[Paper Review] The effect of stay-at-home orders on COVID-19 cases and fatalities in the United States

James H. Fowler, Seth J. Hill+2 more|arXiv (Cornell University)|Apr 13, 2020

COVID-19 epidemiological studies4 citations

TL;DR

This study uses a difference-in-differences design to analyze the impact of U.S. stay-at-home orders on COVID-19 cases and fatalities at the county level. It finds that these orders were associated with a 48.6% reduction in weekly cases and a 59.8% reduction in fatalities after three weeks, preventing an estimated 390,000 cases and 41,000 deaths in the first month.

ABSTRACT

Governments issue "stay at home" orders to reduce the spread of contagious diseases, but the magnitude of such orders' effectiveness is uncertain. In the United States these orders were not coordinated at the national level during the coronavirus disease 2019 (COVID-19) pandemic, which creates an opportunity to use spatial and temporal variation to measure the policies' effect with greater accuracy. Here, we combine data on the timing of stay-at-home orders with daily confirmed COVID-19 cases and fatalities at the county level in the United States. We estimate the effect of stay-at-home orders using a difference-in-differences design that accounts for unmeasured local variation in factors like health systems and demographics and for unmeasured temporal variation in factors like national mitigation actions and access to tests. Compared to counties that did not implement stay-at-home orders, the results show that the orders are associated with a 30.2 percent (11.0 to 45.2) reduction in weekly cases after one week, a 40.0 percent (23.4 to 53.0) reduction after two weeks, and a 48.6 percent (31.1 to 61.7) reduction after three weeks. Stay-at-home orders are also associated with a 59.8 percent (18.3 to 80.2) reduction in weekly fatalities after three weeks. These results suggest that stay-at-home orders reduced confirmed cases by 390,000 (170,000 to 680,000) and fatalities by 41,000 (27,000 to 59,000) within the first three weeks in localities where they were implemented.

Motivation & Objective

• To assess the effectiveness of stay-at-home orders in reducing COVID-19 transmission and fatalities across U.S. counties.
• To isolate the causal effect of stay-at-home orders by accounting for unmeasured local and temporal confounders.
• To estimate the number of prevented cases and fatalities attributable to these orders during the early pandemic.
• To provide evidence on the public health value of non-pharmaceutical interventions during a rapidly spreading infectious disease.

Proposed method

• A difference-in-differences (DiD) model is applied to county-level data on stay-at-home order implementation, confirmed cases, and fatalities.
• The analysis controls for unmeasured county-specific factors such as demographics and healthcare infrastructure through fixed effects.
• It also accounts for unmeasured national-level temporal trends, including test availability and broader mitigation efforts.
• The model estimates the change in weekly case and fatality rates in counties that issued orders compared to those that did not.
• The DiD estimator isolates the causal effect of the policy by comparing trends before and after order implementation.
• Robustness checks include alternative model specifications and sensitivity analyses to validate the results.

Experimental results

Research questions

• RQ1 What is the causal effect of stay-at-home orders on the weekly growth rate of confirmed COVID-19 cases?
• RQ2 How do stay-at-home orders influence the trajectory of weekly fatalities in the United States?
• RQ3 To what extent do these orders reduce the total number of cases and deaths in the first three weeks of implementation?
• RQ4 How do unmeasured local and national factors affect the estimated impact of stay-at-home orders?

Key findings

• Stay-at-home orders were associated with a 30.2% reduction in weekly confirmed cases after one week, with a 95% confidence interval of 11.0% to 45.2%.
• After two weeks, the reduction in weekly cases increased to 40.0%, with a 95% confidence interval of 23.4% to 53.0%.
• By the third week, the reduction in weekly cases reached 48.6%, with a 95% confidence interval of 31.1% to 61.7%.
• The orders were linked to a 59.8% reduction in weekly fatalities after three weeks, with a 95% confidence interval of 18.3% to 80.2%.
• An estimated 390,000 cases (170,000 to 680,000) and 41,000 fatalities (27,000 to 59,000) were averted in the first three weeks in counties that implemented stay-at-home orders.
• The results suggest that stay-at-home orders had a substantial and statistically significant impact on slowing the spread and reducing mortality from COVID-19.