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Table 4 Impact of protests on SARS-CoV-2 infections

From: Social distancing causally impacts the spread of SARS-CoV-2: a U.S. nationwide event study

Variables

(1)

\(Post_{FP}\)

1.34 (0.21–2.47)

Males

59.63 (− 53.94 to 173.20)

Asian

− 38.81 (− 72.57 to − 5.05)

Black

− 25.94 (− 52.91 to 1.04)

Hispanic

21.11 (9.69–32.53)

White

− 32.17 (− 56.31 to − 8.04)

60-years+

5.95 (− 10.17 to 22.08)

Diabetes prevalence

− 58.78 (− 161.35 to 43.78)

Hypertension prevalence

30.15 (− 14.26 to 74.56)

Obesity prevalence

22.79 (1.56–44.01)

Smoking prevalence

− 7.93 (− 48.81 to 32.96)

ln(Population density)

0.80 (0.16–1.45)

ln(Per Capita RGDP)

− 0.02 (− 1.47 to 1.43)

Social distancing restrictions

0.29 (− 0.01 to 0.59)

Social mobility

− 1.20 (− 2.06 to − 0.34)

Constant

− 12.62 (− 77.27 to 52.03)

State fixed effects

Yes

Day fixed effects

Yes

County-days

43,387

Adjusted \(R^{2}\)

0.10

  1. This table reports results from our staggered DID regression equation (1). In this regressions, the dependent variable corresponds to the county-level number of new confirmed COVID-19 cases, per day, per 100,000 population. \(Post_{FP}\) is an indicator variable set equal to zero up until the first protest date in a protest county and to one on every subsequent date. This indicator is set to zero on all dates for the propensity score matching non-protest counties. The 95% confidence intervals reported under the regression coefficients are based on standard errors that are clustered at the county level [26]