Monitoring and forecasting epidemic outbreaks in real-time using multiple data sources and machine learning techniques: Applications to the ongoing COVID-19 pandemic

Oct
19
2021

Monitoring and forecasting epidemic outbreaks in real-time using multiple data sources and machine learning techniques: Applications to the ongoing COVID-19 pandemic

MathBio Seminar

Mauricio Santillana from Harvard University

4:00pm - 5:00pm | Virtual

The next talk at the mathematical biology seminar will be tomorrow (Tuesday, October 19) at 4pm. Our speaker is Mauricio Santillana from Harvard University, whose talk is titled "Monitoring and forecasting epidemic outbreaks in real-time using multiple data sources and machine learning techniques: Applications to the ongoing COVID-19 pandemic". This talk will be held virtually via Zoom. Please see below for the abstract and Zoom link for tomorrow's talk.

Abstract: I will present our most recent work on the use of machine learning methods to track and forecast (endemic and emerging) epidemic outbreaks. I will present details on how we have learned from our past experiences, monitoring Influenza and Dengue, to monitor the COVID-19 pandemic in real-time. I will discuss how data sources that were not conceived originally to track population health trends --such as Google (and Baidu) searches, Twitter microblogs, weather, and anonymized data from mobile phones--can be leveraged for exactly that.

Zoom link:

https://upenn.zoom.us/j/98771561529pwd=WUdvZHd6RUN0K3grWG44RjJUb2NMUT09

Event