  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.
