango district (χ2 = 104.225, p=001) (Table 4.11).
Table 4.11. Net ownership by district
District No. of Total Percent P-value households households (N)
owning nets
Msambweni 518 581 89.2 χ2= 104.225
Kwale 294 443 66.4 Df=2
Kinango 142 152 94 P=0.001
4.2.5. Insecticide treated nets / Long Lasting insecticide treated nets coverage
Of the 1849 nets, 88% were ITNs and the rest 12% were conventional nets. Most of the ITNs
(87%) were LLITNs and the remaining 13% were Non-long lasting insecticide treated nets
(Table 4.12).
Table 4.12. Net coverage by type
Coverage of ITNs No. of nets (%)
Number of ITNs 1626 (88) Number of conventional nets 223 (12) Total 1849 (100)
LLITNs coverage No. of nets (%) LLITNs 1422 (87) Non-LLITNs 204 (13) Total 1626 (100)
4.2.6. Reasons for not owning bed nets
Seventy-nine percent (79.2%) of those who did not own bed nets reported it was because they were too expensive for them. Other reasons for not owning a bed net included there being no mosquitoes (12.3%), feeling uncomfortable when sleeping under a net (5.7%) and being too hot
(2.8%) (Table 4.13).
Table 4.13. Reasons for not owning bed nets
Reason Percent Expensive 79.2 No mosquitoes 12.3 Uncomfortable to sleep under 5.7 Too hot 2.8 Total 100
4.2.7. Net hanging
Ninety six percent (96.4%) of the total households surveyed had hanged their nets over the sleeping place while 3.6% were not (Table 4.14).
Table 4.14. Presence of net hanging over sleeping space
Net hanging Percent nets hanging Yes 96.4 No 3.6 Total 100
4.2.8. Frequency of net use
Daily use (5 to 7 nights) was reported for 87.6% of net respondents while 8.8% had been used more than half (3 to 4 nights) of the days, 2.8% less than half (0 to 2 nights) of the days and
0.8% did not know (Table 4.15).
Table 4.15. Net use frequency
Frequency of net use Percentage 5 to 7 nights 88.3 3 to 4 nights 8.8 0 to 2 nights 2.9 Total 100
4.2.9. Reasons for not using bed nets
Among those who reported not using a bed net daily, the main reasons given included: too hot
53.8% (91), there are no mosquitoes 34.3% (58), forgot to hang the nets 4.7% (8), dirty 3% (5), difficult to hang the nets daily 3% (5) and uses the coil 1% (2) (Table 4.16).
Table 4.16. Reasons for not using bed nets
Reason Percent Too hot 53.8 No mosquitoes 34.5 Forgot to hang the nets 4.7 Dirty 3 Difficult to hang the nets daily 3 Uses the coil 1 Total 100
4.2.10 Net ownership and use by category of owners
Of the 5482 people who slept in the surveyed households, 82% of them owned at least a bed net but only 64% of the people had slept under a net the night prior to the survey. Coverage and net use was higher in infants (84%), young children (72%) and pregnant women (72%) (Table 4.17).
Despite a high bed net coverage of 80%, a relatively moderate proportion of net use (64%) the night preceding the survey was observed among household residents in this study, although this difference was not statistically significant (P=0.3940, CI 0.18 to 0.13).
Table 4.17. Net ownership and use by category of owners
Total Percent Category of owners population Percent usage ownership (N) Pregnant women 47 41 (87) 34 (72) Infant (<1 year) 192 174 (91) 161 (84) Young children (1-5yrs) 845 712 (84) 610 (72) Older children (6-18yrs) 1993 1616 (81) 1069 (54) Others (above 18yrs) 2405 1961 (82) 1612 (67) Total 5482 4504 (82) 3486 (64)
4.2.11. Net use by household
In 47% of the households, all household members slept under a net while some members slept under a net in 31.6% of the households. None of the household members slept under a net in
21.4% of the households, 6.8% (17/252) of which had nets but did not use them (Table 4.18).
Table 4.18. Use of nets by household members
Net use Percent of households All household members 47 Some members 31.6 None of household members 21.4 Total 100
4.2.12. Mean number of people sleeping under nets per household by district
The mean number of people sleeping under nets per household is 2.97. Kinango district had the highest mean (3.86) followed by Msambweni district (3.3) and Kwale district (2.24). Comparison of the mean number of people sleeping under nets in the three districts, the mean difference shown in the tables was highly statistically different between the districts (p=0.001,
F=37.050) (Table 4.19).
Table 4.19. Net use by district
District N Mean p-value
Msambweni 581 3.30 F= 37.050
Kwale 443 2.24 P=0.001
Kinango 152 3.86 (ANOVA)
Total 1176 2.97
4.3 Quality and maintenance behaviour of mosquito bed nets
Net condition was quantified by computing the proportion of nets that had no holes, or had small holes and/or had large holes. Any hole that was less than this size was categorized as a small hole while any hole whose size was >= 2.7 cm was categorized as a large hole. This chapter presents results on quality and maintenance behaviour of mosquito bed nets which includes:
Washing frequency last six months, Net retreatment, retreatment insecticide, cost of retreatment insecticide, reasons for non-retreatment of bed nets, presence of holes, net condition and Causes of holes. Associations between various variables were further investigated including:
Association between net re-treatment and type of net; Association between net age and physical condition of the nets; Association between net fabric and physical condition of the nets: Mean number of intact nets per household by district: Association between net maintenance behaviors and the condition of the net. (Tables 4.20-31).
