Identifying Potential Factors Associated With Racial Disparities in COVID-19 Outcomes: Retrospective Cohort Study Using Machine Learning on Real-World Data
The study reveals that individual and geo-socioeconomic factors significantly influence the outcomes of COVID-19. It also highlights varying risk profiles among different racial groups. While these findings suggest potential disparities, further causal inference and statistical testing are needed to fully substantiate these observations. Recognizing these relationships is vital for creating effective, tailored interventions that reduce disparities and enhance health outcomes across all racial and socioeconomic groups.
Authors
- Osama Dasa (ORCID: https://orcid.org/0000-0003-2645-8530)
- Ruba Sajdeya (ORCID: https://orcid.org/0000-0002-1101-3603)
- Matthew J. Gurka (ORCID: https://orcid.org/0000-0002-3371-4582)
- Stephen E. Kimmel (ORCID: https://orcid.org/0000-0003-3673-2361)
- Thomas A Pearson (ORCID: https://orcid.org/0000-0001-8370-0595)
- Carl J. Pepine (ORCID: https://orcid.org/0000-0002-6011-681X)
- Mamoun Mardini (ORCID: https://orcid.org/0000-0002-5345-8811)
- Reinhard Laubenbacher (ORCID: https://orcid.org/0000-0002-9143-9451)
Institutions
- University of Florida Health (US)
- University of Florida (US)
- University of Virginia (US)
Publication Details
- Journal
- JMIR Public Health and Surveillance
- Published
- 2024-09-26
- DOI
- https://doi.org/10.2196/54421
- Primary Topic
- COVID-19 and healthcare impacts
- Type
- article
- Field-Weighted Citation Impact
- 0.00