Infectious diseases, which are caused by organisms such as bacteria, viruses, fungi, or parasites, have plagued populations since time immemorial. Infectious disease modeling describes a subdiscipline of mathematics and statistics where models are developed to study the mechanisms of disease spread. These models can help predict disease behavior in a population (e.g. will the disease become an epidemic or will it die out), and evaluate control strategies. Such models can be either deterministic or stochastic in nature. Compartmental models comprise one class of models used to understand infectious diseases. These models simplify an infection process by grouping infection states of a pathogen into "compartments" and assume that individuals (1) in the same compartment behave the same and (2) move through the compartments in a particular order. One example of an epidemic compartmental model is the Susceptible, Infectious, Removed (SIR) model. I specialize in Bayesian epidemic compartmental models for neglected tropical diseases, as defined by the World Health Organization.
My dissertation work was featured in the University of Iowa Dare to Discover campaign.