February 17, 2021 from 10am-12pm (MST)

modeling and forecasting the spread of the pandemic

When COVID-19 started to spread, modelers around the world rallied to provide forecasts and longer-term scenarios to guide the public health response. The pace was fast and the methods varied. However, the types of questions faced by developers were the same as for any model, and I will start by reviewing the various decisions that guide such endeavors. I will then present our work on EpiCovDA, a minimalist model developed by former graduate student Hannah Biegel, which combines simple nonlinear dynamics with data assimilation to provide short-term forecasts. EpiCovDA's predictions contribute to the CDC ensemble model and the last part of the talk will describe the open-science forecasting community that was fostered by the CDC mathematical modeling team and its flu forecasting centers of excellence.RACT]



Dr. Joceline Lega is a Professor in Mathematics and Public Health, as well as the Associate Head of Postdoctoral Programs. She was born in France and studied at the Ecole Normale Supérieure (ENS) in Paris. After getting her MS in Physics, she decided to pursue her studies in the then burgeoning field of nonlinear dynamics and completed a post-graduate degree (Diplôme d’Etudes Approfondies) in Dynamical Systems and Turbulence at the Université de Nice. In 1989, she earned her PhD in Theoretical Physics from the University of Nice. In 1989, she was hired by CNRS (the French National Center for Scientific Research) and worked as a researcher first in the Department of Theoretical Physics at the Université de Nice and then at the Institut Non Linéaire de Nice, based in Sophia Antipolis. Between 1990 and 1997, she established various collaborations with colleagues in the Department of Mathematics at the University of Arizona, first as a postdoctoral fellow and then as a Visiting Assistant Professor. In 1997 she was hired by the University of Arizona and became a full Professor in 2006. 

See her website...