4.3.1. Physical condition of bed nets as determined by presence of holes
Out of 1849 nets surveyed, 1843 were inspected for presence of holes and 78% were torn. In total, 53,932 holes were counted; 66% of which were small holes. The mean number of holes among the nets was 37.6 with a median of 23 holes (range: 1–397) (Table 4.20).
Table 4.20. Presence of holes
Presence of holes Percent nets Holes 77.9 No holes 22.1 Total 100
Number of holes Percent Small holes (<2.7 cm diameter) 65.9 Large holes (>=2.7 cm diameter) 34.1 Total 100
4.3.2. Net condition
A total of 908 (69.3%) nets had more than 5 holes (≥2.7cm), and were deemed damaged and offering only very limited, if any, protection; and 402 (30.7%) were in good condition (0≤5 holes of ≥2.7cm) (Table 4.21).
Table 4.21. Condition of nets
Net condition Percent nets Damaged 69.3 Intact 30.7 Total 100
4.3.3. Causes of holes
Respondents indicated that most holes (56%) were caused by the bed frame or mattress during tucking-in. This was in line with the finding that most holes (31%) were located on the front side of the net. The back side (23%), foot side (22%) and head side (21%) had almost equal proportions of holes while the top side (3%) had least number of holes. A significant amount of the holes were also caused by fire (10%) and animals (11%) such as goats and sheep (especially when people sleep in same sleeping spaces with these animals), as well as rats and other rodents
(Table 4.22).
Table 4.22. Causes of holes on bed nets
Causes of holes Percent response Bedframe and mattress 56 Animals 11 Fire 10
Net being old 9 Others 3
Don‘t know 11 Total 100
4.3.4. Association between net age and physical condition of nets
The physical deterioration of bed nets through appearance of holes continued rapidly with age.
Appearance of holes diminished the useful life of 53% of the nets by the end of one year of use,
73% by the end of two years of use, 78% by the end of three years of use and 73% by the end of four years of use. Age of the net was significantly associated with the condition of the net (Chi- square =7.9468, df=2, P=0.0188) (Table 4.23).
Table 4.23. Net condition stratified by age
Variable Options N Damaged Intact Significance
(%) (%)
Net age <1 year 17 17.7 82.4 Chi=7.9468
df=2
1 year 277 52.7 47.3 P=0.0188
2 years 274 72.6 27.4
3 years 193 78.2 21.8
4 years 294 72.6 28.6
>4 years 255 78 56
4.3.5. Association between net fabric and physical condition of nets
Over two thirds (74.7%) of the polyester nets and (66.2%) of the polyethylene nets were damaged. Physical condition of the net was significantly associated with the type of fabric.
(Chi=11.0606, df=3, P=0.0114). (Table 4.24).
Table 4.24. Net condition stratified by type of net fabric Variable Options N Damaged Intact Significance (%) (%)
Fabric Polyethylene 837 66.2 33.8 Chi=11.060 6 df=3 P=0.0114 Polyester 470 74.7 25.3
Nylon 2 100 0
4.3.6. Mean number of intact nets per household by district
The mean number of nets that were still intact per household was 0.79 in the three districts.
Kinango district had the highest (1.19) mean number of intact nets per household followed closely by Kwale district (0.73) and Msambweni district (0.72). Comparison of the mean number of intact nets per household in the three districts, the mean difference shown in the tables was highly statistically different between the districts (p=0.001, F=16.000) (Table 4.25).
Table 4.25: Distribution of households with intact nets per district
District No. of households Mean p-value
Kinango 152 1.19 F= 16.000
Kwale 443 0.73 P= 0.001 Msambweni 581 0.72
Total 1176 0.79
4.3.7. Maintenance behaviour of mosquito bed nets
Maintenance behaviour in this study referred to; washing frequency in the last six months, net re- treatment and net repair.
4.3.7.1. Washing frequency last six months
Bed net washing frequency data within the last six months prior to the survey was available for
1,839 bed nets: eighteen percent had not been washed at all, 51% (938) had been washed either once or twice (the recommended washing frequency) and 31% (570) were washed at least three times (Figure 4.1). On average, the nets were washed 2 times (range: 0-8 within last six months prior to the survey
Figure 4.1: Frequency of washing bed nets (any net) in six months
4.3.7.2. Net retreatment
Out of the total nets (n=1,849), respondents reported re-treating a third (33%) of them while 67% were not retreated. (Table 4.26)
Table 4.26. Proportion of re-treated nets
Retreatment Percent
Yes 33
No 67
Total 100
4.3.7.3. Association between net re-treatment and type of net
Lack of knowledge as to which nets should be re-treated emerged as an important issue, majority
(69%) of the nets reported to have been ever re-treated were LLITNs while the remaining 30.9% were none-long lasting insecticide treated nets. Likewise majority (80.8%) of the nets which were not retreated were LLITNs while only 19% were none-long lasting insecticide treated nets
(Table 4.27).
Table 4.27. Net re-treatment by type of net
Re-treatment N LLITN NLLITN Significance
Treated 614 69.1 30.9 Chi=38.0734 Not treated 1235 80.8 19.2 Df=2 Total 1849 76.4 23.6 P=0.001
4.3.7.4. Retreatment insecticide Almost all (98%) of the re-treatment was done with deltamethrin (branded as Power Tab); 0.2%
(1) used alpha-cypermethrin (branded as Fedona) and 1.8% did not know the insecticide used
(Table 4.28).
