Evidence map›Paper›PMID 34731173›Full record

ArticlePloS one2021

Modeling the differences in the time-series profiles of new COVID-19 daily confirmed cases in 3,108 contiguous U.S. counties: A retrospective analysis.

Fadel M Megahed, L Allison Jones-Farmer, Longwen Zhao, Steven E Rigdon

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Fadel M MegahedFarmer School of Business, Miami University, Oxford, OH, United States of America.ORCID 0000-0003-2194-5110
L Allison Jones-FarmerFarmer School of Business, Miami University, Oxford, OH, United States of America.
Longwen ZhaoCollege for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, United States of America.
Steven E RigdonCollege for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, United States of America.ORCID 0000-0001-7668-0899

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe COVID-19 pandemic in the U.S. has exhibited a distinct multiwave pattern beginning in March 2020. Paradoxically, most counties do not exhibit this same multiwave pattern. We aim to answer three research questions: (1) How many distinct clusters of counties exhibit similar COVID-19 patterns in the time-series of daily confirmed cases? (2) What is the geographic distribution of the counties within each cluster? and (3) Are county-level demographic, socioeconomic and political variables associated with the COVID-19 case patterns? MATERIALS AND

methodsWe analyzed data from counties in the U.S. from March 1, 2020 to January 2, 2021. Time series clustering identified clusters in the daily confirmed cases of COVID-19. An explanatory model was used to identify demographic, socioeconomic and political variables associated with the outbreak patterns.

resultsThree patterns were identified from the cluster solution including counties in which cases are still increasing, those that peaked in the late fall, and those with low case counts to date. Several county-level demographic, socioeconomic, and political variables showed significant associations with the identified clusters. DISCUSSION: The pattern of the outbreak is related both to the geographic location within the U.S. and several variables including population density and government response.

conclusionThe reported pattern of cases in the U.S. is observed through aggregation of the daily confirmed COVID-19 cases, suggesting that local trends may be more informative. The pattern of the outbreak varies by county, and is associated with important demographic, socioeconomic, political and geographic factors.

Indexed as

Cluster AnalysisCOVID-19HumansModels, BiologicalRetrospective StudiesTime and Motion StudiesUnited States

Identifiers

PMID34731173
PMCPMC8565782

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