Estimating the effects of race and social vulnerability on hospital admission and mortality from COVID-19

Author:

Landman Joshua M12ORCID,Steger-May Karen3,Joynt Maddox Karen E4,Hammond Gmerice4,Gupta Aditi13,Rauseo Adriana M5ORCID,Zhao Min1,Foraker Randi E16ORCID

Affiliation:

1. Institute for Informatics, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA

2. Division of Computational and Data Sciences, Washington University in St. Louis, St. Louis, Missouri, USA

3. Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA

4. Cardiovascular Division, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA

5. Division of Infectious Diseases, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA

6. Division of General Medical Sciences, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA

Abstract

Abstract Objective To estimate the risk of hospital admission and mortality from COVID-19 to patients and measure the association of race and area-level social vulnerability with those outcomes. Materials and Methods Using patient records collected at a multisite hospital system from April 2020 to October 2020, the risk of hospital admission and the risk of mortality were estimated for patients who tested positive for COVID-19 and were admitted to the hospital for COVID-19, respectively, using generalized estimating equations while controlling for patient race, patient area-level social vulnerability, and time course of the pandemic. Results Black individuals were 3.57 as likely (95% CI, 3.18–4.00) to be hospitalized than White people, and patients living in the most disadvantaged areas were 2.61 times as likely (95% CI, 2.26–3.02) to be hospitalized than those living in the least disadvantaged areas. While Black patients had lower raw mortality than White patients, mortality was similar after controlling for comorbidities and social vulnerability. Discussion Our findings point to potent correlates of race and socioeconomic status, including resource distribution, employment, and shared living spaces, that may be associated with inequitable burden of disease across patients of different races. Conclusions Public health and policy interventions should address these social factors when responding to the next pandemic.

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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