Determinants of the Spatial and Temporal Distribution of Malaria in Zambia ~D Association with Vector Control
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DETERMINANTS OF THE SPATIAL AND TEMPORAL DISTRIBUTION OF MALARIA IN ZAMBIA ~D ASSOCIATION WITH VECTOR CONTROL AN ABSTRACT SUBMITTED ON THE TWENTY-FIRST DAY OF NOVEMBER OF THE YEAR 2012 TO THE DEPARTMENT OF INTERNATIONAL HEALTH AND DEVELOPMENT IN PARTIAL FULFILLMENT OF THE REQUIREMENTS OF THE SCHOOL OF PUBLIC HEALTH AND TROPICAL MEDICINE OF TULANE UNIVERSITY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY (ADAM F. BENNETT) APPROVED BY: l_ ABSTRACT Despite recent progress by control initiatives, malaria remains one of the leading causes of morbidity and mortality in southern Africa, especially among young children. A recent resurgence in malaria parasite prevalence in 201 0 in palis of central and southern Africa has highlighted the importance of research to better identify and monitor transmission foci and also to document association of programmatic efforts with changes in disease burden. This dissertation examines the determinants of the spatio-temporal distribution of malaria in children under five in Zambia and the association with vector control coverage and climate variability using several cross-sectional surveys conducted over the past six years, health management information system data (HMIS) from health facilities over the past three years, and contemporaneous remotely sensed environmental data from publically-available sources. Three primary analyses are presented: 1) Bayesian gee-statistical methods were employed to model the spatial distribution of malaria parasite prevalence in Zambia from nationaJly-representative malaria indicator surveys (MIS) conducted in 2006, 2008, and 2010, and corresponding remote sensing data, in order to evaluate the relative role of vector control coverage and climate variability in the recent resurgence in prevalence; 2) a digital elevation model and logistic regression models were constructed to determine the role of topographical wetness and dry season vegetation on risk for malaria from cross-sectional household surveys covering two districts with heterogeneous ecological characteristics in Eastern Zambia; and 3) the association of district-level vector control coverage with district-level malaria outpatient case incidence from 2009-2011 was evaluated with negative binomial and conditional autoregressive models, while controlling for climate variability. These 3 analyses provide important analytical tools for the evaluation of national malaria control programs across sub-Saharan Africa and inform targeted control strategies as the malaria community continues intervention scale-up and contemplates elimination. 4 TABLE OF CONTENTS CHAPTER! 6 1.1 Global malaria distribution 6 1.2 Goal and specific aims 7 1.3 Malaria transmission and infection 8 1.4 Malaria vectors in Africa 12 1.5 Measures of transmission 14 1.6 Malaria and climate 20 1.7 Global malaria control 28 1.8 Monitoring and evaluation 33 1.9 Spatial modeling and disease mapping 35 1.10 Study setting 38 1.11 Hypotheses and research questions 40 1.12 Data sources 43 CHAPTER2 47 2.1 Introduction 47 2.2 Methods 50 2.3 Results 57 2.4 Discussion 66 2.5 Tables and figures 72 CHAPTER3 88 3.1 Introduction 88 3.2 Methods 91 3.3 Results 96 3.4 Discussion 101 3.5 Tables and figures 105 CHAPTER4 123 4.1 Introduction 123 4.2 Methods 127 4.3 Results 132 4.4 Discussion 137 4.5 Tables and figures 139 CHAPTERS 149 5.1 Summary of findings 149 5.2Finalremarks 151 REFERENCES 153 5 CHAPTER! INTRODUCTION 1.1 Global malaria distribution Although substantial progress in control has been achieved over the past decade, malaria remains one ofthe world's largest killers of children under five, accounting for an estimated 1 million of child deaths globally and over 300 million cases per year [1]. While most dangerous for young children and pregnant women, malaria infection can . lead to dangerous and debilitating consequences in adults as well; recent estimates of the number of deaths due to malaria in adults were much larger than thought previously, with potentially as many as 435,000 deaths occmTing in 2010 [2]. Malaria is endemic in over 100 countries in the Americas, Asia, and Africa, but by far the greatest burden is in sub Saharan Africa, which accounts for an estimated 85% ofthe global malaria burden, and where the most severe illness and deaths are due primarily to Plasmodiumfalciparum infection [1]. P. falciparum endemicity is highest in the tropical belt between latitude 20° N and 20° S, which conesponds with high population densities on the African continent (Figure 1.1, next page). As a result, malaria remains one of the most bmdensome diseases in Africa, accounting for close to 20% of all child deaths on the continent and up to 50% of outpatient