Following the Science? Examining the Issuance of Stay-At-Home Orders Related to COVID-19 by U.S. Governors

AuthorGregg R. Murray,Susan M. Murray
Published date01 March 2023
Date01 March 2023
Subject MatterArticles
American Politics Research
2023, Vol. 51(2) 147160
© The Author(s) 2022
Article reuse guidelines:
DOI: 10.1177/1532673X221106933
Following the Science? Examining the Issuance
of Stay-At-Home Orders Related to
COVID-19 by U.S. Governors
Gregg R. Murrayand Susan M. Murray
Informed by the public health policymaking literature, this studys objective is to identify scientif‌ic, political, social, economic,
and external factors related to U.S. governorsdecisions to issue stay-at-home orders (SAHOs) in response to the f‌irst wave of
the COVID-19 pandemic. Public health experts advocate for social distancing to slow the spread of infectious diseases, but
government mandates to social distance can impose substantial social and economic costs. This study uses event history analysis
to investigate the issuance of COVID-19-related gubernatorial SAHOs during a 41-day period in the 50 U.S. states. The f‌indings
indicate that scientif‌ic, political, and economic factors were associated with the issuance of SAHOs, but that external con-
siderations played the largest role, particularly those related to the timing of other governorsdecisions. This study offers
evidence about how some U.S. political leaders balance public health concerns against other considerations and, more broadly,
how state governments address crisis-level issues.
COVID-19, public health, policy diffusion, executive orders, governors
Following urgent warnings from public health experts, there
was a surge of new policies as governments around the world
took dramatic steps to limit the spread of the f‌irst wave of the
coronavirus disease 2019 (COVID-19) (Weible et al., 2020).
In an effort to force social distancing, a primary tool used to
stop the spread of infectious diseases, government authorities
in the U.S. incrementally restricted social contact starting
with prohibiting large gatherings of people, closing schools,
and limiting or closing non-essential businesses ultimately
culminating in comprehensive, statewide stay-at-home orders
(SAHOs) in a large majority of U.S. states. Though specif‌ic
restrictions vary from jurisdiction to jurisdiction, SAHOs,
which are also referred to as shelter-in-placeorders, require
people to remain in their residences except to shop for grocery
and pharmacy items, seek medical care, or work in essential
businesses. While SAHOs protect public health and safety,
they impose substantial social and economic costs on society
(e.g., Curley & Federman, 2020;Gostin & Wiley, 2020;Pew
Research Center, 2020). For instance, in the case of COVID-
19 in the U.S., basic constitutional rights such as freedom of
assembly and free exercise of religion were curtailed
(Henson, 2021). Further, over 55 million children were
prevented from attending school (Camera, 2020), more than
20 million people f‌iled initial jobless claims over a 4-week
period (J.P. Morgan, 2020), and almost 300 million
Americans, about 90% of the country, were required to
remain in their residences for several weeks (Norwood,
Given the profound effects and high-stakes nature of these
SAHOs, the objective of this study is to identify factors
related to U.S. governorsdecisions to issue a coronavirus-
related stay-at-home order or not in their states in response to
the f‌irst wave of the disease in early 2020. In particular, this
study evaluates potential public health-related scientif‌ic
factors, the primary drivers one would expect to inf‌luence
public health policy, and other potential factors related to
political, social, and economic conditions as suggested in the
public health policymaking literature (e.g., Brownson et al.,
2009;Spasoff, 1999), as well as factors external to a state that
may have affected these decisions (Berry and Berry, 1992;
Mooney & Lee., 1995). The next section of this manuscript
presents background information on the incremental policy
responses followed by pertinent literature regarding the po-
tential explanatory factors and resulting expectations. The
following section describes the event history analysis method
Augusta University, Augusta, GA, USA
Corresponding Author:
Gregg R. Murray, Augusta University, 1120 15th St, Allgood Hall N225,
Augusta, GA 30912, USA.

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