Real-time Data Fusion for Disease Forecasting Models

Abstract: The COVID-19 pandemic highlighted the need for non-traditional data analysis techniques and data sources to understand the emergence of a deadly, novel virus. In this talk, I will discuss how our team is using mathematical, statistical, and computational models as well as heterogeneous data streams (e.g., social media, weather, mobility information, and satellite imagery) to model and forecast the spread of infectious diseases including influenza, COVID-19, and dengue. In addition, I will demonstrate the role that mathematics and data science has played in responding to the COVID-19 pandemic and challenges that remain to model current and future pandemics.

Mathematics

Audience: general audience

VCU Mathematics and Applied Mathematics Colloquium Series

Series comments: A series of public lectures in Mathematics and Applied Mathematics from Virginia Commonwealth University.

To attend virtually, please connect via Zoom using the following coordinates:

Zoom Meeting ID: 822 7853 4531 Password: VCUMATH101