Experimental Design in Validating Models of Infectious Diseases

David M. Bortz
Department of Applied Mathematics<
University of Colorado

In the mathematical modeling of infectious diseases, it is always a challenge to construct a good model. In particular, we are interested in developing models for early infection HIV pathogenesis and Staphylococcus epiermidis bacteremia. We have proposed a methodology for systematic model selection among a set of candidate models which balances goodness-of-fit with a measure of statistical sophistication (Bortz & Nelson, Bull. of Math. Bio., 2006). Within the experimental design literature there are criteria which can dictate a sampling strategy to minimize either parameter estimate error or minimize model prediction error. Intriguingly, these criteria are directly related to a measure of the statistical complexity of the model. We will present results illustrating selection between competing models for HIV pathogenesis and Staphylococcus epiermidis bacteremia as well as how to identify an optimal sampling strategy for validated incorporation of salient immune system features into the model.

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