Table 4.28: Type of re-treatment insecticide
Insecticide Percent nets Deltamethrin (Power Tab) 98 Alpha-cypermethrin (Fedona) 0.2 Don‘t know 1.8 Total 100
4.3.7.5. Cost of retreatment insecticide
The cost for 71% of the re-treatment kits ranged between Kshs 10 - 80 while 21% of the retreatment kits were acquired for free. The cost for 8.2% of the retreatment kits was unknown
(Table 4.29).
Table 4.29. Cost of insecticide
Cost of insecticide Percent re-treatment kits Kshs 10 - 80 70.9 Free 20.9 Don‘t know 8.2 Total 100
4.3.7.6. Reasons for non-retreatment of bed nets
Lack of knowledge on the re-treatment procedure (11%) was exhibited by the respondents about the reasons for non-retreatment of the bed nets. Cost of the re-treatment insecticide was the most important reason accounting for 49% of the responses. Other barriers included; lack of access to the insecticide (13%) and fear of the effects of retreatment insecticide (4%) (Table 4.30). Table 4.30. Reasons for non-retreatment of bed nets
Reasons for not retreating bednet % response Cost of re-treatment insecticide 49 Access to the insecticide (not being available in retail shops) 13 Bednet is new 11 Lack of knowledge on how to do the re-treatment 11 Bednet is a LLIN 7 Fear of the effects of retreatment insecticide (irritates, allergic) 4 Others (bednet is old, is rarely used, there are no mosquitoes, being busy) 5 Total 100
4.3.7.7. Association between net maintenance behavior and the condition of the net.
Net condition was negatively associated with net re-treatment (p<0.05). Only 36.5% of the damaged nets were retreated. Net repairs were detected in 21.3% of the nets found with holes.
There was an average of 5 repairs per net among the repaired nets (Range: 1-35). No significant association between the frequency of washing in the last six months and the condition of the net
(p>0.05) was realized (Table 4.31).
Table 4.31: Association between net maintenance behavior and the condition of the net
Maintenance Options Physical Condition Significance behaviours % damaged % intact Chi-square =6.7967 Df=2 Retreatment Yes 36.5 31.5 P=0.0334
No 63.5 68.5 Washing >2times 33.7 33.3 Chi-square =1.9097 Df=2 frequency 1-2 times 53.2 50.8 P=0.3849
Never 13.1 15.9
Net repair Yes 21.3 0 Chi-square =99.7408 Df=1 No 78.7 100 P=0.001
4.4. Extent of insecticide treated nets misuse activities
Net misuse was discovered in 18.2% of the surveyed households. In these households, a total of
266 nets were used for other purposes other than prevention of malaria of which, 65.8% were
LLITNs while 34.2% were Non-LLITNs. Thirty five percent of these nets were acquired during the 2006 mass distribution campaign. Hospital was the most dominant source (44.4%) of these misused nets followed by shops (22.9% ), PSI (4.9%) and other sources which accounted for
(18.1%). Majority (42.1%) of misused nets were used for rearing chicken and the remaining were used as wire mesh on windows (23.7%), bathing shelter (10.5%), fencing land (7.9%), wall material (5.3%), animal shed (3%), fishing (2.3%), door curtains (2.3%) and as beddings (1.5%)
(Table 4.32).
Table 4.32 Rate of misuse of nets and types of net misuses
Net misuse by household Percent households Households with misused nets 18.2 Households without misused nets 81.8 Total 100
Coverage by type Percent nets LLITNs 65.8 NLLITNs 34.2 Total 100
Acquired Date Percent nets Before 2006 36.8 2006 34.6 After 2006 28.6 Total 100
Delivery channel Percent nets Hospital 44.4 Duka 22.9 Others 18.1 PSI 4.9 DK/DR 9.8 Total 100
Types of net misuses Percent nets
Chicken shed 42.1 Wire mesh on windows 23.7 Bathing shelter 10.5 Fencing garden 7.9 Wall material 5.3 Animal shed 3.0 Fishing 2.3 Door curtain 2.3 Beddings 1.5 Others 1.5 Total 100
Colour, shape and brand are important in determining the misuse of nets. Olyset (57.9%) nets which are mainly blue-coloured (44.4%) and rectangular-shaped (47%) were mostly misused. In terms of fabric, polyethlyne-based (57.5%) nets were majorly misused (Table 4.33). People preferred to use olyset nets since they are made from polyethylene fabric and considered to be durable to withstand tears. Rectangular nets cover a large surface area and are easy to mount when used in the fields such as chicken shed. Blue coloured nets are preferred for misuse since they are perceived not to be attracting predators as compared to white coloured nets.
Table 4.33. Types of nets preferred for misuse
Brand Percent nets Olyset 57.9 Permanet 7.9 Super net 3.4 Sunflag mmbu net 1.1 Cant Verify 29.7 Total 100
Colour Percent nets Blue 44.4 White 41 Green 14.3 Others 0.4 Total 100
Shape Percent nets Rectangle 47 Round 14.7 Modified shape 38.4 Total 100
Fabric Percent nets Polyethylene 57.5 Polyester 42.5 Total 266 (100)
4.4.1. Proportion of households with net misuses stratified by district
The highest proportion of households with misused nets (21.7%) were from Kinango district,
18.7% were from Kwale district and 16.5% were from Msambweni district. Presence of net misuse was not associated with district (χ2= 2.461, Df=2, P=0.292). (Table 4.34).