cases in high transmission areas [1]. While the substantial global political and financial commitment over the past 10 years has succeeded in "shrinking the malaria map" [3], recent evidence suggests that significant hurdles remain and that without consistently high levels of coverage with proven interventions, resmgence lmks as a persistent threat, especially in historically 6 high transmission areas. Determining the causes of resurgence, rationalizing continued funding through demonstration of program impact, and developing new tools for monitoring, evaluation, surveillance, and the identification of transmission foci are key priorities for malaria research as scale-up continues and elimination becomes feasible in some areas [4]. Figure 1.1 Global Plasmodiumfalciparum endemicity. malaria endemicity In 2010 'J\,. ,______ ...,• •. ooo========='":ii'ooo.._ _____ ,..,s,ooo Kitl)l'l1olrcs c:J Water Mean point estimates or the age-standardised annual mean Plasmodium !a/cipanJmpaHlsite mte In two to ten year olds (PIPfl:.,J wllhln the spatial Umlts ol stable transmission. c=J P.faicip;Jrumlree Areas ol no risk and unslable risk (PfAPI < 0.1%.) are alsO shown. ~ P/API<0.1~ Gething, P.W.", Po.til, A.P:, Smith, O.L', Guerra. CA, Byazar, I.R.F., Johnslon, G.L, Tatom, AJ. and Hay, S.l (2011). A new world malaria map: PI:Jsmodtum lalcfparum endemicity ln 2010. Malaria Joum:tl, 10: 378. BMC highly accessed article. 'indicates equ.al authorship. C2010 Malaria Atlas Project, available under the Creative Commons Atlributlon 3.0 Unportod Llccnso. 1.2 Goal and Specific Aims This dissertation presents sophisticated analytical techniques to address these priorities using several sources of programmatic, routine, remote sensing environmental, and other complementary data from Zambia covering the period of 2006 to 2010, when 7 resurgence occurred in parts of the country. A key contribution is the effort to examine the role of climate variability in changes in disease indices and to evaluate the association of vector control coverage with disease indices while controlling for these factors. Results of these analyses will provide important analytical tools for the evaluation of national malaria control programs across sub-Saharan Africa as well as inform targeted control strategies. This dissertation is structured around three specific aims, each of which represents a distinct research question and analysis: 1. To evaluate the relative effects of climate variability and intervention coverage on malaria parasite prevalence in Zambia 2. To determine the role of dry season surface wetness on the spatial distribution of malaria parasite prevalence in two districts in eastern Zambia 3. To evaluate the association of district level vector control coverage and district level confirmed outpatient malaria case incidence in Zambia while controlling for climate variability 1.3 Malaria transmission and infection An understanding of the life cycle of malaria parasite infection is foundational for describing and modeling malaria epidemiology and determining optimal control measures. Human malaria infection is caused by Plasnwdium species parasite transmitted by an Anopheles species mosquito. Four major species of Plasmodium dominate falciparum, vivax, ovalae, and malariae. P. falciparum is by far the most common in sub- 8 Saharan Africa, and is associated with the most severe form of the disease; P. vivax, which is associated with a less severe but more chronic form of the disease, predominates in Latin America and Asia. Throughout most of human history the complex life cycle of the malaria parasite has complicated control efforts, clinical management, and attempts to develop effective vaccines and maintain prophylaxis and medication regimes. The long history of human interaction with the malaria parasite is evidenced by the numerous genetic polymorphisms resulting in partial resistance to infection. It is estimated that humans and Plasmodium parasites may have coexisted for as long as the past 50,000 years [5]. Sickle cell anemia, glucose-6 phosphate dehydrogenase deficiency, and thalassemia are prominent examples of potentially deleterious genetic traits that have persisted in historically malarious zones due to selective pressure on non-cani.ers and the conference of partial protection against severe malaria infection for carrier individuals [6]. As with many infectious diseases, a lag period of several weeks exists between inoculation with Plasmodium parasites and clinical disease. Elucidating the determinants of this lag period is important for parameterizing the relationship between exposure variables and infection status. Plasmodium species parasites are transmitted to human hosts in the form of sporozoites from the saliva of feeding female Anopheles mosquitoes. Sporozoites invade human liver cells, where over a period of 5-16