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Multicenter Study
. 2021 Jul;174(7):936-944.
doi: 10.7326/M20-3936. Epub 2021 Mar 30.

Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases, and Mortality in 3 U.S. Cities : An Ecological Study

Usama Bilal  1 , Loni P Tabb  1 , Sharrelle Barber  1 , Ana V Diez Roux  1
Affiliations
Multicenter Study

Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases, and Mortality in 3 U.S. Cities : An Ecological Study

Usama Bilal et al. Ann Intern Med. 2021 Jul.

Abstract

Background: Preliminary evidence has shown inequities in coronavirus disease 2019 (COVID-19)-related cases and deaths in the United States.

Objective: To explore the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York, Philadelphia, and Chicago during the first 6 months of the pandemic.

Design: Ecological, observational study at the ZIP code tabulation area (ZCTA) level from March to September 2020.

Setting: Chicago, New York, and Philadelphia.

Participants: All populated ZCTAs in the 3 cities.

Measurements: Outcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September 2020. Predictors were the Centers for Disease Control and Prevention Social Vulnerability Index and its 4 domains, obtained from the 2014-2018 American Community Survey. The spatial autocorrelation of COVID-19 outcomes was examined by using global and local Moran I statistics, and estimated associations were examined by using spatial conditional autoregressive negative binomial models.

Results: Spatial clusters of high and low positivity, confirmed cases, and mortality were found, co-located with clusters of low and high social vulnerability in the 3 cities. Evidence was also found for spatial inequities in testing, positivity, confirmed cases, and mortality. Specifically, neighborhoods with higher social vulnerability had lower testing rates and higher positivity ratios, confirmed case rates, and mortality rates.

Limitations: The ZCTAs are imperfect and heterogeneous geographic units of analysis. Surveillance data were used, which may be incomplete.

Conclusion: Spatial inequities exist in COVID-19 testing, positivity, confirmed cases, and mortality in 3 large U.S. cities.

Primary funding source: National Institutes of Health.

PubMed Disclaimer

Conflict of interest statement

Disclosures: Authors have reported no disclosures of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M20-3936.

Figures

Visual Abstract.
Visual Abstract.. Spatial Inequities in COVID-19 Variables in 3 U.S. Cities.
This study uses data from Philadelphia, Chicago, and New York City and the Centers for Disease Control and Prevention Social Vulnerability Index to explore inequities in COVID-19 testing, positivity, confirmed cases, and mortality during the first 6 months of the COVID-19 pandemic.
Figure 1.
Figure 1.. Spatial distribution and clusters of coronavirus disease 2019 testing, positivity, confirmed cases, and mortality and social vulnerability in ZIP code tabulation areas of Chicago.
Clusters were calculated by using the local Moran I statistic; clusters have a P value < 0.05. “High–high” indicates hot spots and “low–low” indicates cold spots. SVI = Social Vulnerability Index.
Figure 2.
Figure 2.. Spatial distribution and clusters of coronavirus disease 2019 testing, positivity, confirmed cases, and mortality and social vulnerability in ZIP code tabulation areas of New York.
Clusters were calculated by using the local Moran I statistic; clusters have a P value < 0.05. “High–high” indicates hot spots and “low–low” indicates cold spots. SVI = Social Vulnerability Index.
Figure 3.
Figure 3.. Spatial distribution and clusters of coronavirus disease 2019 testing, positivity, confirmed cases, and mortality and social vulnerability in ZIP code tabulation areas of Philadelphia.
Clusters were calculated by using the local Moran I statistic; clusters have a P value < 0.05. “High–high” indicates hot spots and “low–low” indicates cold spots. SVI = Social Vulnerability Index.
Figure 4.
Figure 4.. Scatter plots showing the relationship between the Social Vulnerability Index and coronavirus disease 2019 testing, positivity, confirmed cases, and mortality in ZIP code tabulation areas of Chicago, New York, and Philadelphia.
Solid lines in graph are loess smoothers. The Social Vulnerability Index has been standardized for each city, so that its units are the SD of the Social Vulnerability Index for each city separately.
See this image and copyright information in PMC

Comment in

References

    1. Dong E , Du H , Gardner L . An interactive web-based dashboard to track COVID-19 in real time [Letter]. Lancet Infect Dis. 2020;20:533-534. [PMID: ] doi:10.1016/S1473-3099(20)30120-1 - DOI - PMC - PubMed
    1. Braveman PA , Kumanyika S , Fielding J , et al. Health disparities and health equity: the issue is justice. Am J Public Health. 2011;101 Suppl 1:S149-55. [PMID: ] doi:10.2105/AJPH.2010.300062 - DOI - PMC - PubMed
    1. New York City Department of Health and Mental Hygiene. COVID-19: data. Accessed at www1.nyc.gov/site/doh/covid/covid-19-data.page on 15 December 2020.
    1. Eldeib D, Gallardo A, Johnson A, et al. The First 100. COVID-19 took black lives first. it didn't have to. ProPublica. 9 May 2020. Accessed at https://features.propublica.org/chicago-first-deaths/covid-coronavirus-t... on 18 May 2020.
    1. Philadelphia Department of Public Health. COVID-19 testing and data. Accessed at www.phila.gov/programs/coronavirus-disease-2019-covid-19/testing-and-data on 8 December 2020.

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