Table 4.34. Extent of net misuse by district
District No. of Total Percent P-value
households households (N)
with net
misuses
Msambweni 96 581 16.5 χ2= 2.461
Kwale 83 443 18.7 Df=2
Kinango 33 152 21.7 P=0.292
4.4.2 Coverage of reserve nets and the reasons for accumulation of extra nets
Over a third (39.5%) of the 1176 households surveyed owned extra nets. In this households a total of 675 reserve nets were counted. Of this, 29.8% were acquired during the 2006 free mass distribution campaign. The most cited reasons for the accumulation of these reserve nets include; condition (damaged/dirty) of the net (47.9%), excess nets (39.3%), no perceived risk (6.4%), fears and misconceptions (1.2%) and small size of the net (2.2%) (Table 4.35).
Table 4.35. Coverage of extra bed nets
Household with reserve nets Percent households Households with reserve nets 39.5 Households without reserve nets 60.5 Total 100
Acquired Date Percent nets Before 2006 24.2 2006 29.8 After 2006 46.1 Total 100
Reasons for accumulation of extra nets Percent nets Condition 47.9 Excess nets 39.3 No perceived risk 6.4 Fear and misconceptions 1.2 Size too small 2.2 Others 3 Total 100
4.4.3. Comparison of presence of reserve nets in households using or not using nets
There was a significant association between bed net use and presence of reserve nets in the households (Chi-square = 6.44, df=1, P=0.011). Eighty four percent of households who owned and used bed nets had excess nets which they were not using while in 15.2% of the households, none of the residents slept under a bed net yet there were extra bed nets kept (Table 4.36).
Table 4.36 Association between bed net use and presence of reserve nets
Reserve nets N Bed net usage Significance Yes No Yes 461 84.8 15.2 Chi-square = No 715 78.9 21.1 6.44 Total 1176 81.2 18.8 Df=1 P=0.011
CHAPTER 5: DISCUSSION 5.1 Socio-demographic characteristics
The average household size from this study population was 4.7 which is almost consistent with the national average of 4.4 (CBS, 2008), while the mean number of children less than 18 years was 2.6 which is less than the national average of a desired family size of 3.2 (CBS, 2008).
Ownership of a bed net depended heavily on the sex of the respondent. The respondents were either females or male household head. There was a strong significant association between sex of the respondent and household ownership of at least one any net (chi=19.169, df=1, p<0.001). Net ownership was higher (84.3%) in households where the respondent was a female than where he was a male (73.2%). The most probable reason for this is that females, especially when pregnant and children under five years are considered the most vulnerable groups and therefore, free ITN distribution campaigns have targeted these age groups (WHO, 2008a).
It was also revealed from these findings that households where the respondents were in stable marriages were more likely to own a bed net compared to those where the respondents were in unstable marriages. This finding is consistent with the findings of another study conducted in
Nyamira which found out that mothers who were married were most likely to use a bed net as compared to those who were divorced, separated or single done by (Osero et al., 2005). This could be attributed to the fact that the respondents who were single dependent on their relatives who may not consider owning a bed net as a priority over other household needs. It may also point to lack of time by the divorced and separated respondents to attend public awareness forums for malaria control due to competing demands at home and limited incomes.
Religion plays an important role in promoting preventive health services. Although the study area was mainly dominated by muslims as compared to Christians, a higher (94.9%) percentage of households inhabited by Christians owned bed nets as compared to those inhabited by muslims (77.9%). This may be due to the differences in religious teachings and practices. Due to the conservative nature of the Islamic religion, more muslims may tend to seek health care services from traditional healers other than from modern health facilities. This reduces exposure to extensive health education messages provided by health care workers in modern health facilities, including teachings on the benefits of owning and using bed nets. On the other hand christianity tends to be more liberal and receptive to health education consequently leading to improved health care seeking behavior from modern hospitals. Religion was also significantly associated with whether the respondent had any fears and misconceptions about ITNs
(Chi=14.846, df=4, p=0.005). A higher (87.7%) percentage of muslims had fears and misconceptions about ITNs compared to Christians (12.3%). This may be one of the reasons why low household net ownership was recorded in households which were inhabited by Muslims than
Christians.
Majority of the respondents were fairly literate with primary school level of education. There was a clear indication that the level of education determined ownership of a bed net by a household. Ownership of a bed net increased with the increasing level of education perhaps owing to exposure to information on malaria transmission and ability to access and purchase a net. For instance in this study, a higher (88%) percentage of respondents who completed or attended college had bed nets in their households. This finding supports a study done by Osero et al., 2005 who found out that those who had attained college level of education had ITNs and used them consistently. In Congo (DRC), it was noted that net ownership and use was higher among those with secondary school education or higher (Pettifor et al., 2008).
Majority of the respondents were in occupations with unstable income. Many of them were unemployed while some relied on small scale farming, fishing and business. Some respondents were unskilled labourers. Very few (6.1%) respondents were permanently employed and had a higher (86.1%) chance of possessing a bed net as compared to those in occupations with unstable income. This supports the findings of another study which reported that mothers in occupations with stable income had a higher chance of owning a bed net as compared to those in occupations with unstable income who had a lower chance of bed nets/ITNs ownership (Osero et al., 2005).
