Differential Effects of Race/Ethnicity and Social Vulnerability on COVID-19 Positivity, Hospitalization, and Death in the San Francisco Bay Area

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Abstract

No abstract available

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  1. SciScore for 10.1101/2022.01.04.22268760: (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

    Experimental Models: Organisms/Strains
    SentencesResources
    Racial/ethnic identification was made based on patient self-reporting as non-Hispanic Black (hereafter, Black), non-Hispanic White (hereafter, White), non-Hispanic Asian (hereafter Asian), and Hispanic or Latino (hereafter Hispanic).
    non-Hispanic White
    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:
    Study Limitations: Our study conclusions are specific to a vaccine-naive patient population that sought care at UCSF Health in 2020 and may not be generalizable to populations in other settings or at later time points in the pandemic. Furthermore, our study population differed somewhat in racial and ethnic composition from that of the Bay Area population. The reasons for this discrepancy could have reflected the region’s geographic heterogeneity in the distribution of Asian individuals, as well as other factors, including but not limited to variations in patient access to or preference for UCSF Health care facilities, patient willingness to seek medical care, health insurance coverage-dictated limitations, and referral effects. Patients who lived a distance from a UCSF Health facility may have been less likely to seek care at UCSF Health and thus would been less likely to be included in the study population. For example, Santa Clara County, the most populous in the nine-county Bay Area, lies beyond the immediate referral zone of UCSF Health yet has highest percentage of Asian individuals (38.9%) in the region. Furthermore, it is conceivable that any such distance-related access barriers would have been more difficult to overcome for individuals with higher social vulnerability and lower socioeconomic status. At the same time, amongst large, regional health care systems in the San Francisco Bay Area during the study period, UCSF Health cared for a disproportionately greater sh...

    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.