Viruses experience frequent small random changes in their genetic material, their genomes. Because many of the changes in the viruses that infect one animal happen independently of those that happen in another animal, one can compare the genomes of sampled viruses to glean information about how far and fast an epidemic is spreading. This is known as phylodynamics. This project will develop new mathematical and computational tools to allow us to extract more information about how a virus is moving through a population of animals from virus genomes. Specifically, recent mathematical breakthroughs allow us to understand more precisely how aspects like virus transmission, severity of disease, and duration of immunity—and differences among animals in these aspects—leave their marks on virus genomes. The project will capitalize on these developments, along with recent advances in machine learning technology and the world’s premiere database of avian influenza virus genomes, to reduce some of the key uncertainties about how this virus spills over from wild birds into domestic animals, and potentially into humans. The project is expected to benefit public health by helping us better understand how avian influenza spreads and where the greatest risk-points are by increasing the usefulness of a very common kind of data. The mathematical and computational tools developed will also be useful in other scientific and medical fields, including cancer biology and microbiology. The pro