The synthetic control method, introduced in Abadie and Gardeazabal (2003), has emerged as a popular empirical methodology for estimating causal effects with observational data. In this talk, we first give a background of the Synthetic Control Method, and then present our results on applying the technique for analyzing COVID-19 spread. The technique is able to both accurately predict the spread of COVID-19, as well as estimate the impact of lockdown and social distancing measures, both when they are put in place as well as when they are lifted. We also explore the question of herd immunity and our results demonstrate that the US is far away from any herd immunity effects.
Vishal Misra is a Professor in the Department of Computer Science and Electrical Engineering at Columbia University. He is an ACM and IEEE Fellow and his research emphasis is on mathematical modeling of systems, bridging the gap between practice and analysis. As a graduate student, he co-founded CricInfo, subsequently acquired by ESPN. He also played an active part in the Net Neutrality regulation process in India, where his definition of Net Neutrality was adopted both by the citizen's movement as well as the regulators. He has been awarded a Distinguished Alumnus Award by IIT Bombay (2019) and a Distinguished Young Alumnus Award by UMass-Amherst College of Engineering (2014).