This presentation will be given online by zoom, with the zoom link sent to the AMC seminar list. Participants interested in viewing should sign up for that list (see AMC Seminar website).
ABSTRACT: The outbreak of COVID-19 has increased tremendous interest in uses of mathematical models to study the spread and control of infectious diseases. Different modeling approaches have been employed to address various questions to better understand the transmission dynamics, to evaluate mitigation programs and identify optimal intervention strategies, and to forecast spatial and temporal spread of COVID-19. Several examples of these modeling approaches will be discussed.
BIO: Zhilan Feng studied mathematics at Jilin and Arizona State Universities, where she was a doctoral student of Horst Thieme. She was a post-doctoral and visiting fellow with Carlos Castillo-Chavez and Simon Levin at Cornell and Princeton Universities, respectively, before joining the faculty in the Department of Mathematics at Purdue University, where she became full professor in 2005. Her research includes mathematical modeling of ecology and epidemiology using ordinary, partial, and integro-differential equations. Many of her research projects had been partially supported by grants from NSF, CDC, James S. McDonnell Foundation, and Showalter Trust. She has supervised 15 Ph.D. students at Purdue University. She has co-authored three books and published more than 100 papers on mathematical biology and applied mathematics. She is an editor for Journal of Theoretical Biology, Mathematical Biosciences, SIAM Journal of Applied Mathematics, and Journal of Biological Dynamics. She is the chair of the Mathematical Epidemiology subgroup of the Society for Mathematical Biology. She is currently a program director in the Mathematical Biology program at the National Science Foundation.