Aerosol formation during processing of potentially infectious samples on Roche immunochemistry analyzers (cobas e analyzers) and in an end-to-end laboratory workflow to model SARS-CoV-2 infection risk for laboratory operators

  1. Géza V. Burghardt
  2. Markus Eckl
  3. Doris Huether
  4. Oliver H. D. Larbolette
  5. Alessia Lo Faso
  6. Beatus R. Ofenloch-Haehnle
  7. Marlene A. Riesch
  8. Rolf A. Herb

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Abstract

To assess aerosol formation during processing of model samples in a simulated real-world laboratory setting, then apply these findings to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to assess the risk of infection to laboratory operators.

Design

This study assessed aerosol formation when using cobas e analyzers only and in an end-to-end laboratory workflow. Recombinant hepatitis B surface antigen (HBsAg) was used as a surrogate marker for infectious SARS-CoV-2 viral particles. Using the HBsAg model, air sampling was performed at different positions around the cobas e analyzers and in four scenarios reflecting critical handling and/or transport locations in an end-to-end laboratory workflow. Aerosol formation of HBsAg was quantified using the Elecsys ® HBsAg II quant II immunoassay. The model was then applied to SARS-CoV-2.

Results

Following application to SARS-CoV-2, mean HBsAg uptake/hour was 1.9 viral particles across the cobas e analyzers and 0.87 viral particles across all tested scenarios in an end-to-end laboratory workflow, corresponding to a maximum inhalation rate of <16 viral particles during an 8-hour shift.

Conclusion

Low production of marker-containing aerosol when using cobas e analyzers and in an end-to-end laboratory workflow is consistent with a remote risk of laboratory-acquired SARS-CoV-2 infection for laboratory operators.

Article activity feed

  1. Version published to 10.3389/fpubh.2022.1034289
  2. Version published to 10.1101/2022.02.08.479519v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2022.02.08.479519: (What is this?)

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

    Table 1: Rigor

    EthicsField Sample Permit: Following air sampling, the elution and quantification of HBsAg concentration was performed in the same way as previously described for the cobas e analyzer panel sub-study but was conducted on the cobas e 801 analytical unit
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Internally validated software (OASEpro HetIA, Roche Diagnostics International) was used to calculate the concentration (IU/mL) of HBsAg from the signal detected by the cobas e analyzers and data were processed using Microsoft Excel (
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  4. Version published to 10.1101/2022.02.08.479519v1 on bioRxiv