SARS-CoV-2 virus and antibodies in front-line Health Care Workers in an acute hospital in London: preliminary results from a longitudinal study

  1. Catherine F Houlihan
  2. Nina Vora
  3. Thomas Byrne
  4. Dan Lewer
  5. Judith Heaney
  6. David A. Moore
  7. Rebecca Matthews
  8. Sajida Adam
  9. Louise Enfield
  10. Abigail Severn
  11. Angela McBride
  12. Moira Spyer
  13. Rupert Beale
  14. Peter Cherepanov
  15. Kathleen Gaertner
  16. Sarah Edwards
  17. Maryam Shahmanesh
  18. Kevin Ng
  19. Nikhil Faulkner
  20. Georgina Cornish
  21. Naomi Walker
  22. Susan Michie
  23. Ed Manley
  24. Fabiana Lorencatto
  25. Richard Gilson
  26. Sonia Gandhi
  27. Steve Gamblin
  28. George Kassiotis
  29. Laura E McCoy
  30. Charles Swanton
  31. Andrew Hayward
  32. Eleni Nastouli

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Abstract

Background

Although SARS-CoV-2 infection in Healthcare Workers (HCWs) is a public health concern, there is little description of their longitudinal antibody response in the presence or absence of SARS-CoV-2 and symptoms. We followed HCWs in an acute London hospital to measure seroconversion and RNA detection at the peak of the pandemic.

Methods

We enrolled 200 patient-facing HCWs between 26 March and 8 April 2020 and collected twice-weekly self-administered nose and throat swabs, symptom data and monthly blood samples. Swabs were tested for SARS-CoV-2 by PCR, and serum for antibodies to spike protein by ELISA and flow cytometry.

Findings

During the first month, 42/200 (21%) HCWs were PCR positive in at least one nose and throat swab. Only 8/42 HCW (19%) who were PCR positive during the study period had symptoms that met current case definition. Of 181 HCWs who provided enrollment and follow-up blood samples, 82/181 (45.3%) were seropositive. In 33 HCWs who had positive serology at baseline but were PCR negative, 32 remained PCR negative. One HCW had a PCR positive swab six days after enrollment, likely representing waning infection.

Conclusion

The high seropositivity and RNA detection in these front-line HCWs brings policies to protect staff and patients into acute focus. Our findings have implications for planning for the ‘second wave’ and for vaccination campaigns in similar settings. The evidence of asymptomatic SARS-CoV-2 infection indicates that asymptomatic HCW surveillance is essential, while our study sets the foundations to answer pertinent questions around the duration of protective immune response and the risk of re-infection.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.08.20120584: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: With consent, we conducted baseline interviews including demographic data, self-reported comorbidities, and information on patient contact and aerosol generating procedures (AGPs).
    IRB: ethical oversight was provided by the South Central Berkshire Research Ethics Committee Laboratory testing: As part of the pandemic response, UCLH formed a partnership with the Francis Crick Institute (the Crick-COVID-Consortium) to increase diagnostic capacity and swabs were tested for SARS-CoV-2 RNA by PCR (11).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Briefly, flow cytometry used HEK293T cells which expressed wild-type SARS-CoV-2 Spike protein bound to a 96-well plate.
    HEK293T
    suggested: None
    Software and Algorithms
    SentencesResources
    Plates were read on a Ze5 (Bio-Rad) running Bio-Rad Everest software v2.4.
    Bio-Rad Everest
    suggested: None
    Analysis was carried out using FlowJo vlO
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Data management and analysis: Data from the questionnaires were double-entered onto a REDCap database(14) and analysed using R v3.5.1 and STATA V15.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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:
    The limitations of this study lie in the challenge of following a cohort of individuals who work irregular shifts, in stressful environments, at the peak of the pandemic and often travel to work from long distances. The study aim was to capture infections with twice weekly swabs and avoid missing short lived or transient infections. In order to do this, we sampled HCWs whether they were working a shift or not, providing significant strength to our study. However, gaps in follow-up where participants have not submitted twice-weekly swabs can be seen and there are some who have seroconverted between time points without SARS-CoV-2 RNA being detected. Samples were occasionally held in participants’ home fridges for up to 1 week before they were submitted to the laboratory with potential RNA degradation during these times. This is a preliminary report of the first month of follow up of the London cohort. Future analysis including all study data across study sites will examine the risk by HCW occupation and other demographic variables. We report early results from a closely observed cohort of front line HCWs who worked throughout the peak of COVID-19 in central London and have the highest seroprevalence in HCWs published to date. This has implications for the expected ‘second wave’ during which hospital admissions are likely to increase again and is applicable to similar large inner-city hospital settings. In light of the rapid launch of vaccine trials, our data can provide useful ...

    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. ScreenIT

    SciScore for 10.1101/2020.06.08.20120584: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementWith consent , we conducted baseline interviews including demographic data , self-reported comorbidities , and information on patient contact and aerosol generating procedures ( AGPs) .RandomizationA cross sectional study combining SARSCoV-2 seroprevalence with nose and throat swab PCR in 578 randomly selected HCWs in a large teaching hospital in Barcelona found a combined point prevalence of infection of 11% (16).Blindingnot detected.Power Analysisnot detected.Sex as a biological variableA greater proportion of men tested positive 22/76 (29.0%, 95% CI 19.7-40.4) than women 20/122 (16%, 95% CI 10.8-24.2) p=0.0498.Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Briefly , flow cytometry used HEK293T cells which expressed wild-type SARS-CoV-2 Spike protein bound to a 96-well plate.
    HEK293T
    suggested: None
    Software and Algorithms
    SentencesResources
    Plates were read on a Ze5 ( Bio-Rad ) running Bio-Rad Everest software v2.4 .
    Bio-Rad Everest
    suggested: None
    Analysis was carried out using FlowJo v10
    FlowJo
    suggested: (FlowJo, SCR_008520)
    Data management and analysis Data from the questionnaires were double-entered onto a REDCap database(14 ) and analysed using R v3.5.1 and STATA V15 .
    REDCap
    suggested: (REDCap, SCR_003445)
          <div style="margin-bottom:8px">
        <div><b>STATA</b></div>
        <div>suggested: (Stata, <a href="https://scicrunch.org/resources/Any/search?q=SCR_012763">SCR_012763</a>)</div>
      </div>
    </td></tr></table>

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.06.08.20120584v1 on medRxiv