Wearing masks saves lives

Dr. Biplav Srivastava, professor of computer science at the University of South Carolina, and his team have developed a data-driven tool that helps demonstrate the effect of wearing masks on COVID-19 cases and deaths. His model utilizes a variety of data sources to create alternate scenarios that can tell us “What could have happened?” if a county in the U.S. had a higher or lower rate of mask adherence. In this interview, he explains how the model works, its limitations and what conclusions we can draw from it.

This is a nationwide tool which can show the effect that wearing masks can have. If it’s a county where people wear masks regularly, it will show you how many COVID-19 cases and deaths they avoided. If you pick a county where people don’t wear masks, it will show you how many cases and deaths could have been prevented there.

It is based on a mathematical technique called robust synthetic control, which is often used in drug research, where there is a control group and there is a treatment group.

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