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Predicting the Development of COVID-19 Epidemics from Reported Case Data

Predicting the Development of COVID-19 Epidemics from Reported Case Data

Speaker: Dr. Glenn Webb, Vanderbilt University

Abstract: Our goal is to develop mathematical models to provide predictions for COVID-19 epidemics. The models incorporate asymptomatic and symptomatic infectiousness transmission. We use reported case data to parameterize the models at the epidemic outbreak stage. The models incorporate social distancing and public health measures. The models will be applied to specific countries. We project forward in time the epidemics in these locations.

Bio: Dr. Webb received his Ph.D. from Emory University and is a Full Professor at the Department of Mathematics at Vanderbilt University. Dr. Webb has authored or co-authored over 190 papers, written one research monograph, and co-edited six volumes. He has delivered plenary lectures, colloquia, and seminars worldwide as well as being a member of 11 archival journals’ editorial boards. Since 2012, he has been a Fellow of the American Mathematical Society. His research interests are nonlinear semigroups, functional differential equations, infinite dimensional dynamical systems, mathematical population dynamics, mathematical biology, and biomedical mathematics. He employs elementary methods whenever possible, but for more complex problems, he shows a great ability to employ power abstract methods.