The Removal of Airborne Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Other Microbial Bioaerosols by Air Filtration on Coronavirus Disease 2019 (COVID-19) Surge Units

  1. Andrew Conway Morris
  2. Katherine Sharrocks
  3. Rachel Bousfield
  4. Leanne Kermack
  5. Mailis Maes
  6. Ellen Higginson
  7. Sally Forrest
  8. Joana Pereira-Dias
  9. Claire Cormie
  10. Tim Old
  11. Sophie Brooks
  12. Islam Hamed
  13. Alicia Koenig
  14. Andrew Turner
  15. Paul White
  16. R Andres Floto
  17. Gordon Dougan
  18. Effrossyni Gkrania-Klotsas
  19. Theodore Gouliouris
  20. Stephen Baker
  21. Vilas Navapurkar

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Abstract

Airborne severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected in a coronavirus disease 19 (COVID-19) ward before activation of HEPA-air filtration but not during filter operation; SARS-CoV-2 was again detected following filter deactivation. Airborne SARS-CoV-2 was infrequently detected in a COVID-19 intensive care unit. Bioaerosol was also effectively filtered.

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  1. Version published to 10.1093/cid/ciab933
  2. ScreenIT

    SciScore for 10.1101/2021.09.16.21263684: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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:
    This study has limitations, being conducted rapidly in active wards during an ongoing pandemic. The evaluation was conducted in two rooms and there are no data defining the optimal air changes required to remove detectable pathogens with the specified devices. Given the large volume of air within the room and the stability of viruses in the sampling fluid, it was predictable that the amount of SARS-CoV-2 detected via qPCR would be minimal, as evidenced by high CT values. Therefore, we cannot categorically state that there was circulating infectious virus. RNA is sufficient to suggest the virus was present and it has been shown that aerosolised virus can remain infectious for >3 hours 27,28; additionally, air sampling devices can artefactually reduce the apparent viability of sampled virus. Negative results from the control sampler, and the striking but reversible effect of the air filtration devices, suggest these are not false positive detections and we cannot exclude the risk of airborne infection. Future studies should examine whether air filtration devices, such as those used here, have an impact on healthcare professional and patient focussed outcomes, including measuring infection/exposure as an endpoint, as well as assessing potential harm, such as noise, reduced ambient humidity or impact on delivery of care. In conclusion, we were able to detect airborne SARS-CoV-2 RNA in a repurposed COVID-19 ‘surge ward’ and found that air filtration can remove SARS-CoV-2 RNA below...

    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.

  3. Version published to 10.1101/2021.09.16.21263684v1 on medRxiv