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Geospatial Analysis of Individual and Community-Level Socioeconomic Factors Impacting SARS-CoV-2 Prevalence and Outcomes.
Cromer, Sara J; Lakhani, Chirag M; Wexler, Deborah J; Burnett-Bowie, Sherri-Ann M; Udler, Miriam; Patel, Chirag J.
Afiliação
  • Cromer SJ; Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114.
  • Lakhani CM; Harvard Medical School, Boston, MA 02115.
  • Wexler DJ; Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142.
  • Burnett-Bowie SM; Harvard Medical School, Boston, MA 02115.
  • Udler M; Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142.
  • Patel CJ; Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114.
medRxiv ; 2020 Sep 30.
Article em En | MEDLINE | ID: mdl-33024982
ABSTRACT

Background:

The 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

Findings:

All 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.

Conclusions:

This 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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prevalence_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prevalence_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article