God is in the Rain: The Impact of Rainfall-Induced Early Social Distancing on COVID-19 Outbreaks

Impacts of State Reopening Policy on Human Mobility

“…There are several differences between these existing studies on the largest determinants of mobility slowdowns experienced from early March to early April, and the literature has not fully resolved reasons for differences in conclusions. Studies also emphasize the importance of political variables in understanding mobility responses; the role of weather as an instrument for mobility holds promise in newly emerging research (Kapoor et al, 2020).…”

“…News reports from Georgia indicate that there were lines of people waiting to get hair cuts after the state allowed hair salons to reopen (Stevens, 2020), complete with visible indicators of pent-up demand due to unkempt hair or fading hair dye. Because these reopenings occur in late spring, the warmer weather may discourage social distancing (Kapoor et al, 2020). It is also likely that individuals will engage in less social distancing after a reopening if they fail to take account of the infection externality that they impose on others (Bethune and Korinek, 2020).…”

Understanding Spatial Variation in COVID-19 across the United States

“…show that countries with stricter policies to limit social contact had later and less pronounced disease peaks. Dave et al (2020) adopt an event study approach finding large effects especially among early adopters and dense locations Kapoor et al (2020). use rainfall shocks to identify the effect of staying at home, finding that social distancing has a persistent negative effect on cases and deaths across US counties.…”

Divided We Stay Home: Social Distancing and Ethnic Diversity

“…To put our estimates in a perspective, we produce a back-of-the-envelope calculation of how many lives might have been saved by a stronger social distancing response in communities with higher levels of diversity. For our calculations, we rely on two estimates of the effect of social distancing on the eventual number of COVID-19 deaths: one coming from a mainstream epidemiological model by Walker et al (2020) and one from the local average treatment effect estimated by Kapoor et al (2020) based on a rainfall IV strategy. We consider the elasticity produced by Walker et al 2020as an upper bound, as they take into account all potential future deaths from the disease that evolves according to their model.…”

“…We consider the elasticity produced by Walker et al 2020as an upper bound, as they take into account all potential future deaths from the disease that evolves according to their model. In contrast, we consider the elasticities in Kapoor et al (2020) as the lower bound, as they study a temporary reduction in social distancing on one particular weekend and because they only take into account data available by the time of writing that article. Based on these two studies, we calculate that a one standard deviation increase in ethnic fractionalization is associated with a range from 570 to 22,250 fewer deaths in Russia and from 2,000 to 40,000 fewer deaths in the United States.…”