Delayed healthcare seeking and prolonged illness in healthcare workers during the COVID-19 pandemic: a single-centre observational study

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Abstract

To describe a cohort of self-isolating healthcare workers (HCWs) with presumed COVID-19.

Design

A cross-sectional, single-centre study.

Setting

A large, teaching hospital based in Central London with tertiary infection services.

Participants

236 HCWs completed a survey distributed by internal staff email bulletin. 167 were women and 65 men.

Measures

Information on symptomatology, exposures and health-seeking behaviour were collected from participants by self-report.

Results

The 236 respondents reported illness compatible with COVID-19 and there was an increase in illness reporting during March 2020 Diagnostic swabs were not routinely performed. Cough (n=179, 75.8%), fever (n=138, 58.5%), breathlessness (n=84, 35.6%) were reported. Anosmia was reported in 42.2%. Fever generally settled within 1 week (n=110/138, 88%). Several respondents remained at home and did not seek formal medical attention despite reporting severe breathlessness and measuring hypoxia (n=5/9, 55.6%). 2 patients required hospital admission but recovered following oxygen therapy. 84 respondents (41.2%) required greater than the obligated 7 days off work and 9 required greater than 3 weeks off.

Conclusion

There was a significant increase in staff reporting illness compatible with possible COVID-19 during March 2020. Subsequent serology studies at the same hospital study site have confirmed sero-positivity for COVID-19 up to 45% by the end of April 2020 in frontline HCWs. The study revealed a concerning lack of healthcare seeking in respondents with significant red flag symptoms (severe breathlessness, hypoxia). This study also highlighted anosmia as a key symptom of COVID-19 early in the pandemic, prior to this symptom being more widely recognised as a feature of COVID-19.

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  1. SciScore for 10.1101/2020.05.07.20094177: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The Study was approved by the Audit and Research Committee at the Hospital of Tropical Diseases, UCLH [9], Anonymous data was exported to Microsoft Excel 2010 (Microsoft Corporation) and R (R Development Core Team 2008) for analysis.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The Study was approved by the Audit and Research Committee at the Hospital of Tropical Diseases, UCLH [9], Anonymous data was exported to Microsoft Excel 2010 (Microsoft Corporation) and R (R Development Core Team 2008) for analysis.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    R Development Core
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Venn diagrams were generated using Venny 2.1.0 (https://bioinfoep.cnb.csic.es/tools/vennv/) [10] and BioVenn (https://www.biovenn.nl/) [11],
    BioVenn
    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: 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 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.