Longitudinal changes in age and race of patients with SARS-CoV-2 in a multi-hospital health system

  1. Ian J. Barbash
  2. Lee H. Harrison
  3. Jana L. Jacobs
  4. Faraaz Ali Shah
  5. Tomeka L. Suber
  6. Kevin L. Quinn
  7. Oscar C. Marroquin
  8. Mark T. Gladwin
  9. Rachel E. Sackrowitz
  10. Alison Morris

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Abstract

Background

The COVID-19 pandemic continues to affect the United States and the world. Media reports have suggested that the wave of the alpha variant in the Spring of 2021 in the US caused more cases among younger patients and racial and ethnic subgroups.

Approach

We analyzed electronic health record data from a multihospital health system to test whether younger patients accounted for more cases and more severe disease, and whether racial disparities are widening. We compared demographics, patient characteristics, and hospitalization variables for patients admitted from November 2020 through January 2021 to those admitted in March and April 2021.

Results

We analyzed data for 37, 502 unique inpatients and outpatients at 21 hospitals from November 1, 2020 to April 30, 2021. Compared to patients from November through January, those with positive tests in March and April were younger and less likely to die. Among patients under age 50, those with positive tests in March and April were three times as likely to be hospitalized and twice as likely to require ICU admission or mechanical ventilation. Individuals identified as Black represented a greater proportion of cases and hospitalizations in March and April as compared to November through January.

Conclusions

We found that relative COVID-19 hospitalization rates for younger individuals and individuals identified as Black were rising over time. These findings have important implications for ongoing public health measures to mitigate the impact of the pandemic.

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  1. ScreenIT

    SciScore for 10.1101/2021.08.16.21262016: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We also attempted SARS-CoV-2 whole genome sequencing (WGS) directly from residual endotracheal aspirate specimens from five younger patients who experienced a rapid clinical decline during admission in March and April, 2021 (6).
    WGS
    suggested: None

    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:
    An important limitation is that these racial disparities are due to the fact that reported race is just a proxy for other socioeconomic factors which mediate racial disparities in COVID-19 and were not available in our data, rather than race itself being the causal factor (10). Our findings emphasize the need for institutions to expand intentionally-designed programs promoting access to and trust in the COVID-19 vaccine in communities experiencing disproportionate effects from the pandemic (9, 11). In the absence of sustained, effective, and equitable vaccination campaigns at local, state, and national levels, we will likely see continued deaths as well as long-term morbidity among survivors in the US throughout the remainder of 2021.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.08.16.21262016 on medRxiv