The disproportionate rise in COVID-19 cases among Hispanic/Latinx in disadvantaged communities of Orange County, California: A socioeconomic case-series

  1. Daniel S. Chow
  2. Jennifer E. Soun
  3. Justin Glavis-Bloom
  4. Brent Weinberg
  5. Peter D. Chang
  6. Simukayi Mutasa
  7. Edwin Monuki
  8. Jung In Park
  9. Xiaohui Xie
  10. Daniela Bota
  11. Jie Wu
  12. Leslie Thompson
  13. Alpesh N. Amin
  14. Saahir Khan
  15. Bernadette Boden-Albala

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

Recent epidemiological evidence has demonstrated a higher rate of COVID-19 hospitalizations and deaths among minorities. This pattern of race-ethnic disparities emerging throughout the United States raises the question of what social factors may influence spread of a highly transmissible novel coronavirus. The purpose of this study is to describe race-ethnic and socioeconomic disparities associated with COVID-19 in patients in our community in Orange County, California and understand the role of individual-level factors, neighborhood-level factors, and access to care on outcomes.

Methods

This is a case-series of COVID-19 patients from the University of California, Irvine (UCI) across six-weeks between 3/12/2020 and 4/22/2020. Note, California’s shelter-in-place order began on 3/19/2020. Individual-level factors included race-ethnicity status were recorded. Neighborhood-level factors from census tracts included median household income, mean household size, proportion without a college degree, proportion working from home, and proportion without health insurance were also recorded.

Results

A total of 210-patients tested were COVID-19 positive, of which 73.3% (154/210) resided in Orange County. Hispanic/Latinx patients residing in census tracts below the median income demonstrated exponential growth (rate = 55.9%, R2 = 0.9742) during the study period. In addition, there was a significant difference for both race-ethnic (p < 0.001) and income bracket (p = 0.001) distributions prior to and after California’s shelter-in-place. In addition, the percentage of individuals residing in neighborhoods with denser households (p = 0.046), lower levels of college graduation (p < 0.001), health insurance coverage (p = 0.01), and ability to work from home (p < 0.001) significantly increased over the same timeframe.

Conclusions and Relevance

Our study examines the race-ethnic disparities in Orange County, CA, and highlights vulnerable populations that are at increased risk for contracting COVID-19. Our descriptive case series illustrates that we also need to consider socioeconomic factors, which ultimately set the stage for biological and social disparities.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.04.20090878: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Retrospective collection of patient data was approved by UCI’s Institutional Review Board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The significantly greater presence of metabolic syndrome in underserved populations11 may provide some insight into the racial-ethnic disparities in COVID-19 incidence, particularly for critical disease Limitations of this study include the small sample of patients from a single-center, so conclusions may not be broadly generalizable. However, the strengths of this study include the collection of comprehensive data, including race-ethnic and census-tract derived community determinants from all patients presenting with COVID-19 over the study period. Future studies should evaluate the complex interactions of the social determinants of income and ethnicity with other demographic, clinical, and laboratory factors. In summary, our study examines the unveiling of race-ethnic disparities over the first six weeks of COVID-19 in Orange County, CA, and highlights vulnerable populations that are at increased risk for contracting COVID-19 and experiencing disproportionately severe outcomes. While our findings that Hispanic/Latinx populations are at increased risk corroborates reports elsewhere in the United States2, this study demonstrates the increase was most dramatic in minority groups living in disadvantaged communities. When we think of race-ethnic disparities, we often investigate immediate causes of disease, including risk factors. Our descriptive case series illustrates that for COVID-19 disparities, we also need to consider the “causes of those causes,” which ultimately set the...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.05.04.20090878v1 on medRxiv