Human ecology of malaria in a rural Highland region of South-west Kenya [Elektronische Ressource] / vorgelegt von Sophia Wanjiku Githinji

Human ecology of malaria in a rural Highland region of South-west Kenya [Elektronische Ressource] / vorgelegt von Sophia Wanjiku Githinji

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Human Ecology of Malaria in a Rural Highland Region of South-West Kenya Dissertation zur Erlangung des Doktorgrades (Dr. rer. nat.) der Mathematisch-Naturwissenschaftlichen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn vorgelegt von Sophia Wanjiku Githinji aus Nairobi Bonn 2009 Angefertigt mit Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn 1. Gutachter: Prof. Dr. Thomas Kistemann 2. Gutachter: Prof. Dr. Paul L.G. Vlek Tag der Promotion: 30.11.2009 „…und je weiser einer ist, um so mehr wird er um seine Unwissenheit wissen. Um dieses Zieles willen habe ich die Mühe auf mich genommen, einiges wenige über die wissende Unwissenheit zu schreiben…“ Auszug aus „De docta ignorantia“ (1440) Hl. Nikolaus von Kues (1401~1464) ABSTRACT Malaria kills nearly a million people a year, uses almost half of the clinical services in Africa, and reduces economic growth by up to 1%. These numbers illustrate the immense and persistent burden of malaria, making its control one of the most important challenges in global public health. Interventions such as the use of insecticide treated nets (ITNs) for people at risk; appropriate anti-malaria drugs for people with probable or confirmed malaria and indoor residual spraying (IRS) of insecticides have been at the forefront of global efforts to control the disease.

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Human Ecology of Malaria
in a Rural Highland Region
of South-West Kenya

Dissertation
zur
Erlangung des Doktorgrades (Dr. rer. nat.)
der
Mathematisch-Naturwissenschaftlichen Fakultät
der
Rheinischen Friedrich-Wilhelms-Universität Bonn


vorgelegt von
Sophia Wanjiku Githinji
aus
Nairobi

Bonn 2009 Angefertigt mit Genehmigung der Mathematisch-Naturwissenschaftlichen
Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn






















1. Gutachter: Prof. Dr. Thomas Kistemann
2. Gutachter: Prof. Dr. Paul L.G. Vlek

Tag der Promotion: 30.11.2009 „…und je weiser einer ist, um so mehr wird er um seine Unwissenheit wissen.
Um dieses Zieles willen habe ich die Mühe auf mich genommen, einiges wenige
über die wissende Unwissenheit zu schreiben…“

