High Amounts of SARS-CoV-2 Precede Sickness Among Asymptomatic Health Care Workers

  1. Joakim Dillner
  2. K Miriam Elfström
  3. Jonas Blomqvist
  4. Lars Engstrand
  5. Mathias Uhlén
  6. Carina Eklund
  7. Fredrik Boulund
  8. Camilla Lagheden
  9. Marica Hamsten
  10. Sara Nordqvist-Kleppe
  11. Maike Seifert
  12. Cecilia Hellström
  13. Jennie Olofsson
  14. Eni Andersson
  15. August Jernbom Falk
  16. Sofia Bergström
  17. Emilie Hultin
  18. Elisa Pin
  19. Ville N Pimenoff
  20. Sadaf Hassan
  21. Anna Månberg
  22. Peter Nilsson
  23. My Hedhammar
  24. Sophia Hober
  25. Johan Mattsson
  26. Laila Sara Arroyo Mühr
  27. Kalle Conneryd Lundgren

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Abstract

Background

Whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity among asymptomatic subjects reflects past or future disease may be difficult to ascertain.

Methods

We tested 9449 employees at Karolinska University Hospital, Stockholm, Sweden for SARS-CoV-2 RNA and antibodies, linked the results to sick leave records, and determined associations with past or future sick leave using multinomial logistic regression.

Results

Subjects with high amounts of SARS-CoV-2 virus, indicated by polymerase chain reaction (PCR) cycle threshold (Ct) value, had the highest risk for sick leave in the 2 weeks after testing (odds ratio [OR], 11.97; 95% confidence interval [CI], 6.29–22.80) whereas subjects with low amounts of virus had the highest risk for sick leave in the 3 weeks before testing (OR, 6.31; 95% CI, 4.38–9.08). Only 2.5% of employees were SARS-CoV-2 positive while 10.5% were positive by serology and 1.2% were positive in both tests. Serology-positive subjects were not at excess risk for future sick leave (OR, 1.06; 95% CI, .71–1.57).

Conclusions

High amounts of SARS-CoV-2 virus, as determined using PCR Ct values, was associated with development of sickness in the next few weeks. Results support the concept that PCR Ct may be informative when testing for SARS-CoV-2.

Clinical Trials Registration. NCT04411576.

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  1. Version published to 10.1093/infdis/jiab099
  2. ScreenIT

    SciScore for 10.1101/2020.12.13.20248122: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All enrolled participants signed a written informed consent that also included permission to extract data from the employer’s administrative databases that included data on sick leave.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisWith conventional statistical power and confidence while assuming a cumulative proportion of sick leave among non-exposed persons of 30% and that 10% of the cohort might be exposed, about 3,800 subjects would need to be enrolled to be able to detect associations of 1.4 or greater.
    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: We detected the following sentences addressing limitations in the study:
    Weaknesses of our study include that we were not able to study the relation of biomarkers to infections occurring more than 6-7 weeks before testing, as community transmission of SARS-CoV-2 started in our region only about 6-7 weeks before the study. Also, employees who were not at work were not eligible for inclusion which is likely to have resulted in an underestimation of the spread of the infection at the hospital as employees may have been absent because of COVID-19. The fact that some participants did not have both tests completed is not likely to have affected results, as lack of analysis results was a random phenomenon and the study was still substantially overpowered. Finally, participants were not questioned about present or prior symptoms. The hospital rules were clear that employees with symptoms should not be at work and we had, by design, decided to use only sick leave data to avoid possible recall bias. Subjects may of course have sick leave for many other reasons than Covid-19, but the increases of total sick leave associated with SARS-CoV-2 test positivity was greatly increased compared to the sick leave rates for SARS-CoV-2 negative subjects. We conclude that the amount of virus as determined by the Ct value of the PCR test and also the serology status are useful testing results for distinction between post-symptomatic, asymptomatic, and pre-symptomatic subjects. This is essential for optimal identification of subjects to be targeted by infection control pro...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04411576RecruitingCurrent and Past SARS-CoV-2 Infection and COVID-19 in Health…

    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

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  3. Version published to 10.1101/2020.12.13.20248122v1 on medRxiv