Seminar Series: Leah Johnson

There are a variety of approaches to modeling and making predictions about the dynamics of infectious disease. For instance, one can take a strategic/mechanistic approach that primarily concerns itself with determining what types of processes can cause certain patterns. Strategic models often require large amounts of data to parameterize them and make them useful for prediction. On the other extreme are tactical/phenomenological models, like regressions, that usually focus on fitting a pattern without elucidating why those patterns exist. Tactical models, while often conceptually simpler, can be poor for extrapolating beyond the range of the data. Thus each approach has its strengths and weaknesses in terms of data needed to parameterize and validate the model and the types of predictions that we can make using them. I talk about the open challenge of how to use data at different resolutions with models that incorporate both mechanistic and strategic elements to improve prediction. In particular I focus on building models to prediction the dynamics of vector-borne diseases at different spatial and temporal scales using Dengue in the Americas as a case study.