Quanquan Gu, UCLA.
November 17, 2020. 12:45 – 1:45pm.
A Virtual Seminar on Blackboard Collaborate.
The novel coronavirus disease (COVID-19) has emerged as a global pandemic, and caused over 910,000 deaths in the world. In this talk, I will introduce our project (https://covid19.uclaml.org) using an epidemic model-guided machine learning approach to understand and forecast the spread of COVID-19 and further facilitate the decision making of the government agencies. In specific, I will introduce our UCLA-SuEIR model, which is a variant of the SEIR model and takes into account the unreported cases of COVID-19. Our model can provide forecasts of COVID-19 confirmed cases and deaths, as well as hospital/ICU bed occupancy at county, state and national level. Our forecasts are being used by the Centers for Disease Control and Prevention (CDC) and California Department of Public Health (CDPH). Various performance evaluations indicate that our model is consistently among the top three forecast models used by CDC.