FIGURE 3—

Relationship Between State or Federal Prison Presence and Inverse Hyperbolic Sine (IHS)-Transformed Cases or Deaths by Days Since Outbreak: United States, 2020

Note. CI = confidence interval. We use ordinary least squares regression to estimate the relationship between state or federal prison presence (using binary indicator equal to 1 if the county does have a state or federal prison) and IHS-transformed cases or deaths using a duration-equalized sample of counties a certain number of days since outbreak onset.³⁵ Column 1 indicates the number of days since outbreak onset in that county. Column 2 indicates the outcome variable of interest. The points and spikes represent the estimated effect size and 95% confidence interval, whereas the last column states these effect sizes and confidence intervals in numbers. We include state-level fixed effects to account for state policy and economic factors that may be associated with COVID-19 spread. We control for presence of a meat processor within the county, logged population, population density, urban–rural classification dummies, population share commuting by public transit, population share older than 75 years, population share living in a nursing home, average temperature February to April, logged median household income, the social capital index value, and 2018 midterm Republican vote share.