Evidence map›Paper›PMID 33534870›Full record

ArticlePloS one2021

Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina.

Qian Huang, Sarah Jackson, Sahar Derakhshan, Logan Lee, Erika Pham, Amber Jackson, Susan L Cutter

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. Cited by 79 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed, 4 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.

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

79 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. What Makes Urban Communities More Resilient to COVID-19? A Systematic Review of Current Evidence.International journal of environmental research and public health · 2022
    Pooled it
  3. 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
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  15. Prediction models for COVID-19 disease outcomes.Emerging microbes & infections · 2024
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19 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

7 authors.

Qian HuangDepartment of Geography, Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, South Carolina, United States of America.ORCID 0000-0002-5502-1023
Sarah JacksonDepartment of Geography, Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, South Carolina, United States of America.
Sahar DerakhshanDepartment of Geography, Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, South Carolina, United States of America.
Logan LeeDepartment of Geography, Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, South Carolina, United States of America.
Erika PhamDepartment of Geography, Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, South Carolina, United States of America.
Amber JacksonDepartment of Geography, Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, South Carolina, United States of America.
Susan L CutterDepartment of Geography, Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, South Carolina, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the COVID-19 pandemic moved beyond the initial heavily impacted and urbanized Northeast region of the United States, hotspots of cases in other urban areas ensued across the country in early 2020. In South Carolina, the spatial and temporal patterns were different, initially concentrating in small towns within metro counties, then diffusing to centralized urban areas and rural areas. When mitigation restrictions were relaxed, hotspots reappeared in the major cities. This paper examines the county-scale spatial and temporal patterns of confirmed cases of COVID-19 for South Carolina from March 1st-September 5th, 2020. We first describe the initial diffusion of the new confirmed cases per week across the state, which remained under 2,000 cases until Memorial Day weekend (epi week 23) then dramatically increased, peaking in mid-July (epi week 29), and slowly declining thereafter. Second, we found significant differences in cases and deaths between urban and rural counties, partially related to the timing of the number of confirmed cases and deaths and the implementation of state and local mitigations. Third, we found that the case rates and mortality rates positively correlated with pre-existing social vulnerability. There was also a negative correlation between mortality rates and county resilience patterns, as expected, suggesting that counties with higher levels of inherent resilience had fewer deaths per 100,000 population.

Indexed as

Healthcare DisparitiesCOVID-19Databases, FactualHumansRural PopulationSARS-CoV-2South CarolinaSurvival AnalysisUrban Population

Identifiers

PMID33534870
PMCPMC7857563

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

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.