Epidemic modeling – basics and challenges


I will review basics of epidemic modeling including eponential growth, compartmental models and self-exciting point process models. I will illustrate how such models have been used in the past for previous pandemics and what the challenges are for forecasting the current COVID-19 pandemic. I will show some examples of fitting of data to US states and what one can do with those results. Overall, model prediction has a degree of uncertainty especially with early time data and with many unknowns.

This talk is hosted by ETH-Zurich, Michigan State, TUM, UCLA, UCSD. Link to the talk site.