Evidence map›Paper›PMID 33947527›Full record

ArticleAmerican journal of preventive medicine2021

County-Level Socioeconomic and Political Predictors of Distancing for COVID-19.

Nolan M Kavanagh, Rishi R Goel, Atheendar S Venkataramani

Abstract read
In one paragraph

Article in American journal of preventive medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–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

13 citing papers in PubMed.

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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

3 authors.

Nolan M KavanaghPerelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: nolan.kavanagh@pennmedicine.upenn.edu.
Rishi R GoelPerelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Atheendar S VenkataramaniPerelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn response to the COVID-19 pandemic, governments have implemented social distancing measures to slow viral transmission. This work aims to determine the extent to which socioeconomic and political conditions have shaped community-level distancing behaviors during the COVID-19 pandemic, especially how these dynamics have evolved over time.

methodsThis study used daily data on physical distancing from 15‒17 million cell phone users in 3,037 U.S. counties. County-level changes in the average distance traveled per person were estimated relative to prepandemic weeks as a proxy for physical distancing. Pooled ordinary least squares regressions estimated the association between physical distancing and a variety of county-level demographic, socioeconomic, and political characteristics by week from March 9, 2020 to January 17, 2021. Data were collected until January 2021, at which point the analyses were finalized.

resultsLower per capita income and greater Republican orientation were associated with significantly reduced physical distancing throughout nearly all the study period. These associations persisted after adjusting for a variety of county-level demographic and socioeconomic characteristics. Other county-level characteristics, such as the shares of Black and Hispanic residents, were associated with reduced distancing at various points during the study period.

conclusionsThese results highlight the importance of dynamic socioeconomic and political gradients in preventive behavior and imply the need for nimble policy responses.

Indexed as

COVID-19HumansPandemicsPhysical DistancingSARS-CoV-2Socioeconomic Factors

Identifiers

PMID33947527
PMCPMC7988444

What OpenQuestion holds

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Registered trials

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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.