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Project

Eco epidemiology of asymptomatic malaria hotspots, a prerequisite for malaria elimination? (MalaSpot)

Investment in malaria elimination is believed to provide one of the highest returns in global health. Elimination however requires a different approach as compared to what is done in present control programs. New insights in the eco-epidemiology of the malaria parasites will be essential in defining this approach, especially for Plasmodium vivax of which current knowledge is relatively poor. In the proposed research program we seek to identify and characterize malaria hotspots that are stable in time at different geographical resolutions for each of the four human malaria parasites (P. falciparum, P. vivax, P. malariae, and P. ovale), with the aim of enabling hotspot targeting for malaria elimination. It is based on the hypothesis that stable hotspots, in which the human reservoir of the parasite consists of mainly asymptomatic cases, 1) feed the temporary (unstable) hotspots in which otherwise the parasite will not persist, and 2) possess a unique combination of host, vector and environmental conditions which determine its stability over time.

In a first phase, a unique dataset, previously collected in a project carried out in the most endemic province of Cambodia, will be used to determine stable and unstable hotspots or cold spots at a village resolution. This dataset consists of malaria prevalence (113 villages, 4 surveys, 2 years, >20,000 individuals sampled) and incidence data of symptomatic and asymptomatic cases (PCR, serology & passive case detection) at the village level. In addition, the hotspot information obtained will be linked using spatio-temporal models with human-, parasite-, vector- andenvironment- related factors, all collected in the same time period. In a second phase we will zoom in to a subvillage resolution to refine the analysis by collecting additional data in identified hotspots at individual and household level, as such defining the scale at which risk factors for asymptomatic malaria hotspots occur (individual – household – village – cluster of villages). The relation between the type of hotspot (stable, unstable or cold) defined geographically, and occurrence of symptomatic cases will further be explored. As such, focussing classical epidemiology on asymptomatic instead of symptomatic malaria cases and combining it with environmental, entomological and social science data will provide a novel and useful approach to predict the locality and dynamics of malaria hotspots for each of the four parasite species.We thus expect that this study, unparalleled in available data and combined disciplines, will provide fundamental insights for hotspot targeting, a prerequisite for efficient malaria elimination in many countries.

Date:1 Nov 2014 →  31 Dec 2018
Project type:PhD project