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Geospatial Analysis of Individual and Community-Level Socioeconomic Factors Impacting SARS-CoV-2 Prevalence and Outcomes
Sara J Cromer; Chirag M Lakhani; Deborah J Wexler; Sherri-Ann M Burnett-Bowie; Miriam Udler; Chirag J Patel.
Affiliation
  • Sara J Cromer; Massachusetts General Hospital
  • Chirag M Lakhani; Harvard Medical School
  • Deborah J Wexler; Massachusetts General Hospital
  • Sherri-Ann M Burnett-Bowie; Massachusetts General Hospital
  • Miriam Udler; Massachusetts General Hospital
  • Chirag J Patel; Harvard Medical School
Preprint in En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20201830
Journal article
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ABSTRACT
BackgroundThe SARS-CoV-2 pandemic has disproportionately affected racial and ethnic minority communities across the United States. We sought to disentangle individual and census tract-level sociodemographic and economic factors associated with these disparities. Methods and FindingsAll adults tested for SARS-CoV-2 between February 1 and June 21, 2020 were geocoded to a census tract based on their address; hospital employees and individuals with invalid addresses were excluded. Individual (age, sex, race/ethnicity, preferred language, insurance) and census tract-level (demographics, insurance, income, education, employment, occupation, household crowding and occupancy, built home environment, and transportation) variables were analyzed using linear mixed models predicting infection, hospitalization, and death from SARS-CoV-2. Among 57,865 individuals, per capita testing rates, individual (older age, male sex, non-White race, non-English preferred language, and non-private insurance), and census tract-level (increased population density, higher household occupancy, and lower education) measures were associated with likelihood of infection. Among those infected, individual age, sex, race, language, and insurance, and census tract-level measures of lower education, more multi-family homes, and extreme household crowding were associated with increased likelihood of hospitalization, while higher per capita testing rates were associated with decreased likelihood. Only individual-level variables (older age, male sex, Medicare insurance) were associated with increased mortality among those hospitalized. ConclusionsThis study of the first wave of the SARS-CoV-2 pandemic in a major U.S. city presents the cascade of outcomes following SARS-CoV-2 infection within a large, multi-ethnic cohort. SARS-CoV-2 infection and hospitalization rates, but not death rates among those hospitalized, are related to census tract-level socioeconomic characteristics including lower educational attainment and higher household crowding and occupancy, but not neighborhood measures of race, independent of individual factors.
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Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Cohort_studies / Experimental_studies / Observational_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Cohort_studies / Experimental_studies / Observational_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint