Vishal Misra - April 15, 2020

Vishal Misra, PhD, "A synthetic control based analysis of COVID spread"

Dr. Misra presented on how a tool, synthetic control, can be used to model the spread of COVID-19. Synthetic control is an empirical methodology used for casual interference using observational data. He uses this tool for both counterfactual analysis (impact of interventions like lockdown, school closures etc.) as well projections of the spread. The analysis is done at the US county, US state and global level. With regard to modeling COVID-19 spread, he explained that it is important to align timelines from different regions, which is often done by tracking a region once it hits a certain threshold of deaths/cases (either at the absolute or population level) and then that threshold becomes t = 0 for all of the regions. From there, researchers can build synthetic COVID models to predict spread. Synthetic control is a promising, data way to conduct projections but selecting the “donor” data is important for the model to be accurate. His team is currently working on developing systemic ways to identify the right donor pools based on data driven techniques, intervention information, and demographics. Synthetic control/interventions may have different uses, including how to model how different economies will re-start, future needs required by hospitals, and which FDA-approved drugs may prove efficacy based on RNAseq data and historical clinical data (ongoing collaboration with MIT).