Does Gender or Religion Contribute to the Risk of COVID-19 in Hospital Doctors in the UK?

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Abstract

The novel coronavirus pandemic is posing significant challenges to healthcare workers (HCWs) in adjusting to redeployed clinical settings and enhanced risk to their own health. Studies suggest a variable impact of COVID-19 based on factors such as age, gender, comorbidities and ethnicity. Workplace measures such as personal protective equipment (PPE), social distancing (SD) and avoidance of exposure for the vulnerable, mitigate this risk. This online questionnaire-based study explored the impact of gender and religion in addition to workplace measures associated with risk of COVID-19 in hospital doctors in acute and mental health institutions in the UK. The survey had 1206 responses, majority (94%) from BAME backgrounds. A quarter of the respondents had either confirmed or suspected COVID-19, a similar proportion reported inadequate PPE and 2/3 could not comply with SD. One third reported being reprimanded in relation to PPE or avoidance of risk. In univariate analysis, age over 50 years, being female, Muslim and inability to avoid exposure in the workplace was associated with risk of COVID-19. On multivariate analysis, inadequate PPE remained an independent predictor with a twofold (OR 2.29, (CI - 1.22-4.33), p=0.01) risk of COVID-19. This study demonstrates that PPE, SD and workplace measures to mitigate risk remain important for reducing the risk of COVID-19 in hospital doctors. Gender and religion did not appear to be independent determinants. It is imperative that employers consolidate risk reduction measures and foster a culture of safety to encourage employees to voice any safety concerns.

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  1. SciScore for 10.1101/2020.06.15.20125450: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.
    • Thank you for including a protocol registration statement.

    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.