Epidemics occur when an infection spreads through a population that has certain mixing properties as a result of social interactions and environment. The observed dynamics, which exhibits a wide variety of states depending on the disease, may be quite complex depending on the disease parameters as well as population mixing states. To address different patterns of social interactions that may occur, the classes of models being used to predict epidemic outbreaks range from compartmental models, to coupled patch models, to adaptive network models. Such models are necessary to predict natural and unnatural outbreaks. In this talk, I will review some of the basic models and ideas used to predict disease outbreaks, as well as some of the analysis methods. Dynamical predictions and control will be illustrated in both deterministic and stochastic settings. The majority of the work presented is done in collaboration with Drs. Leah Shaw and Lora Billings.
Audio (MP3 File, Podcast Ready)
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