Timing of State and Territorial COVID-19 Stay-at-Home Orders and Changes in Population Movement — United States, March 1–May 31, 2020

Amanda Moreland, JD¹; Christine Herlihy, MS²; Michael A. Tynan³; Gregory Sunshine, JD^1,3; Russell F. McCord, JD^1,3; Charity Hilton²; Jason Poovey, MS²; Angela K. Werner, PhD³; Christopher D. Jones, PhD³; Erika B. Fulmer, MHA³; Adi V. Gundlapalli, MD, PhD³; Heather Strosnider³; Aaron Potvien, PhD²; Macarena C. García, DrPH³; Sally Honeycutt, MPH³; Grant Baldwin, PhD³; CDC Public Health Law Program; CDC COVID-19 Response Team, Mitigation Policy Analysis Unit (View author affiliations)

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Summary

What is already known about this topic?

Stay-at-home orders are a community mitigation strategy used to reduce the spread of COVID-19 in the United States.

What is added by this report?

States and territories that issued mandatory stay-at-home orders experienced decreased population movement in most counties. The period after the first state relaxed a stay-at-home order was associated with increased population movement in states or territories that had not relaxed a stay-at-home order in the same period.

What are the implications for public health practice?

Stay-at-home orders can reduce activities associated with community spread of COVID-19, including population movement and close person-to-person contact outside the household. These findings can inform future public policies to reduce community spread of COVID-19.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is thought to spread from person to person primarily by the respiratory route and mainly through close contact (1). Community mitigation strategies can lower the risk for disease transmission by limiting or preventing person-to-person interactions (2). U.S. states and territories began implementing various community mitigation policies in March 2020. One widely implemented strategy was the issuance of orders requiring persons to stay home, resulting in decreased population movement in some jurisdictions (3). Each state or territory has authority to enact its own laws and policies to protect the public’s health, and jurisdictions varied widely in the type and timing of orders issued related to stay-at-home requirements. To identify the broader impact of these stay-at-home orders, using publicly accessible, anonymized location data from mobile devices, CDC and the Georgia Tech Research Institute analyzed changes in population movement relative to stay-at-home orders issued during March 1–May 31, 2020, by all 50 states, the District of Columbia, and five U.S. territories.* During this period, 42 states and territories issued mandatory stay-at-home orders. When counties subject to mandatory state- and territory-issued stay-at-home orders were stratified along rural-urban categories, movement decreased significantly relative to the preorder baseline in all strata. Mandatory stay-at-home orders can help reduce activities associated with the spread of COVID-19, including population movement and close person-to-person contact outside the household.

Data on state and territorial stay-at-home orders were obtained from government websites containing executive or administrative orders or press releases for each jurisdiction. Each order was analyzed and coded into one of five mutually exclusive categories: 1) mandatory for all persons; 2) mandatory only for persons in certain areas of the jurisdiction; 3) mandatory only for persons at increased risk in the jurisdiction; 4) mandatory only for persons at increased risk in certain areas of the jurisdiction; or 5) advisory or recommendation (i.e., nonmandatory). Jurisdictions that did not issue an order were coded as having no state- or territory-issued order.^† These data underwent secondary review and quality assurance checks and were published in a freely available data set (4).

Publicly accessible, anonymized location data from mobile devices were obtained to estimate county-level raw data regarding movement (5). Population movement was estimated by computing the percentage of individual mobile devices (e.g., mobile phones, tablets, or watches) reporting each day that were completely at home (i.e., had not moved beyond a 150-meter radius of its common nighttime location) within a given county, using a 7-day rolling average to smooth each county’s pre- and postorder time series values. This analysis used four types of order index dates, based only on mandatory orders: 1) the start date of each state or territorial stay-at-home order for each county in that jurisdiction; 2) the relaxation or expiration date of each state or territorial stay-at-home order for each county in that jurisdiction; 3) the effective date of the first state-issued stay-at-home order (i.e., California); and 4) the first date a state-issued stay-at-home order ended (i.e., Alaska).^§

To assess changes in movement when mandatory state or territorial stay-at-home orders went into effect and ended, counties were first stratified along rural-urban categories to ensure that counties with similar population sizes were grouped together.^¶ A box plot was constructed for each rural-urban category to examine the distribution of county mean percentages of devices at home during the pre- and postorder periods associated with each index date. Because it was not assumed that movement values follow a normal distribution for all counties and periods, a clustered Wilcoxon signed rank test was then performed for each stratum, with counties as clusters, on the constituent counties’ median pre- and postorder values associated with each index date. A lower-tailed test was used for index dates related to the start of state and territorial orders, and an upper-tailed test was used for index dates related to the end of state and territorial orders** (6). Strata-level statistical significance was assessed at the 99% confidence level (α = 0.01). Analyses were performed using Python (version 3.6; Python Software Foundation) and R (version 3.5; The R Foundation). This activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy.^††

During March 1–May 31, 42 states and territories issued mandatory stay-at-home orders, affecting 2,355 (73%) of 3,233 U.S. counties (Figure 1). The first territorial order was issued by Puerto Rico (March 15), and the first state order by California (March 19). Eight jurisdictions issued only an advisory order or recommendation to stay home, and six did not issue any stay-at-home orders. Most jurisdictions issued multiple orders during the observation period, and coding varied among individual orders. The duration and termination of each order varied by jurisdiction. During the observation period, 22 jurisdictions transitioned from a mandatory order to an advisory order, 11 rescinded or allowed orders to expire without extending, and the order in one jurisdiction was ruled invalid by the state’s supreme court.^§§ The first state to rescind or allow a stay-at-home order to expire was Alaska (April 24). Eight jurisdictions had mandatory orders applicable to at least some part of the population that extended beyond May 31.

Differences in county-level mean population movement during the pre- and postorder periods varied by index date and rural-urban strata (Figure 2). Decreased median population movement was observed in 2,295 (97.6%) of the 2,351 counties for which population movement data were available. Mandatory stay-at-home orders were associated with decreased population movement (i.e., higher median percentage of devices at home) during the 28-day period after the order start date, relative to the baseline 28-day period before the order start date. This relationship was significant in all rural-urban strata (Supplementary Table, https://stacks.cdc.gov/view/cdc/92406). Among the 2,355 counties subject to mandatory stay-at-home orders, 436 (19%) had an order that expired on or before May 3, which is the latest possible expiration date that allows for a 28-day postorder observation period.^¶¶ Movement significantly increased (i.e., lower median percentage of devices at home) in the period immediately after the expiration or lifting of orders in all rural-urban strata.

The 14-day period immediately after the first state stay-at-home order was issued in the United States was associated with a significant decrease in movement in all rural-urban strata relative to the 14-day period immediately preceding its implementation.*** The period after the first state relaxed a stay-at-home order was associated with increased population movement at the strata level among states or territories that had not relaxed a stay-at-home order in the same period.^†††

Acknowledgments

Matthew Penn, Timmy Pierce, Nicholas Skaff.

FIGURE 1. Type and duration of COVID-19 state and territorial stay-at-home orders,* by jurisdiction — United States,† March 1–May 31, 2020

Abbreviations: COVID-19 = coronavirus disease 2019; CNMI = Northern Mariana Islands.

* Including the type of stay-at-home order implemented, to whom it applied, and the period for which it was in place.

^† Jurisdictions that did not issue any orders requiring or recommending persons to stay home during the observation period were not included in this figure. Jurisdictions without any orders were American Samoa, Arkansas, Connecticut, Nebraska, North Dakota, and Wyoming.

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