Auszug aus „De docta ignorantia“ (1440) Hl. Nikolaus von Kues (1401~1464)
ABSTRACT
Malaria kills nearly a million people a year, uses almost half of the clinical
services in Africa, and reduces economic growth by up to 1%. These numbers
illustrate the immense and persistent burden of malaria, making its control one
of the most important challenges in global public health. Interventions such as
the use of insecticide treated nets (ITNs) for people at risk; appropriate anti-
malaria drugs for people with probable or confirmed malaria and indoor residual
spraying (IRS) of insecticides have been at the forefront of global efforts to
control the disease. While these measures are important, proven environmental
measures that succeeded in eradicating malaria vectors in vast parts of Europe
thand the Americas in the early 20 century and even in some parts of Africa are
largely lacking.
Malaria is considered to result from special interactions between vectors,
parasites, human beings and various environmental and anthropogenic
determinants. The present study set out to investigate the extent to which actual
malaria incidences could be related to these interactions. Specifically, the study
examined the associations of malaria incidences with micro-ecological, socio-
demographic and behavioural aspects in a rural epidemic zone in south western
Kenya.
A case-control epidemiological study design was applied. Malaria patients
seeking treatment at a rural health care facility were randomly sampled during a
peak transmission period between May and July 2007. Each case was
individually matched with a control of the same sex and approximately the same
age. Controls were drawn from patients suffering from diseases of the
respiratory system diagnosed at the facility during the same time period. In total,
342 cases and 328 controls were sampled. Home visits for both cases and
controls were done within a period of two weeks from the day of treatment at
the health facility. A standardised questionnaire investigating the social,
demographic and behavioural aspects related to malaria at the household level
was administered to each case, control or their carer. The houses and homesteads of the study subjects were spot checked for the
presence of factors which could favour mosquito breeding and their contact with
human beings. These included housing characteristics such as openings
through which mosquitoes could enter the houses, presence of stagnant water
and proximity to known breeding sites such as swamps and valley bottoms. In
addition, the survey homesteads were geo-positioned with a hand held global
positioning system and straight line distances from the study homesteads to
possible risk areas measured. Statistical analysis was done with conditional
TMlogistic regression using STATA. Spatial analysis was done with SaTscan and
ArcGIS.
Location of houses on flat swampy areas (mOR 1.81, p-value 0.03), staying
outdoors at night (mOR 1.94, p-value 0.03); presence of oxen in the compound
(mOR1.53, p-value 0.03); sleeping in a house with open eaves (mOR 1.45,
p-value 0.03) and family size greater than four people (odds ratio 1.44, p-value
0.04) were significantly associated with increased risk of malaria. On the other
hand, having sufficient food supplies throughout the year (mOR 0.60, p-value
0.003) and keeping medicine at home (mOR 0.58, p-value 0.006) were
significantly associated with reduced risk of malaria. Analysis of perceptions
showed that apart from mosquitoes, malaria was commonly associated with
environmental factors (24.7%) and nutritional deficiencies (24.5%) among other
factors. 48.2% of the respondents perceived malaria to be transmitted through
direct or indirect contacts with sick persons. Spatial analysis identified two
clusters of malaria both located on the lower parts of the study area close to a
big river.
These findings point to the need for holistic approaches that draw connections
between behavioural, socio-economic and micro-ecological factors in malaria
control. TABLE OF CONTENTS

