The coronavirus pandemic has led to a collapse of the labor market and a massive increase in unemployment. In addition to losing their jobs, millions of Americans have also lost their health insurance. Existing studies have estimated health insurance losses based on models and assumptions about the relationship between employer-sponsored insurance (ESI) and unemployment rates. In this grant, Paul Fronstin and Stephen Woodbury will construct estimates from unemployment claims data on the characteristics of workers who have lost their jobs since the start of the pandemic including industry, gender, age, and race/ethnicity. The claims data will be combined with data on what is known about worker characteristics and the likelihood of having job-based benefits. Industry-specific estimates will generate more accurate estimates of ESI losses because certain industries, such as food service and hospitality, may have been affected far more severely than others. Furthermore, because their study will produce estimates of ESI loss across demographic and industry groups, the estimates will add to the understanding of the disparate impacts of the pandemic recession on various groups of workers.