Using parasite population genomics to improve understanding of malaria epidemiology

Malaria parasites carry a genetic record of their own movements and evolution, and this project will read that record across Africa and Southeast Asia to track how parasite populations change over time. Current methods for monitoring malaria rely on counting cases and testing drug resistance in individual patients, which gives a delayed and incomplete picture. The parasite population itself—its growth, spread, and genetic shifts—remains largely invisible. This project fills that gap by sequencing parasite genomes from thousands of blood samples collected repeatedly at sites with different transmission levels, then linking those genetic patterns to real-world clinical and epidemiological data. If successful, the work will produce practical tools for public health agencies. Genomic surveillance could detect the early stirrings of a drug-resistant strain or a local resurgence before case numbers rise, allowing faster, more targeted interventions. The researchers are also building statistical models that combine genetic data with spatial mapping and transmission modelling, creating a framework that could eventually be used wherever malaria is endemic. This is primarily fundamental science—establishing whether and how population genomics can be integrated into routine malaria surveillance. But the payoff is concrete: better early-warning systems for one of the world’s most persistent infectious diseases.