Title
A Bayesian SEIR Approach to Modeling Epidemics
Speaker
Vanja Dukic, University of Chicago
Abstract
Recent U.S. public policy debates regarding smallpox vaccination were largely focused on comparing mass versus trace vaccination strategies; namely, whether to vaccinate the entire population or only those who have been in contact with infected individuals. In this talk, we present a Bayesian susceptible-exposed-infected-recovered (SEIR) model and apply it to analyze a set of eight smallpox epidemics in Southwest Native American communities during 1780–81. The outcome of the model is the posterior distribution of epidemic parameters, after taking into account the population and geographical heterogeneity. We then present a comparison of the two main vaccination strategies based on the posterior predictive distribution of the fatalities under each.
Meet the speaker in Room 212 Cockins Hall at 4:30 p.m. Refreshments will be served.
