Computational Epidemiology: Challenges and Opportunities

Speaker: Madhav Marathe

Abstract

Infectious diseases cause more than 13 million deaths a year worldwide. Globalization, urbanization, climate change, and ecological pressures increase the risk and impact of future pandemics. The ongoing COVID-19 pandemic has exemplified several of these issues. The social, economic, and health impact of the pandemic has been immense and will continue to be felt for decades to come. India is currently experiencing an unprecedented second wave that has claimed thousands of precious lives. The talk will give an overview of the state of the art in real-time computational epidemiology. Then using COVID-19 as an exemplar, we will describe how scalable computing, AI and data science can play an important role in advancing real-time epidemic science. Computational challenges and directions for future research will be discussed.

Bio

Madhav Marathe is a Distinguished Professor in Biocomplexity, the division director of the Network Systems Science and Advanced Computing Division at the Biocomplexity Institute and Initiative, and a Professor in the Department of Computer Science at the University of Virginia (UVA). His research interests are in network science, computational epidemiology, AI, foundations of computing and high performance computing. Over the last 20 years, his division has supported federal and state authorities in their effort to combat epidemics in real-time, including the H1N1 pandemic in 2009, the Ebola outbreak in 2014 and most recently the COVID-19 pandemic. Before joining UVA, he held positions at Virginia Tech and the Los Alamos National Laboratory. He is a Fellow of the IEEE, ACM, SIAM and AAAS.