The Social Determinants of Health and Space-Time Clustering of COVID-19 Cases in the United States Veteran Population Open Access

Richard, Danielle (Spring 2022)

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Introduction: Disparities in COVID-19 outcomes are demonstrated globally and in the United States (U.S.). However, less is known about the spatial distribution and clustering of cases in the U.S. The U.S. Department of Veteran’s Affairs (VA) offers a comprehensive dataset with COVID-19 incidence that allows for county-level spatial analysis in conjunction with social determinants of health.

Methods: Data for 6,342,455 Veterans who utilized VA services between January 1, 2018 and September 30, 2021 were assessed for COVID-19 testing and test positivity. Analysis examined characteristics of all Veterans who received care, and by those who received at least one COVID-19 test or at least one positive COVID-19 test. Maps were produced that indicated testing and positivity rates by county. Using SaTScan software, a spatial cluster analysis was conducted over space and time to identify where and when Veterans were most at risk of COVID-19 test positivity.

Results: Of the 6,342,455 Veterans who utilized VA services during the study period, 1,352,736 (21.33%) received at least one COVID-19 test, and 275,863 (20.4%) of those tested received at least one positive COVID-19 test. Non-Hispanic Black and Hispanic Veterans were more likely to receive at least one COVID-19 test than their white counterparts, and Hispanic Veterans were more likely to receive at least one positive COVID-19 test than their non-Hispanic counterparts. County-level maps suggested that testing rates may cluster around VA facilities. Space-time cluster analysis indicated that Veterans were most at risk of testing positive between November 2020 and January 2021 in the Midwest, compared to those who received testing outside of the identified cluster (RR: 3.45, p < .001).

Discussion: Results indicate areas and time periods in the continental U.S. where Veterans were at increased risk of testing positive. Findings align with existing literature on clusters of COVID-19 cases in the general U.S. population but additional analysis is needed to understand patterns during the Delta and Omicron variant-predominant periods. These findings and methods can be extended as the pandemic progresses and in smaller geographic areas to inform VA policy and resource allocation.

Table of Contents

I.     Background

II.   Methods

A.   Study Design

B.   Study Population

C.   Data Sources

D.   Data Measures

E.    Analysis

III.  Results

IV.  Discussion

V.   References

VI.  Tables and Figures

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