Evidence map›Paper›PMID 32543763›Full record

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

Spatial Disparities in Coronavirus Incidence and Mortality in the United States: An Ecological Analysis as of May 2020.

Charlie H Zhang, Gary G Schwartz

2 registry-linked trialsAbstract 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 2 registered trials, which are not on this map. Cited by 138 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
138citing papers in PubMed, 3 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.

NCT04472078 completednot on this map

Seroprevalence of Antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) in a Vulnerable Neighbourhood, Buenos Aries Argentina

Typeobservational_patient_registrySponsorHospital Italiano de Buenos AiresRan2020 to 2020Enrolled873ConditionsSARS-CoV-2ArmsSerological Assay or IgG for SARS-CoV-2
NCT04870307 nacompletednot on this map

Community-engaged Approaches to Testing in Community and Healthcare Settings for Underserved Populations

TypeinterventionalSponsorUniversity of OklahomaRan2020 to 2023Enrolled323ConditionsCovid19ArmsDissemination and Implementation Research
3 · Its place in the literature

Who cites it

138 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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78 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

2 authors.

Charlie H ZhangDepartment of Geography & Geosciences, University of Louisville, Louisville, Kentucky.ORCID 0000-0003-1633-2440
Gary G SchwartzDepartment of Population Health, School of Medicine & Health Sciences, University of North Dakota, Grand Forks, North Dakota.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis ecological analysis investigates the spatial patterns of the COVID-19 epidemic in the United States in relation to socioeconomic variables that characterize US counties.

methodsData on confirmed cases and deaths from COVID-19 for 2,814 US counties were obtained from Johns Hopkins University. We used Geographic Information Systems (GIS) to map the spatial aspects of this pandemic and investigate the disparities between metropolitan and nonmetropolitan communities. Multiple regression models were used to explore the contextual risk factors of infections and death across US counties. We included population density, percent of population aged 65+, percent population in poverty, percent minority population, and percent of the uninsured as independent variables. A state-level measure of the percent of the population that has been tested for COVID-19 was used to control for the impact of testing.

findingsThe impact of COVID-19 in the United States has been extremely uneven. Although densely populated large cities and their surrounding metropolitan areas are hotspots of the pandemic, it is counterintuitive that incidence and mortality rates in some small cities and nonmetropolitan counties approximate those in epicenters such as New York City. Regression analyses support the hypotheses of positive correlations between COVID-19 incidence and mortality rates and socioeconomic factors including population density, proportions of elderly residents, poverty, and percent population tested.

conclusionsKnowledge about the spatial aspects of the COVID-19 epidemic and its socioeconomic correlates can inform first responders and government efforts. Directives for social distancing and to "shelter-in-place" should continue to stem the spread of COVID-19.

Indexed as

Age FactorsBetacoronavirusCoronavirus InfectionsCOVID-19Geographic Information SystemsHumansNew York CityPandemicsPneumonia, ViralResidence CharacteristicsRisk FactorsSARS-CoV-2Socioeconomic FactorsSpatial AnalysisUnited StatesCOVID-19metropolitan areaspandemicrural or nonmetropolitanspatial disparities

Identifiers

PMID32543763
PMCPMC7323165

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.