5.2.1 Ownership of bed nets
Results on ownership of bed nets revealed that in this community, ownership of bed nets was high. Eighty percent of the households owned at least one net (treated or untreated), 76% owned at least one ITN. These findings are significantly higher than the current national overall coverage of 57% (p<0.001, CI -0.14 to -0.19) for any net and 48% (p<0.001, CI -0.27 to -0.32) for ITNs (KMIS, 2010). They have also surpassed the current national coverage for coast endemic areas of 69.6 % (p<0.001, CI -0.042 to -0.09) for any nets and 35.4 % (p<0.001, CI -
0.16 to -0.22) for ITNs (KMIS, 2010). The bed net scale-up strategies; catch-up (mass distribution) and keep-up (distribution through antenatal clinics) (Oliveira et al., 2010) are credited for the success, consequently leading to enhanced protection of vulnerable groups, while protecting all community members (Killeen et al., 2007a; WHO, 2007). This increases household savings for other essentials of living (Afolabi et al., 2009).
Despite high bed net ownership recorded in this study, findings indicated that universal coverage was achieved in 45% of the households. This finding was below the current national universal coverage of 67% (DOMC, 2011) and also below the 100% target set by the government of
Kenya. This underlines the validity of the current national malaria policy on universal coverage target of 0.5 nets per person (or one net per two people) (DOMC 2009a). This could be attributed to the fact that a small percentage (7%) of the surveyed households owned four or more nets. In addition both routine and mass distribution of ITNs in the past have mainly targeted children under five years and pregnant women while not focusing on the other age groups.
Disparities in net ownership of bed nets were noted across the three districts. This differences were statistically significant (χ2 = 104.225, p=001). Households in Kinango district were more likely to own bed nets as compared to households in Kwale and Msambweni districts. The difference in net ownership could be attributed to the differences in socio-economic status in the three districts. Kinango could be leading in the number of richest households as compared to other two districts. It could also be linked to the fact that net distribution channels mainly used in
Kwale and Msambweni districts do not reduce inequalities between the rich and the poor. This speculation is consistent with the findings of recent studies conducted in Tanzania which indicated that the poorest households were less likely to own and use a mosquito bed net
(Ruhago et al., 2011, Bernard et al., 2009).
Ownership of LLITNs in this study (87%) was above the initial targets set by the RBM summit in Abuja of 60% coverage with LLITN for vulnerable groups (WHO, 2000; KMIS, 2007), the revised RBM objectives of 80% (RBM, 2005) and the President‘s Malaria Initiative target of
85% ( WHO, 2008b). More efforts are required to achieve the targets set by the Kenya National
Malaria Strategy (KNMS), which aims at 100% coverage with LLITN and 80% use in each targeted area (DOMC, 2009b).
Income determines demand for nets and it is also a constraint for net ownership (Kikumbih et al.,
2005). Due to the prevailing high levels of poverty and low levels of income in the study area, cost of nets was considered as a major barrier to acquisition of nets by households that did not own any net. This is consistent with the findings of another study in Eastern province which indicated that the main reasons for not having ITNs in households was lack of money and cost of nets (Malusha et al., 2009). Other reasons for not having a bed net as cited by the respondents during this study included, lack of perceived risk (No mosquitoes and hot weather conditions) and the respondents feeling uncomfortable while sleeping under a net.
5.2.2 Bed net use
Bed net use in this study was good because majority of the nets were found hanging over the sleeping place and daily use in the past week was also high (87.6%). Lack of perceived risk (no mosquites) and hot weather were the main barriers affecting net use in the study area. Overall, despite a high bed net coverage of 80%, a relatively moderate proportion of net use (64%) the night preceding the survey was observed among household residents in this study, although these difference was not statistically significant (p>0.05, CI 0.18 to 0.13). In contrast to these findings, discrepancies of 83.4 – 67.2% and 95 – 59% between ownership and usage have been observed in Sierra Leon (Gerstl et al., 2010) and Western Kenya (Githinji et al., 2010) respectively. The reported usage and ownership rates by this study should be able to offer community-wide protection since modest usage (around 60%) of all adults and children can achieve equitable community-wide benefits (Killeen et al., 2007a).
Members of the vulnerable groups (infants, young children and expectant mothers) were more likely to sleep under a net than any other household resident and this is consistent with other studies (Kulkarni et al., 2010; Bernard et al., 2009; Matovu et al., 2009 and Baume et al., 2007).
This could be attributed to the intensive health education messages regarding net use that had accompanied net distribution campaigns. Older children (6 to 18 years) in this study represented the lowest proportion of net users, yet they had been reported to be potential reservoirs of
Plasmodium falciparum especially in malaria endemic areas (Teklehaimanot et al., 2007). This therefore made them vulnerable to severe malaria and death, suggesting that ITN coverage and use should cover all age groups.
Adequate intra-household access to bed nets can only be guaranteed if distribution programmes achieve a greater net-to-person ratio (Eisele et al., 2009). In 21% of the households visited during this study, none of the household members slept under a bed net while some members slept under a net in 31% of the households visited. Furthermore, there were marked differences in the mean number of people sleeping under nets per household in the three districts including;
Kinango, Kwale and Msambweni. The study revealed that Kinango district had the highest mean number of people sleeping under nets per household as compared to the other two districts. This could be attributed to the fact that the Kinango is mainly inhabited by culex mosquitoes whose biting pressure is high and noticeable as compared to Msambweni and Kwale districts which were inhabited by the anopheles mosquitoes whose biting pressure is cryptic. This observation corresponds to the finding in another study in Nigeria where marked differences in household possession and use of treated mosquito nets were realized between two ecologically diverse regions (Afolabi et al., 2009).
