Niharika Khanna, Elena N. Klyushnenkova, Alexander Kaysin
Corresponding Author: Niharika Khanna, MD, MBBS, DGO; University of Maryland School of Medicine. Email: nkhanna@som.umaryland.edu
Section: Original Research
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Introduction: Recent data demonstrated that socioeconomic, environmental, demographic and health factors can contribute to vulnerability for COVID-19. The goal of this study was to assess association between SARS CoV-2 infection, and demographic and socioeconomic factors in patients from a large academic Family Medicine practice to support practice operations. Methods: Patients referred for SARS CoV-2 testing by practice providers were identified using shared patient lists in the Electronic Health Records (Epic). The Health Information Exchange (CRISP) was used to identify additional practice-attributed patients receiving testing elsewhere. Area Deprivation Index was derived from the Neighborhood Atlas database and linked to individual patients via (5+4) zip codes. Multivariate logistic regression modeling and Latent Class Analysis (LCA) were used to identify factors associated with COVID-19, including the combined effect of race and poverty. Results: Compared to White non-Hispanic patients, the odds of COVID-19 detection were higher in Black non-Hispanic (OR=1.75; 95% CI 1.18, 2.59, p=0.0052) and Hispanic (OR=5.40; 95% CI 3.11, 9.38, p<0.0001) patients. The LCA revealed additional patterns in health disparities. Patients living in the areas with ADI 8-10 who were predominantly Black, had higher risk for SARS CoV-2 infection compared to patients living in less socio-economically deprived areas who were predominantly White (OR=1.68; 95% CI 1.25, 2.28; p=0.0007). Conclusion: Our data provide insight into the association of COVID-19 with race/ethnic minority patients residing in highly socio-economically deprived areas. These data could impact outreach and management of ambulatory COVID-19 in the future.