COVID Modeling: Testing Scenarios and Geographical Networks
Compartmental models for epidemiological modeling are a classic tool. In this talk I will share work we did to understand the effects of various testing strategies using a straightforward SIR model. I will also cover an extension to the typical SIR model to account for geographic heterogeneity and the incorporation of mobility data.
Natalie Sheils is a research scientist at UnitedHealth Group Research and Development. She earned her PhD in Applied Mathematics from the University of Washington in 2015 and then completed a postdoctoral fellowship at the University of Minnesota School of Mathematics. Her current research includes disease modeling and applications of healthcare data. She is involved in scientific policy and previously served on the SIAM Committee on Science Policy (2018-2019) and is now on the AMS Committee on Science Policy (2021-2024).