5.3.1. Physical condition of bed nets as determined by presence of holes
This study investigated the physical durability of the nets and majority of the total nets counted had evidence of holes, out of which 69.3% were damaged (>5 holes of ≥2.7cm). Majority of the holes were less than 2.7cm in diameter. Majority of the holes were caused by bed frame, animals and fire. LLITNs offer protection against malaria by imposing both a physical and a chemical barrier to mosquitoes (Smith et al., 2007). The deterioration of the physical integrity of bed nets investigated by this study seemed to occur faster than expected and thus bed net replacement policies should be adjusted to occur following shorter durations. Within one year of net use, the useful life of 53% of the nets counted in this study was diminished indicating that an unknown number of nets may have been discarded. More research on the physical integrity is required. For example: what is the rate of progression from good to poor condition. Studies conducted in
Burundi and Kenya also revealed a high rate of physical deterioration after the first year of use
(Protopopoff et al., 2007 and Githinji et al., 2010).). Likewise a study conducted in Lao PDR, discovered that 40% of the nets which had been distributed 2-3 years before showed physical damage (Shirayama et al., 2007). This study compared the physical condition of the net by type of fabric and the results indicated that nets made from polyester were more damaged as compared to those made from polyethylene. This therefore meant that polyethylene fibres were strong enough to withstand the faster development of holes, suggesting the need to raise quality of fabric for LLITNs as indicated by the quantity and the size of holes in nets made from polyester. These findings are consistent with those by Shirayama and others (2007) who also found out that polyethylene-based Olyset nets were more durable than polyester.
This study revealed that the condition of the nets depended on where they were being used
(p=0.001, F=16.000). Kinango district had the highest (1.19) mean number of intact nets per household as compared to Kwale and Msambweni districts. This could be attributed to the fact that residents in Kinango district properly maintained their nets as compared to the other districts. In Ghana, significant differences in the number of intact nets between the highland areas (84.6%) and the low land areas (56.6%) after 38 months of domestic use were noted (Smith et al., 2007).
5.3.2. Maintenance behaviour of mosquito bed nets
The surveyed community in this study has poor bed net re-treatment and washing practices. A knowledge gap existed with regard to these practices, and needs to be addressed to achieve the envisaged goals of universal bed net coverage. Determination of the number and frequency of washing of the net was very important in this study because the efficacy of the net depends on how often the net is being washed and conditions of use. It has been documented that the use of alkaline soaps and repeated vigorous washing can remove some of the pyrethroid deposit from nets (Najera and Zaim, 2002). An LLITN should retain biological activity for at least 20 washes and 5 years of use, according to the WHOPES Working Group (WHO, 2007). Using this definition, the study considered the number of times that the net had been washed in the last six months, which were not supposed to exceed 2 times. The findings revealed that the owners of a substantial number of nets did not adhere to the recommended washing frequency (at least three times) and this implied that they were less effective. This closely compares with the findings of a study done in Lao PDR which found out that 30.9% of the households that had received Olyset nets washed their nets more frequently than needed (Shirayama et al., 2007).
Lack of knowledge as to which nets should be re-treated emerged as an important issue. Majority of the nets reported to have been ever re-treated were LLITNs (Olyset nets and Permanet). This raised more questions about the quality of the messages delivered by those who distribute the nets. It also raised questions about the identity and experience of those who conduct and provide the re-impregnation of nets. To alleviate difficulties in maintaining a regular re-treatment service
(Shirayama et al., 2007) for conventional nets, WHO Pesticide Evaluation Scheme prompted industries to develop Long Lasting Insecticide Treated Nets (LLITNs) which are ready-to-use, factory pre-treated nets that require no further treatment during their expected life span of 3-5 years and up to 20 washes (WHO, 2009b; 2007).
5.3.3. Association between net maintenance behavior and the condition of the net
Understanding the association between maintenance behaviors and the condition of nets is crucial when determining the useful life of a bed net. Findings of this study showed that only a small (36.5%) percentage of the badly damaged nets were retreated, indicating that majority
(63.5%) of these nets suffered extensive damage and insecticide loss and were thus no longer effective in preventing malaria transmission, raising the need to continue availing only LLITNs through various distribution channels. Other studies have documented that in the event holes develop in a bed net, net re- treatment becomes a backup protection and this is because hole formation is concurrent with insecticide loss (Smith et al., 2007). Experimental hut studies conducted by Curtis and others (1996) have demonstrated that even after 15 months of domestic use, treated nets having 6, 4 x 4 cm holes significantly inhibited and killed mosquitoes. In a
Tanzanian study, the authors discovered that periodic retreatment of physically damaged nets can still reduce parasitemia rates (Maxwel et al., 2006).
This study also revealed a low prevalence (21.3%) of bed net repairs combined with poor quality of repairs. Most of the repairs were in the form of knots and stitches but still had open holes with an average of 5 repairs per net. Only a small percentage of the nets with holes had repairs. The maintenance behavior of the residents in the study area was poor when compared with findings from Ghana which showed that 64% of the nets with holes had evidence of repairs (Smith et al.,
2007).
The efficacy of a bed net also depends on how often the net is being washed and the extent of damage. Although the findings in this study failed to establish a significant association between the condition of the net and frequency of washing in the last six months (p>0.05), it was evident that a substantial (33.7%) number of the damaged nets had been washed more than recommended. Therefore, the efficacy of these nets was reduced suggesting a need for extensive health education messages targeting maintenance of bed nets and their conditions.
