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abstract Transmission dynamics of the malaria parasite Plasmodium falciparum have been proposed to be largely driven by immune selection to the major surface antigen of the blood stages known as erythrocyte membrane protein 1 (PfEMP1) encoded by up to 60 members of the var multigene family per haploid genome. Emerging population genetic data have revealed that the malaria transmission system is remarkably complex necessitating a much deeper molecular sampling of parasite populations and the development of computational approaches that extend previous 'strain theory' through the lens of var genetics. This project aims to define the population structure of P. falciparum in the context of var gene diversity and explore epidemiological dynamics in this framework. A team project has been created that brings together mathematical modelers, epidemiologists, entomologists, bioinformaticians, population geneticists and malaria epidemiologists from Ghana and US. Our approach combines both modeling and empirical studies to explore malaria transmission dynamics of P. falciparum at the level of local parasite populations in northern Ghana in the context of var genetics. Specific objectives are: (1) An individual-based, stochastic modeling framework that couples within and between-host transmission and describes the individual-host immunological history of exposure to different var gene repertoires to explore strain dynamics of P. falciparum in relation to age, seasonality and vector intervention. (2): For the first time in malaria epidemiology research, the longitudinal seasonal sampling of entire asymptomatic P. falciparum populations in human communities using deep 454 sequencing of var genes. (3): The quantitative description of var gene diversity and of var repertoires in wet and dry seasons, as well as across a major vector control intervention using indoor residual spraying (IRS), in comparison to microsatellite diversity. Through these objectives',-we-will address the fundamental question of strain structure despite extensive recombination and driven by immune selection, competitive interactions between parasites for hosts in the transmission dynamics. In turn, we will also ask how this structure and associated parasite diversity influence transmission dynamics.
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  • Epidemiologic
  • Modeling