Evidence map›Paper›PMID 32602983›Full record

ArticleThe Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association2020

Progression of COVID-19 From Urban to Rural Areas in the United States: A Spatiotemporal Analysis of Prevalence Rates.

Rajib Paul, Ahmed A Arif, Oluwaseun Adeyemi, Subhanwita Ghosh, Dan Han

Registry-linked trialAbstract read
In one paragraph

Article in The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04533360 (Seroprevalence of SARS CoV2 Antibodies Among Adults in Kingman AZ), which is not on this map. Cited by 97 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
97citing papers in PubMed, 5 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.

NCT04533360 completednot on this map

Seroprevalence of SARS CoV2 Antibodies Among Adults in Kingman AZ

Typeobservational_patient_registrySponsorKingman Regional Medical CenterRan2020 to 2021Enrolled566ConditionsCovid19ArmsVITROS Anti-SARS-CoV-2 IgG test
3 · Its place in the literature

Who cites it

97 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review.International journal of environmental research and public health · 2022
    Pooled it
  5. Pooled it
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Dimensions of Uncertainty: A spatiotemporal review of five COVID-19 datasets.Cartography and geographic information science · 2024
    Article
  15. Observational
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

37 more citing papers are in PubMed but not listed here.

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

5 authors.

Rajib PaulDepartment of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, North Carolina.ORCID 0000-0002-5120-7525
Ahmed A ArifDepartment of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, North Carolina.ORCID 0000-0002-0237-9937
Oluwaseun AdeyemiDepartment of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, North Carolina.
Subhanwita GhoshDepartment of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, North Carolina.
Dan HanDepartment of Mathematics, University of Louisville, Louisville, Kentucky.

Funding

Division of Civil, Mechanical and Manufacturing Innovation # 1537379
6 · The paper itself

Abstract

purposeThere are growing signs that the COVID-19 virus has started to spread to rural areas and can impact the rural health care system that is already stretched and lacks resources. To aid in the legislative decision process and proper channelizing of resources, we estimated and compared the county-level change in prevalence rates of COVID-19 by rural-urban status over 3 weeks. Additionally, we identified hotspots based on estimated prevalence rates.

methodsWe used crowdsourced data on COVID-19 and linked them to county-level demographics, smoking rates, and chronic diseases. We fitted a Bayesian hierarchical spatiotemporal model using the Markov Chain Monte Carlo algorithm in R-studio. We mapped the estimated prevalence rates using ArcGIS 10.8, and identified hotspots using Gettis-Ord local statistics.

findingsIn the rural counties, the mean prevalence of COVID-19 increased from 3.6 per 100,000 population to 43.6 per 100,000 within 3 weeks from April 3 to April 22, 2020. In the urban counties, the median prevalence of COVID-19 increased from 10.1 per 100,000 population to 107.6 per 100,000 within the same period. The COVID-19 adjusted prevalence rates in rural counties were substantially elevated in counties with higher black populations, smoking rates, and obesity rates. Counties with high rates of people aged 25-49 years had increased COVID-19 prevalence rates.

conclusionsOur findings show a rapid spread of COVID-19 across urban and rural areas in 21 days. Studies based on quality data are needed to explain further the role of social determinants of health on COVID-19 prevalence.

Indexed as

BetacoronavirusHealth Status DisparitiesBayes TheoremCoronavirus InfectionsCOVID-19FemaleHumansPandemicsPneumonia, ViralPopulation SurveillancePrevalencePrognosisRisk FactorsRural PopulationSARS-CoV-2United StatesBayesian influencedisease hotspotsgeographic disparitypandemicrespiratory disease

Identifiers

PMID32602983
PMCPMC7361905

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.