5.4. Extent of ITN misuse This study revealed that a substantial number of households used nets for other activities other than protection against malaria. Nets were being used as chicken shed, wiremesh on windows, bathing shelter, fencing land, wall material, animal shed, fishing, as door curtains and as beddings. This widespread misuse of bed nets may hinder efforts towards realization of targets set by the Kenya National Malaria Strategy, Abuja summit and RBM. Elsewhere, cases of net misuse have been reported with nets being diverted to economic uses. For instance, in fishing communities living a long Lake Victoria, ITNs were used for fishing and drying fish (Minakawa et al., 2008). Similarly in Zambia bed nets were reported to have been used for fishing (Hopkin,
2008). Atkinson et al., 2009 also found out that nets were used as wedding dress material.
Long lasting insecticide treated nets are readily acquired free of charge from health facilities or through free mass distribution campaigns. This study revealed that a significant proportion of misused nets were obtained during the 2006 free mass distribution campaign, a finding which concurs with the documented evidence which reported that misuse of bed nets started in the year
2006 when the Kenya Ministry of Health and NGO‘s began distributing LLITNs (Minakawa et al., 2008). Information acquired in this study affirmed that ITNs obtained through the free mass distribution campaign in 2006 was associated with various fears and misconceptions including;
‗Talking nets‘, ‗Have devils‘ and ‗Sing‘. This could have acted as motivating factors for the residents to misuse the nets.
Olyset nets made from polyethylene and distributed for free either through routine Maternal and child health (MCH) clinics or free mass distribution campaigns were predominantly misused. In line with this finding, another study conducted in Nyanza found out that 84.5% of the nets used for fishing and drying fish were obtained for free or at subsidized prices from NGO‘s and local health facilities (Minakawa et al., 2008). These findings implied that free nets were not given value compared to nets that had been bought at a price. This is why majority of the misused nets were the ones acquired free of charge. There was no difference in proportion of households that misused their nets among the three surveyed districts.
A substantial number of households had an accumulation of excess nets and this could be attributed to the fact that ‗one-net-per vulnerable child‘ strategy was used during the free mass net distribution campaign in 2006. A considerable number of these excess nets were acquired in
2006 during the free mass distribution campaign. This view is consistent with the findings of
Baume et al., 2009 who found out that the most used nets were those that had been purchased as compared to free nets. Presence of surplus nets in households implied that those households already had other nets which they were using. In this study, presence of reserve nets was mainly reported in households that were already using nets (84.8%) than those that did not (78.9%). Net condition (dirty or torn) was the main factor leading to accumulation of extra nets while some households had reserve nets because they were considered as extra nets and in good condition.
CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS
6.1 Conclusions
Based on the results of this study the following conclusions were drawn
1. The results have shown high (80%) coverage of bed nets (treated or untreated) and
moderate use (64%). Cost and lack of money were the main barriers to net ownership.
Household ownership of any net varied by district (χ2 = 104.225, p=001), Kinango
district (94%) had the highest proportion of households that own bed nets, followed by
Msambweni district (89.2%) and Kwale district (66%).
2. Discrepancies in use of nets were noted among the three districts. Kinango district had
the highest (3.86) mean number of people sleeping under nets per household, followed by
Msambweni district (3.3) and Kwale district (2.24). These mean differences were
statistically different between the districts (p=0.001, F=37.050).
3. Infants (84%), 1 to 5 years old (72%) and pregnant women (72%) represented the highest
proportion of persons using bed nets.
4. Sixty nine percent of the total nets inspected had more than 5 holes of >=2.7cm in
diameter and were classified as damaged
5. Presence of nets which were still intact (not damaged) varied by district (p=0.001,
F=16.000). Kinango district had the highest (1.19) mean number of nets that were still
intact per household followed by Kwale district (0.73) and Msambweni district (0.72).
6. There was lack of knowledge as to which nets should be retreated due to the quality of
messages delivered by those who distribute the nets, 69% of the retreated nets were
LLITNs. 7. The owners of a substantial number of nets (31%) did not adhere to the recommended
washing frequency (less than or equal to 2 washes in six months)
8. Only a small percentage (21%) of the nets with holes were repaired.
9. Eighteen percent of the total households surveyed misused their nets. Highest proportion
of households with misused nets (21.7%) were from Kinango district, 18.7% were from
Kwale district and 16.5% were from Msambweni district, although this difference was
not statistically significant (χ2= 2.461, Df=2, P=0.292),
10. Various misuse activities were identified in this study including: rearing chicken, as
wiremesh on windows, bathing shelter, fencing land, wall material, animal shed, fishing,
door curtains and as beddings.
6.2 Recommendations for policy making and planning
1. Universal distribution of LLITNs should be conducted at much shorter intervals than the
suggested 3 years period as per the Kenya National Malaria Strategy, since physical
deterioration of the nets occurred at a faster rate. 2. There is need for manufacturers to raise the fabric quality for LLITNs as indicated by the
quantity and the size of holes in nets made from polyester. Nets made from polyethylene
fibres would be able to withstand physical damage for a longer time.
3. Communities to benefit from the distribution of LLITNs should receive quality education
on proper use and maintenance of these commodities and their importance to the health
and wealth of the households.
4. Before free mass net distribution campaigns, it is important to identify those houses
without enough bed nets. This will reduce the accumulation rate of surplus nets while at
the same time maintaining the ideal number of people per net which is usually taken to be
two people per net.
5. There is need for a simplified treatment process to increase the effective lifespan of
conventionally treated nets using the K-O tabs 1-2-3®
6. There is need to intensify health education on the benefits of ITNs to create an
understanding of the connection between malaria and mosquitoes.
Recommendations for further research
More research on the physical integrity of the net is required. For example: what is the
rate of progression from good to poor condition.
