Project Summary Seasonal influenza is a significant public health concern, yet it is not clear why individuals and populations differ in their protection against influenza infection. The factors underlying protection can act at multiple scales, and thus building a more complete understanding of protection requires an approach that integrates data at the population, individual, and molecular levels. What factors influence population and individual risk of influenza infection? How different are the antibody responses of individuals against influenza and what factors drive those differences? Here, I propose to identify the relative influence of past infection, vaccination, and antigenic evolution on determining both individual and population susceptibility by quantitatively modeling high-resolution epidemiological and immunological data. In particular, I aim to determine the role of past influenza infection in shaping the susceptibility of different age groups, identify the specific targets of the human antibody response against influenza, and infer the relative importance of infection history, vaccination, and epitope immunogenicity on antibody specificity. This work will have a significant impact on our ability to predict future influenza infection and allow us to target interventions toward the most at-risk populations. Success of this project requires training in advanced computational and statistical methods and state-of-the-art immunological techniques by members of the Departments of Ecology & Evolution and Medicine at the University of Chicago. This interdisciplinary and collaborative training environment will provide a strong foundation for gaining more complete understanding of the interactions between influenza and the human immune system.