Racial, Ethnic, and Geographic Disparities in Novel Coronavirus (Severe Acute Respiratory Syndrome Coronavirus 2) Test Positivity in North Carolina

Nicholas A Turner; William Pan; Viviana S Martinez-Bianchi; Gabriela M Maradiaga Panayotti; Arrianna M Planey; Christopher W Woods; Paul M Lantos

doi:10.1093/ofid/ofaa413

Racial, Ethnic, and Geographic Disparities in Novel Coronavirus (Severe Acute Respiratory Syndrome Coronavirus 2) Test Positivity in North Carolina

Open Forum Infect Dis. 2020 Sep 8;8(1):ofaa413. doi: 10.1093/ofid/ofaa413. eCollection 2021 Jan.

Authors

Nicholas A Turner¹, William Pan^{2

3}, Viviana S Martinez-Bianchi¹, Gabriela M Maradiaga Panayotti¹, Arrianna M Planey⁴, Christopher W Woods^{1

2}, Paul M Lantos^{1

2}

Affiliations

¹ Duke University School of Medicine, Durham, North Carolina, USA.
² Duke Global Health Institute, Durham, North Carolina, USA.
³ Duke University Nicholas School of the Environment, Durham, North Carolina, USA.
⁴ University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, USA.

Abstract

Background: Emerging evidence suggests that black and Hispanic communities in the United States are disproportionately affected by coronavirus disease 2019 (COVID-19). A complex interplay of socioeconomic and healthcare disparities likely contribute to disproportionate COVID-19 risk.

Methods: We conducted a geospatial analysis to determine whether individual- and neighborhood-level attributes predict local odds of testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We analyzed 29 138 SARS-CoV-2 tests within the 6-county catchment area for Duke University Health System from March to June 2020. We used generalized additive models to analyze the spatial distribution of SARS-CoV-2 positivity. Adjusted models included individual-level age, gender, and race, as well as neighborhood-level Area Deprivation Index, population density, demographic composition, and household size.

Results: Our dataset included 27 099 negative and 2039 positive unique SARS-CoV-2 tests. The odds of a positive SARS-CoV-2 test were higher for males (odds ratio [OR], 1.43; 95% credible interval [CI], 1.30-1.58), blacks (OR, 1.47; 95% CI, 1.27-1.70), and Hispanics (OR, 4.25; 955 CI, 3.55-5.12). Among neighborhood-level predictors, percentage of black population (OR, 1.14; 95% CI, 1.05-1.25), and percentage Hispanic population (OR, 1.23; 95% CI, 1.07-1.41) also influenced the odds of a positive SARS-CoV-2 test. Population density, average household size, and Area Deprivation Index were not associated with SARS-CoV-2 test results after adjusting for race.

Conclusions: The odds of testing positive for SARS-CoV-2 were higher for both black and Hispanic individuals, as well as within neighborhoods with a higher proportion of black or Hispanic residents-confirming that black and Hispanic communities are disproportionately affected by SARS-CoV-2.

Keywords: Bayesian statistics; COVID-19; SARS-CoV-2; disparities; geographic information systems.