Similar studies should be conducted in other areas so as to conclusively generalize the
results and remove bias introduced by geography, climate and demographics.
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APPENDICES
APPENDIX I: QUESTIONNAIRE
KWALE, MSAMBWENI AND KINANGO DISTRICT STUDY ON BED NETS
QUESTIONNAIRE/INTERVIEW GUIDE FOR HOUSEHOLD HEADS
Section 1
Identification
1. Village ______Village No_____ Household No______Study ID______
Section 2
Sociodemographic Characteristics
2) Sex: □ Male □ Female
3) What month and year were you born? ____ /______
4) Marital status:
□ Single □ Married □ Divorced □ Separated □ Refused
5) What is your tribe?
□ Swahili □ Duruma □ Digo □ Kamba □ Others______□ No response
6) What is your religion? □ Islam/Muslim □ Christian □ Refused □ Others ______
7) What was the highest level of schooling that you completed?
□ Primary □Secondary □ College □ University □ Madrassa □ None □ Refused
8) What is your occupation?
□ Employed □ Housewife □ Farming □ Fishing □ Trade
□ Others______
9) How much income does the family make in a month?
□ Zero to 1000 Kshs □ 1000 to 5000 Kshs □ 5000 to 10000Kshs
□ 10,000 to 20,000Kshs □ Over 20,000 Kshs
Section 3
Coverage and Maintenance of Bed Nets
10. How many people slept in the house last night?
Infant (Less than Child (1-5yrs) Child (5-18yrs) Expectant Others Total 1yr) mother
11. Do you have bed net (s) in this household? Yes No
12. If no, why? Cost Too Hot No Mosquitoes Uncomfortable to sleep under Not available in shops Others (specify)
(SINCE THERE IS NO NET, SKIP TO Q52) I would like to see each bednet you have in your household because I want to ask you questions about each. OBSERVE EACH NET WHILE YOU ASK ALL THE QUESTIONS ABOUT IT (28-51) AFTER FINISHING WITH THE FIRST NET, PLEASE MOVE TO THE SECOND NET AND ASK ALL THE QUESTIONS AGAIN, THEN THE THIRD, FOURTH, FIFTH AND SIXTH. PLEASE DO NOT READ THE OPTIONS TO THE RESPONDENT. Options Net 1 Net 2 Net 3 Net Net Net 6 4 5 13. Net hanging or in [Yes / No] position (OBSERVE) 14. Net type Permanet Safi net Olyset Super net Others 15. Net colour White (OBSERVE) Green Blue Other (specify)
16. Net Shape Round Rectangle Modified shape
17. Net fabric/Material Cotton (OBSERVE TAG) Polyester Nylon Polyethylene Other (specify) 18. How many people Infants Less slept under this net last than 1yr night? 1-5yr olds (RECORD THE 6-18yr olds NUMBERS) Expectant Mothers Others 19. In the past week, how 5-7 nights often was each net used? 3-4 nights
0-2 nights
DK 20. If the net was not used Too hot every night, why not? No mosquitoes Use coil/spray Hard to hang Forgot Get dirty quickly DK Other (specify) 21. Where did you get this PSI net from? Hospital/Clinic Duka DK
Can’t remember Other (specify)
22. When did you acquire Date this net? DK Can’t remember
23. What was the cost of Ksh this net? Free Don’t know Don’t remember
24. Have you washed this Yes net in the last month? No DK 25. How many times have NO. Of times you washed this net in DK the last 6 months? 26. Has this net ever been Yes treated with an No insecticide? DK Refused 28. When you last treated Power tab your net, what insecticide did you Others use? DK 29. Why haven‘t you -Smell treated/retreated the irritating bed net(s) (More than -Child (ren) one answer possible. If are allergic ‘other’ specify) -Insecticide is costly -Are not in the shops -Other
30. OBSERVE IF THE Yes NET HAS HOLES OR IS No TORN
31. (IF THE NET HAS Fire/Smoke HOLES OR IS TORN) Rats/Animals Why? Bed/Mat DK Old Others (Specify) 32. Have you ever mended Yes this net? No
33. If so, who mended this Myself net? Household member Neighbour Fundi Other
34. No of mending (PLEASE COUNT) 35. No. of Small Holes [ Head side Holes smaller than the Foot side old 1 Kenya Shilling Front side Coin] Back side Top 36. No. of Large Holes ( Head side Holes larger than the Foot side old 1 Kenya Shilling Front side Coin ) Back side Top
Section 4 Misuse of ITNs
37. Do you have any bed net that you do not use? Yes No______
38. If yes, how many are they? No ………………………………
Net Type Shape Materia Colour Yea Where Reason l r acquire Not used d
39. Apart from using ITNs to protect yourself from mosquito bites, are there any other uses in your homestead? Yes No Refused
40. If yes, What other uses do you know? Fishing Chicken shed Bathing shelter Wall material Wire mesh on windows Others (specify)
Can you show me other uses of nets if they are there around your house? (OBSERVE THE NETS BEING USED FOR OTHER USES AND ANSWER QUESTIONS 56-61)
Options Net 1 Net 2 Net 3 Net Net Net 6 4 5 41. Net type Permanet Safi net Olyset Supernet Cannot verify Others 42. Net colour White (OBSERVE) Green Blue Other (specify) 43. Net Shape Round Rectangle Modified shape 44. Net fabric/Material) Cotton
Polyester
Nylon Polyethylene
Others (specify)
45. When did you Date acquire this net? DK Can’t remember
Please thank the interviewee for his/her participation
Interviewer ______Signature______Date____/___/____