Evidence map›Paper›PMID 41045431›Full record

ArticleHealth care management science2025

County-level mobility and sociopolitical context in the spread of COVID-19 during spring 2020.

Chris Parker, Jorge Mejia

Abstract read
In one paragraph

Article in Health care management science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Chris Parker *Darden Graduate School of Business, University of Virginia, 100 Darden Boulevard, Charlottesville, VA, 22903, USA. ParkerC@darden.virginia.edu.ORCID https://orcid.org/0000-0003-1690-770X
Jorge Mejia *Department of Operations & Decision Technologies, Kelley School of Business, HH4100, 1309 E. 10th St., Bloomington, IN, 47405, USA.ORCID http://orcid.org/0000-0002-4479-1209

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The implementation of social distancing policies is key to reduce the spread of the recent COVID-19 pandemic and future pandemics. However, their effectiveness ultimately depends on human behavior. For example, in the United States, compliance with social distancing policies widely varied in Spring 2020. What factors were associated with the observed variability in behavioral compliance with the policies? Utilizing detailed county-level data, we estimate the association between human mobility and the growth rate of COVID-19 cases across approximately 3,100 U.S. counties from January 1, 2020 to June 20, 2020. In addition, using data from U.S. presidential elections we measured how the association between mobility and COVID-19 growth rate varied as a function of county voting pattern. Our results generalize previous reports in finding a significant association between political leaning and the COVID-19 growth rate. These results highlight how it might be beneficial to consider political orientation when building models of the multivariate relationships between the spread of pandemics and public health policies intended to curb the expansion of the pandemic.

Indexed as

COVID-19PoliticsHealth PolicyHumansPandemicsPhysical DistancingSARS-CoV-2United StatesCOVID-19EconometricsLongitudinal analysisManaging pandemicsOpen dataPanel dataSociopolitical

Identifiers

PMID41045431
PMCPMC12743688

What OpenQuestion holds

Textmetadata
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.