Title: From computational biology to disease control: insights from bacterial zoonotic diseases

Abstract: Newly emerging bacterial diseases are major threats to public and animal health. Bacteria that have long latent periods and can jump the species barrier are especially difficult to diagnose and control. Animal tuberculosis caused by Mycobacterium bovis has been recognized as a problem in many parts of the world. Infections have been found in multiple wildlife and livestock populations, as well as in humans. Recognition of the epidemiologic circumstances involved in spillover events, amplification, and spread of animal TB is essential for prioritizing surveillance and predicting future disease emergence risk. Here, I will present research to investigate ecological and evolutionary questions in the wildlife-livestock animal TB system. Using multiple data streams and a combination of statistical and mechanistic models, I will explore the main drivers enabling M. bovis persistence at the population level, as well as the impacts of cross-species transmission events on the management and control of the disease.