Incidence of SARS-CoV-2 infection among asymptomatic frontline health workers in Los Angeles County, California

  1. Megan Halbrook
  2. Adva Gadoth
  3. Rachel Martin-Blais
  4. Ashley Grey
  5. Deisy Contreras
  6. Saman Kashani
  7. Clayton Kazan
  8. Brian Kane
  9. Nicole H. Tobin
  10. Jennifer A. Fulcher
  11. Sarah L. Brooker
  12. Scott G. Kitchen
  13. Emmanuelle Faure-Kumar
  14. Otto O. Yang
  15. Kathie G. Ferbas
  16. Grace M. Aldrovandi
  17. Anne W. Rimoin

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Abstract

Beginning April 8, 2020, we enrolled 1787 frontline heath workers who were asymptomatic for COVID-19 into a longitudinal surveillance study. During that time 4 healthcare workers and 6 first responders tested positive for SARS-CoV-2 by RT-PCR. Additionally, 43 healthcare workers and 55 first responders had detectable IgG antibodies to SARS-CoV-2.

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  1. ScreenIT

    SciScore for 10.1101/2020.11.18.20234211: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the UCLA institutional review board on March 25, 2020.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Tabular counts, attack rates and associations between seroprevalence and demographic factors and occupational exposures were calculated using SAS statistical software version 9.4 (Cary, NC).
    SAS statistical
    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.

  2. Version published to 10.1101/2020.11.18.20234211 on medRxiv