The Immediate Effect of COVID-19 Policies on Social-Distancing Behavior in the United States.

Rahi Abouk,Babak Heydari

doi:10.1177/0033354920976575

Rahi Abouk, Babak Heydari

Open Access

https://doi.org/10.1177/0033354920976575

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Abstract

ObjectiveAlthough anecdotal evidence indicates the effectiveness of coronavirus disease 2019 (COVID-19) social-distancing policies, their effectiveness in relation to what is driven by public awareness and voluntary actions needs to be determined. We evaluated the effectiveness of the 6 most common social-distancing policies in the United States (statewide stay-at-home orders, limited stay-at-home orders, nonessential business closures, bans on large gatherings, school closure mandates, and limits on restaurants and bars) during the early stage of the pandemic.MethodsWe applied difference-in-differences and event-study methodologies to evaluate the effect of the 6 social-distancing policies on Google-released aggregated, anonymized daily location data on movement trends over time by state for all 50 states and the District of Columbia in 6 location categories: retail and recreation, grocery stores and pharmacies, parks, transit stations, workplaces, and residences. We compared the outcome of interest in states that adopted COVID-19–related policies with states that did not adopt such policies, before and after these policies took effect during February 15–April 25, 2020.ResultsStatewide stay-at-home orders had the strongest effect on reducing out-of-home mobility and increased the time people spent at home by an estimated 2.5 percentage points (15.2%) from before to after policies took effect. Limits on restaurants and bars ranked second and resulted in an increase in presence at home by an estimated 1.4 percentage points (8.5%). The other 4 policies did not significantly reduce mobility.ConclusionStatewide stay-at-home orders and limits on bars and restaurants were most closely linked to reduced mobility in the early stages of the COVID-19 pandemic, whereas the potential benefits of other such policies may have already been reaped from voluntary social distancing. Further research is needed to understand how the effect of social-distancing policies changes as voluntary social distancing wanes during later stages of a pandemic.

Highlights

N the absence of antiviral drugs and vaccines to contain the coronavirus disease 2019 (COVID-19) pandemic, social- distancing policies have been adopted by various affected countries.[1,2] These attempts have been made, largely, to keep the peak infection level below the resource capacity of health care systems and to buy time for possible drug and vaccine development.[3]
A decrease in the social contact rate during pandemic outbreaks is caused by a combination of voluntary actions by people and businesses driven by social awareness[4,5] and an array of nonpharmaceutical interventions (NPIs) implemented at the national, state, or local level
Social distancing played a substantial role in containing the first wave of the COVID-19 outbreak in China,[6,7] and evidence indicates the effectiveness of such policies in several European countries[8] and some US states.[9,10,11,12,13]

Summary

Methods

We applied difference-in-differences and event-study methodologies to evaluate the effect of the 6 social- distancing policies on Google-released aggregated, anonymized daily location data on movement trends over time by state for all 50 states and the District of Columbia in 6 location categories: retail and recreation, grocery stores and pharmacies, parks, transit stations, workplaces, and residences. We used publicly available Google-released aggregated, anonymized daily location data on movement trends over time by state, across 6 location categories from February 15 through April 25, 2020.18 The data illustrated how the frequency and duration of visits from several places and the length of stay changed relative to the baseline period, defined as the median value, for the corresponding day of the week, during the 5-week period January 3 through February 6, 2020. The data included mobility trends for 6 location categories: retail and recreation, grocery stores and pharmacies, parks, transit stations, workplaces, and residences.[19] Because we used de-identified, publicly available data, institutional review board review was not required. We used the dates on which policies were effective that are consistent with other published studies on the topic.[13,17,21] To control for the effect of temperature variation, humidity, and wind speed on human mobility and spread of disease, we constructed average daily temperature (in degrees Fahrenheit), humidity (in percentage), and wind speed (in miles per hour) for each state by aggregating daily data for the top 5 biggest cities in each state (supplementary material available at https://tinyurl.com/y3zyv2uj)

Results

Discussion

Conclusion