Real-time genetic cartography of viral epidemics (360G-Wellcome-204311_Z_16_Z)

Predicting the course of an epidemic following its emergence remains one of the greatest challenges in infectious disease control. Although rapidly evolving viruses frequently threaten global public health, uneven surveillance efforts can obfuscate predictions of virus dynamics across local, regional and global scales. Genomic epidemiology is currently being revolutionized by the "real-time" sequencing of whole virus genomes in the field within days. Yet empirical datasets are often biased or hampered by limited analytical tools, potentially biasing inferences of viral dynamics and hindering predictions useful for outbreak control. To address these problems, I propose to develop a framework, termed ‘genetic cartography’, aimed at unifying the evolutionary analysis of viral genomes with medical surveillance data, high-resolution geographic measurements, and real-time human mobility data. The proposed research will deliver a statistical framework that unifies genetic, epidemiological and cartographic data in order to: 1) determine the impact of ecological and epidemiological drivers on the historical spread of RNA viruses across spatial scales, mobility networks and social groups; 2) incorporate metrics of human movement to infer present patterns of virus diversity and transmission; and 3) combine real-time genetic and mobility measures to deliver accurate future predictions of virus movement and disease burden.