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Early relaxation of community mitigation policies and risk of COVID-19 resurgence in the United States.
Hatef, Elham; Kitchen, Christopher; Chang, Hsien-Yen; Kharrazi, Hadi; Tang, Wenze; Weiner, Jonathan P.
  • Hatef E; Center for Population Health Information Technology, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America. Electronic address: ehatef1@jhu.edu.
  • Kitchen C; Center for Population Health Information Technology, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Chang HY; Center for Population Health Information Technology, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Kharrazi H; Center for Population Health Information Technology, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
  • Tang W; Department of Epidemiology, Harvard School of Public Health, Boston, MA, United States of America.
  • Weiner JP; Center for Population Health Information Technology, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
Prev Med ; 145: 106435, 2021 04.
Article in English | MEDLINE | ID: covidwho-1042307
ABSTRACT
This study aimed to assess the impact of coronavirus disease (COVID-19) prevalence in the United States in the week leading to the relaxation of the stay-at-home orders (SAH) on future prevalence across states that implemented different SAH policies. We used data on the number of confirmed COVID-19 cases as of August 21, 2020 on county level. We classified states into four groups based on the 7-day change in prevalence and the state's approach to SAH policy. The groups included (1) High Change (19 states; 7-day prevalence change ≥50th percentile), (2) Low Change (19 states; 7-day prevalence change <50th percentile), (3) No SAH (11 states did not adopt SAH order), and (4) No SAH End (2 states did not relax SAH order). We performed regression modeling assessing the association between change in prevalence at the time of SAH order relaxation and COVID-19 prevalence days after the relaxation of SAH order for four selected groups. After adjusting for other factors, compared to the High Change group, counties in the Low Change group had 33.8 (per 100,000 population) fewer cases (standard error (SE) 19.8, p < 0.001) 7 days after the relaxation of SAH order and the difference was larger by time passing. On August 21, 2020, the No SAH End group had 383.1 fewer cases (per 100,000 population) than the High Change group (SE 143.6, p < 0.01). A measured, evidence-based approach is required to safely relax the community mitigation strategies and practice phased-reopening of the country.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Quarantine / Public Health / Risk Assessment / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: North America Language: English Journal: Prev Med Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Quarantine / Public Health / Risk Assessment / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: North America Language: English Journal: Prev Med Year: 2021 Document Type: Article