Mathematical Epidemiology

Quantifying model uncertainty in agent-based simulations for forecasting the spread of infectious diseases and understanding human behavior using social media

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  • Sara Del Valle
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Providing decision support to policy makers on consequence, mitigation, and response to the risks of infectious diseases.


We are interested in using system dynamics models to understand the spread of infectious diseases and the impact of pharmaceutical and non-pharmaceutical interventions. We have developed simple, and more structured mathematical models for various diseases including HIV, smallpox, influenza, and malaria.  Some of the mitigations we analyze include vaccines and antivirals, as well as facemasks, isolation, quarantine, and other changes in human behavior. Our goal is to understand the dynamics that influence disease spread and find optimal mitigation strategies.

Schematic showing active and less active smallpox infection

Schematic relationship between normally active (n) and less active (l) individuals for smallpox infection. The arrows represent movement of individuals from one group to and adjacent one.