Using genetic diversity to map fine-scale epidemiology in malaria (360G-Wellcome-109107_Z_15_A)

The recent evolution of artemisin-resistant strains of P.falciparum in Southeast Asia have highlighted the need for a deeper understanding of the genetic epidemiology of malaria and for more strategic implementation of malaria control resources. Assessment of the efficacy of these control efforts requires accurate and standardised estimates of epidemological parameters, such as transmission intensity. As of now, these estimates are not standarised across regions, are often labor-intensive, and work poorly in low-transmission areas. Genomics, via the sequencing of geolocated patient blood-derived parasites, has the power to provide key insights into the migration and evolution of malaria. Moreover, the rich data provided by genome sequencing represents an attractive alternative from which epidemological parameters can be calculated. To this end, my DPhil will involve the development and benchmarking of genetic epidemological models of malaria built from thousands of spatially-referenced malaria genomes collected from across Africa and Asia. These models will analysze the structure of regional genetic diversity to make estimates of parasite migration, population size and transmission intensity. Estimates will be systematically compared to field gold-standards and against simulated environments of malaria infection. The overarching goal is to guide malaria eradication policy through improved disease survelliance and control effort assessment.