Study population and setting
The objective of the study was to determine the impact of stay-at-home and shelter-in-place ordinances on COVID-19 transmission in the United States. The authors estimated the rate of new COVID-19 infections at the county level from March 1 to April 16, 2020, specifying in a model infectivity, susceptibility, and recovery as parameters, and then modeling outcomes as a function of time and the existence of stay-at-home orders. To estimate the effectiveness of stay-at-home or shelter-in-place ordinances on COVID-19 epidemic growth, the authors compared daily county-level trends in COVID-19 incidence before and after these policies were announced in each municipality.
Summary of Main Findings
Implementation of stay-at-home and shelter-in-place policies were estimated to have exponentially reduced COVID-19 infections over time, from a mean incidence reduction of 3.9% one week after implementation (95% CI: 1.2 – 6.6%) to a 22.6% mean reduction 27 days after implementation (95% CI: 14.8 – 30.5%) corresponding to a net decline in new cases. The initial announcement of these policies (as early as March 16, 2020) preceded estimated peak COVID-19 incidence across municipalities. Applying the effect estimates to the entire United States under the counterfactual scenario in which every county issued stay-at-home orders on March 16, 2020 (the day a national emergency was declared), translated into a 63.2% decrease in cases.
The authors aggregated stay-at-home and shelter-in-place ordinances at various ecological scales (e.g., state and municipal) to estimate impact of these policies on COVID-19 transmission at a national scale. The authors also accounted for heterogeneity in county characteristics and the timing of shelter-in-place ordinance announcements. The authors recognize some of the challenges in doing causal inference in these longitudinal state-level settings with varying treatment start dates, and do reasonable model checks regarding some of those issues, including inspecting trends in the pre-period.
Stay-at-home and shelter-in-place ordinances were often accompanied by other policies designed to enforce physical distancing (e.g., school and business closures, mass gathering prohibitions), limiting inferences about their independent effects. The epidemiological model used to estimate COVID-19 transmission, while derived from empirical estimates of confirmed COVID-19 cases in the United States, may underestimate true transmission patterns (given shortages in testing capacity in the U.S.), resulting in misleading inferences about the impact of these policies on COVID-19 transmission. There is limited discussion of the selection factors involved, i.e., why some counties implemented this measure and how they may differ from those that did not.
This is among the first studies to apply causal inference methods to estimate impact of stay-at-home and shelter-in-place orders on COVID-19 transmission in the United States.