Evidence map›Paper›PMID 32889227›Full record

ArticlePublic health2020

Variation in COVID-19 outbreaks at the US state and county levels.

W Messner, S E Payson

Abstract read
In one paragraph

Article in Public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 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

2 authors.

W MessnerUniversity of South Carolina, United States. Electronic address: wolfgang.messner@moore.sc.edu.
S E PaysonUniversity of South Carolina, United States. Electronic address: spayson@email.sc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe COVID-19 pandemic poses an unprecedented threat to the health and economic prosperity of the world's population. Yet, because not all regions are affected equally, this research aims to understand whether the relative growth rate of the initial outbreak in early 2020 varied significantly between the US states and counties. STUDY

designBased on publicly available case data from across the USA, the initial outbreak is statistically modeled as an exponential curve.

methodsRegional differences are visually compared using geo maps and spaghetti lines. In addition, they are statistically analyzed as an unconditional model (one-way random effects analysis of variance estimated with HLM 7.03); the bias between state- and county-level models is evidenced with distribution tests and Bland-Altman plots (using SPSS 26).

resultsAt the state level, the outbreak rate follows a normal distribution with an average relative growth rate of 0.197 (doubling time 3.518 days). But there is a low degree of reliability between state-wide and county-specific data reported (Intraclass correlation coefficient ICC = 0.169, P < 0.001), with a bias of 0.070 (standard deviation 0.062) as shown with a Bland-Altman plot. Hence, there is a significant variation in the outbreak between the US states and counties.

conclusionsThe results emphasize the need for policy makers to look at the pandemic from the smallest population subdivision possible, so that countermeasures can be implemented, and critical resources provided effectively. Further research is needed to understand the reasons for these regional differences.

Indexed as

Data AccuracyDisease OutbreaksCoronavirus InfectionsCOVID-19GeographyHumansPandemicsPneumonia, ViralReproducibility of ResultsUnited StatesCOVID-19Novel coronavirusOutbreakPandemicRegional differences

Identifiers

PMID32889227
PMCPMC7396895

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.