Evidence map›Paper›PMID 34126964›Full record

ArticleBMC public health2021

Differential impact of mitigation policies and socioeconomic status on COVID-19 prevalence and social distancing in the United States.

Hsien-Yen Chang, Wenze Tang, Elham Hatef, Christopher Kitchen, Jonathan P Weiner, Hadi Kharrazi

Abstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Measures implemented in the school setting to contain the COVID-19 pandemic.The Cochrane database of systematic reviews · 2024
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  10. Combating coronavirus disease (COVID-19) in rural areas of Malawi: Factors affecting the fight.African journal of primary health care & family medicine · 2023
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  17. Sleep of infants and toddlers during 12 months of the COVID-19 pandemic in the midwestern United States.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hsien-Yen Chang *Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. hchang24@jhmi.edu.ORCID 0000-0002-7997-4822
Wenze Tang *Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Elham HatefDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Christopher KitchenDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Jonathan P WeinerDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Hadi KharraziDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19HumansPhysical DistancingPolicyPrevalenceSARS-CoV-2Social ClassUnited StatesArea deprivation indexComparative interrupted time-series analysisCOVID-19 policyCOVID-19 prevalenceSocial determinants of healthSocial distancing indexStay-at-home order

Identifiers

PMID34126964
PMCPMC8201431

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.