The global malaria burden remains high despite recent advances in malaria control efforts. The goal of this project is to develop data-driven tool to enable malaria control programs to target the malaria transmission reservoir. We will use samples from the Democratic Republic of the Congo, one of countries with the highest malaria burden in the world. Dried blood spots will be obtained a large cross-sectional study, the 2014 Demographic and Health Survey (DHS), and from a new prospective study of 1000 individuals in 4 sites with varying levels of endemicity. Gametocytemia will be measured by reverse transcriptase PCR.
Our first aim i s to map the gametocyte reservoir and determine how individual, community-level, and ecological factors determine an individual's risk for gametocyte carriage.
Our second aim i s to identify barriers and corridors of gene flow. The structure of the P. falciparum at each cluster in the DHS will be assessed using neutral microsatellites. The genetic distances between parasite subpopulations will be calculated using population genetic metrics (Rst, Gst, Nm) and used to infer corridors of, and barriers to, gene flow.
Our third aim i s to use the results from aims 1 and 2 to parameterize and improve an existing mathematical spatial model for malaria transmission. This latter model will be developed into a user-friendly freely available PC-based tool to allow the impact of targeted control to be explored in DRC and the surrounding region. This project represents a unique multidisciplinary collaboration between molecular epidemiologists, medical geographers and mathematical modelers. By incorporating results from molecular and spatial epidemiological studies into mathematical models, we hope to develop a useful and practical tool for malaria control.
Malaria represents a huge global health problem, especially in the Democratic Republic of the Congo (DRC) where 1/3 of adults may be infected. Malaria control efforts need to target the transmission reservoir, people bearing the gametocyte lifecycle stage. The aim of this proposal is to develop maps and tools to enable malaria control programs to predict how malaria spreads over space and how to target hotspots of transmission
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