Identifying Potential Factors Associated With Racial Disparities in COVID-19 Outcomes: Retrospective Cohort Study Using Machine Learning on Real-World Data.

Journal: JMIR public health and surveillance
PMID: 39326040

Abstract

BACKGROUND: Racial disparities in COVID-19 incidence and outcomes have been widely reported. Non-Hispanic Black patients endured worse outcomes disproportionately compared with non-Hispanic White patients, but the epidemiological basis for these observations was complex and multifaceted.

Authors

  • Osama Dasa
    Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States.
  • Chen Bai
    Department of Radiology, The First Affiliated Hospital of Chengdu Medical College, The 278th Baoguang Avenue, Xindu District, Chengdu, Sichuan, 610500, People's Republic of China.
  • Ruba Sajdeya
    Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina.
  • Stephen E Kimmel
    Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, FL, USA.
  • Carl J Pepine
    Division of Cardiovascular Medicine, Department of Medicine, University of Florida College of Medicine, Gainesville, FL, USA.
  • Matthew J Gurka J
    Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA, United States.
  • Reinhard Laubenbacher
    Laboratory for Systems Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of Florida, Gainesville, FL, United States.
  • Thomas A Pearson
    Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States.
  • Mamoun T Mardini
    University of Florida, Gainesville, Florida, USA.

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