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Early relaxation of community mitigation policies and risk of COVID-19 resurgence in the United States.

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.

SUBMITTER: Hatef E

PROVIDER: S-EPMC7825905 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Early relaxation of community mitigation policies and risk of COVID-19 resurgence in the United States.

Hatef Elham E Kitchen Christopher C Chang Hsien-Yen HY Kharrazi Hadi H Tang Wenze W Weiner Jonathan P JP

Preventive medicine 20210122

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 ...[more]

PMID: 33486000

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Project description:BackgroundThe spread of COVID-19 has highlighted the long-standing health inequalities across the U.S. as neighborhoods with fewer resources were associated with higher rates of COVID-19 transmission. Although the stay-at-home order was one of the most effective methods to contain its spread, residents in lower-income neighborhoods faced barriers to practicing social distancing. We aimed to quantify the differential impact of stay-at-home policy on COVID-19 transmission and residents' mobility across neighborhoods of different levels of socioeconomic disadvantage.MethodsThis was a comparative interrupted time-series analysis at the county level. We included 2087 counties from 38 states which both implemented and lifted the state-wide stay-at-home order. Every county was assigned to one of four equally-sized groups based on its levels of disadvantage, represented by the Area Deprivation Index. Prevalence of COVID-19 was calculated by dividing the daily number of cumulative confirmed COVID-19 cases by the number of residents from the 2010 Census. We used the Social Distancing Index (SDI), derived from the COVID-19 Impact Analysis Platform, to measure the mobility. For the evaluation of implementation, the observation started from Mar 1st 2020 to 1 day before lifting; and, for lifting, it ranged from 1 day after implementation to Jul 5th 2020. We calculated a comparative change of daily trends in COVID-19 prevalence and Social Distancing Index between counties with three highest disadvantage levels and those with the least level before and after the implementation and lifting of the stay-at-home order, separately.ResultsOn both stay-at-home implementation and lifting dates, COVID-19 prevalence was much higher among counties with the highest or lowest disadvantage level, while mobility decreased as the disadvantage level increased. Mobility of the most disadvantaged counties was least impacted by stay-at-home implementation and relaxation compared to counties with the most resources; however, disadvantaged counties experienced the largest relative increase in COVID-19 infection after both stay-at-home implementation and relaxation.ConclusionsNeighborhoods with varying levels of socioeconomic disadvantage reacted differently to the implementation and relaxation of COVID-19 mitigation policies. Policymakers should consider investing more resources in disadvantaged counties as the pandemic may not stop until most neighborhoods have it under control.

Project description:IntroductionCommunity mitigation strategies (CMS) have demonstrated to be effective in the reduction of transmission and incidence of COVID-19, especially in the population with symptoms associated with the disease. The aim of this study was to evaluate the association between the presence of COVID-19 symptoms and adherence to CMS in Latin American adults.MethodsWe carried out a secondary analysis of a database developed by the University of Maryland and Facebook social network during the COVID-19 pandemic. We included Latin American adults that used the Facebook platform and participated in a survey conducted from April 23 to May 23, 2020. The principal outcome variable was reported compliance with the three main CMS (physical distancing, use of face masks, and hand washing). The exposure variable included symptoms suspicious for COVID-19 defined as the presence of three or more symptoms of an acute clinical case of COVID-19. We performed generalized linear models of the Poisson family with a logarithmic link function to evaluate the association between the presence of COVID-19 symptoms and reported compliance with CMS. We calculated crude and adjusted prevalence ratios (PR) with their 95% confidence intervals (95%CI).ResultsWe analyzed 1,310,690 adults from Latin America; 48.1% were male and 42.9% were under 35 years of age. The prevalence of suspicious symptoms of COVID-19 was 18.5% and reported compliance with the three CMS was 45.3%. The countries with the highest proportion of reported compliance with the three CMS were Peru, Bolivia and Panama, while those with the lowest reported compliance were Costa Rica, Nicaragua and Honduras. In the adjusted model, people with suspicious symptoms for COVID-19 had a 14% lower compliance with the three CMS (aPR = 0.86; 95%CI: 0.85-0.87; p < 0.001).ConclusionsLess than half of the participants complied with the CMS, and those presenting suspicious symptoms for COVID-19 had lower reported compliance with the three CMS.

Project description:IntroductionAlthough factors such as urbanicity, population demographics, and political affiliation have been linked with COVID-19 masking behavior and policy in community settings, little work has investigated factors associated with school mask policies. We sought to characterize United States state and school district student COVID-19 masking policies during the 2021-22 school year and determine predictors of these mandates at four time points, including before and after federal guidance relaxed school mask recommendations in February 2022.MethodsStudent mask policies for US states and the District of Columbia, as well as a sample of 56 districts were categorized as prohibited, recommended, or required in September 2021, November 2021, January 2022, and March 2022 based on the Johns Hopkins eSchool+ Initiative School Reopening Tracker. Changes in policies over time were characterized. Generalized estimating equations and logistic regression were used to evaluate whether political affiliation of governor, urbanicity, economic disadvantage, and race/ethnic composition of district students, and county-level COVID-19 incidence predicted the presence of a district mask mandate at any time point and at all four time points.ResultsState and district policies changed over time. Districts that implemented student mandates at any point were more likely to be in states with Democratic governors (AOR: 5.52; 95% CI: 2.23, 13.64) or in non-rural areas (AOR: 8.20; 95% CI: 2.63, 25.51). Districts that retained mask mandates at all four time points were more likely to have Democratic governors (AOR: 5.39; 95% CI: 2.69, 10.82) and serve a smaller proportion of economically disadvantaged students (AOR: 0.97; 95% CI: 0.95, 0.99). Districts serving a larger proportion of students from minoritized racial/ethnic groups were more likely to have mask mandates at any or all timepoints. Notably, county-level COVID-19 prevalence was not related to the presence of a mask mandate at any or all time points. By March 2022, no factors were significantly associated with district mask policy.DiscussionPolitical, geographic, and demographic characteristics predicted the likelihood of student mask mandates in the 2021-22 school year. Public health promotion messages and policy must account for variation in these factors, potentially through centralized and consistent messaging and unbiased, trustworthy communication.

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Early relaxation of community mitigation policies and risk of COVID-19 resurgence in the United States.

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Early relaxation of community mitigation policies and risk of COVID-19 resurgence in the United States.

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