1 GENERAL INTRODUCTION...................................................................... 1
1.1 Country background............................................................................. 3
1.2 Malaria situation in Kenya.................................................................... 5
1.3 Objectives of the study......................................................................... 9
1.4 Research questions 9
1.5 The study area..................................................................................... 9
1.6 Conceptual framework....................................................................... 14
2 METHODS................................................................................................ 19
2.1 Sampling of cases and controls ......................................................... 20
2.2 Development and testing of research tools........................................ 21
2.2.1 Training of enumerators.............................................................. 22
2.2.2 Administration of the questionnaire............................................. 24
2.3 Spot checks ....................................................................................... 26
2.3.1 Housing characteristics............................................................... 26
2.3.2 Homestead surroundings............................................................ 28
2.3.3 Bed net spot check ..................................................................... 31
2.3.4 Homestead sketching ................................................................. 32
2.3.5 GPS mapping ............................................................................. 32
2.4 Community interviews........................................................................ 33
2.4.1 Interviews with key informants.................................................... 35
2.4.2 Data mining ................................................................................ 35
2.5 Summary of data collected ................................................................ 36
2.5.1 Data entry and processing.......................................................... 36
2.5.2 Variable classification 37
2.6 Data analysis ..................................................................................... 38
2.6.1 Conditional logistic regression .................................................... 41
2.6.2 Model development .................................................................... 44
2.6.3 Spatial point pattern analysis...................................................... 47
2.6.4 Spatial clustering ........................................................................ 49
3 DESCRIPTIVE RESULTS 53
3.1 Demographic and socio-economic characteristics............................. 53
3.2 Housing characteristics...................................................................... 56
3.3 Malaria trends and climatic characteristics of the study area............. 58
4 ANALYTICAL RESULTS ......................................................................... 63
4.1 Micro-ecological risk factors............................................................... 63 4.1.1 Housing factors ........................................................................... 63
4.1.2 Elevation and slope..................................................................... 64
4.1.3 Proximity to known breeding sites............................................... 65
4.1.4 Home hygiene and vegetation..................................................... 66
4.1.5 Water collection points ................................................................ 67
4.2 Demographic and socio-economic factors ......................................... 69
4.2.1 Demographic factors................................................................... 69
4.2.2 Socio-economic factors............................................................... 73
4.3 Behavioural factors............................................................................. 74
4.3.1 Health seeking behaviour............................................................ 74
4.3.2 Accessibility to health care centre............................................... 76
4.4 Preventive measures.......................................................................... 77
4.4.1 Bed net survey and indoor residual spraying .............................. 78
4.4.2 Bed net spot check...................................................................... 79
4.4.3 Summary of variables selected ................................................... 81
4.5 Multivariate analysis........................................................................... 82
4.5.1 Model refinement ........................................................................ 84
4.5.2 Assessing interactions ................................................................ 85
4.5.3 Description of the model ............................................................. 86
4.5.4 Spatial analysis and detection of clusters ................................... 87
4.6 Perceptions of malaria 95
4.6.1 Perceptions of factors leading to occurrence of malaria.............. 95
4.6.2 Perceptions of malaria transmission and prevention................... 96
4.6.3 Perceptions gathered from community interviews....................... 97
5 DISCUSSION ............................................................................................ 99
5.1 Housing characteristics ...................................................................... 99
5.2 Elevation and slope.......................................................................... 103
5.3 Risk factors within the homestead surroundings .............................. 106
5.4 Demographic and socio-economic factors ....................................... 113
5.5 Socio-cultural factors........................................................................ 115
5.5.1 Health seeking behaviour.......................................................... 116
5.5.2 Preventive measures ................................................................ 118
5.5.3 Perceptions: do they matter? .................................................... 120
6 CONCLUSIONS...................................................................................... 123
7 GLOSSARY ............................................................................................ 127
8 REFERENCES........................................................................................ 131
9 APPENDICES ......................................................................................... 142
ACKNOWLEDGEMENTSLIST OF TABLES
Table 1.1 Health facilities in Nyamarambe division .................................... 12
Table 2.1 Most common diseases at Nduru health centre.......................... 19
Table 2.2 Classification of variables ........................................................... 37
Table 2.3 General layout of matched case -control 2 x 2 tables................. 45
Table 3.1 Demographic characteristics of the study subjects...................... 53
Table 3.2 Characteristics of study subjects by education and occupation .. 54
Table 3.3 Characteristics of survey respondents ........................................ 55
Table 3.4 Household characteristics by ownership of durable goods.......... 56
Table 3.5 Housing units owned by the survey households.......................... 58
Table 3.6 Community interviews ................................................................. 58
Table 3.7 Correlation matrix of climatic variables and malaria incidences .. 62
Table 4.1 Malaria risk by condition of house............................................... 64
Table 4.2 elevation and slope............................................. 65
Table 4.3 Malaria risk by closeness to breeding habitats ........................... 66
Table 4.4 Malaria risk by home hygiene and vegetation............................. 67
Table 4.5 Malaria risk by sources of water ................................................. 68
Table 4.6 Distance of homestead to river or stream ................................... 68
Table 4.7 Malaria risk by demographic factors and sleep patterns............. 70
Table 4.8 Comparisons of different models 72
Table 4.9 Malaria risk by socio-economic factors....................................... 73
Table 4.10 Event analysis of last sickness episode...................................... 75
Table 4.11 Distance to health care centre .................................................... 77
Table 4.12 Proximity to road and tracks ....................................................... 77
Table 4.13 Actual methods of protection against malaria ............................. 78
Table 4.14 Bed net survey and indoor residual spraying.............................. 79
Table 4.15 Characteristics of bed nets in the survey households................. 80
Table 4.16 Characteristics of specific bed nets used by cases and controls 81 Table 4.17 Summary of selected variables ...................................................82
Table 4.18 Multivariate model with all selected variables.............................. 83
Table 4.19 Preliminary main effects model 84
Table 4.20 Main effects model......................................................................85
Table 4.21 Likelihood ratio test (G) of interactions assessed........................ 85
Table 4.22 Final main effects model with one interaction.............................. 86
Table 4.23 Clusters of malaria identified with spatial scan statistics ............. 93
Table 4.24 Perceptions of causes of malaria and its seriousness................. 95
Table 4.25 Perceptions of malaria transmission ........................................... 96
Table 4.26 preventive measures 96
Table 4.27 Perceptions of symptoms............................................................ 97
Table 4.28 Ranking of malaria in the community 97
Table 4.29 Community perceptions of causes and prevention of malaria..... 98