Evidence map›Paper›PMID 34127982›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Ecological Analysis of the Temporal Trends in the Association of Social Vulnerability and Race/Ethnicity with County-Level COVID-19 Incidence and Outcomes in the United States.

Shabatun J Islam, Aditi Nayak, Yingtian Hu, Anurag Mehta, Katherine Dieppa, Zakaria Almuwaqqat, Yi-An Ko, Shivani A Patel, Abhinav Goyal, Samaah Sullivan and 4 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Shabatun J Islam *Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA.
Aditi Nayak *Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA.
Yingtian Hu *Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.
Anurag Mehta *Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA.
Katherine DieppaCity Operations, Getaround Incorportated, San Francisco, CA.
Zakaria AlmuwaqqatDepartment of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA.
Yi-An KoDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.
Shivani A PatelDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.
Abhinav GoyalDepartment of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA.
Samaah SullivanDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.
Tené T LewisDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.
Viola VaccarinoDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.
Alanna A MorrisDepartment of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA.
Arshed A QuyyumiDepartment of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA.

Funding

Research Trainng in Academic CardiologyT32HL007745 · NHLBI · EMORY UNIVERSITY · PI TAYLOR, WILLIAM ROBERT · 1994 to 2023
$10.6M
Multidisciplinary Research Training to Reduce Inequities in Cardiovascular HealthT32HL130025 · NHLBI · EMORY UNIVERSITY · PI Tené T Lewis, Viola Vaccarino · 2016 to 2026
$6.4M
NHLBI NIH HHS T32 HL007745NHLBI NIH HHS T32 HL130025
6 · The paper itself

Abstract

Background: The COVID-19 pandemic adversely affected the socially vulnerable and minority communities in the U.S. initially, but the temporal trends during the year-long pandemic remain unknown. Objective: We examined the temporal association between the county-level Social Vulnerability Index (SVI), a percentile-based measure of social vulnerability to disasters, its subcomponents and race/ethnic composition with COVID-19 incidence and mortality in the U.S. in the year starting in March 2020. Methods: Counties (n=3091) with ≥ 50 COVID-19 cases by March 6 Results: Higher SVI, indicative of greater social vulnerability, was independently associated with higher COVID-19 incidence (adjusted incidence rate ratio [IRR] per-10 percentile increase:1.02, (95% CI 1.02, 1.03, p<0.001), and death per capita (1.04, (95% CI 1.04, 1.05, p<0.001). SVI became an independent predictor of incidence starting from March 2020, but this association became weak or insignificant by the winter, a period that coincided with a sharp increase in infection rates and mortality, and when counties with higher proportion of White residents were disproportionately represented ("third wave"). By Spring of 2021, SVI was again a predictor of COVID-19 outcomes. Counties with greater proportion of Black residents also observed similar temporal trends COVID-19-related adverse outcomes. Counties with greater proportion of Hispanic residents had worse outcomes throughout the duration of the analysis. Conclusion: Except for the winter "third wave" when majority White communities had the highest incidence of cases, counties with greater social vulnerability and proportionately higher minority populations, experienced worse COVID-19 outcomes.

Identifiers

PMID34127982
PMCPMC8202439

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.