Dental Mitigation Strategies to Reduce Aerosolization of SARS-CoV-2

  1. J.J. Vernon
  2. E.V.I. Black
  3. T. Dennis
  4. D.A. Devine
  5. L. Fletcher
  6. D.J. Wood
  7. B.R. Nattress

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Abstract

Limiting infection transmission is central to the safety of all in dentistry, particularly during the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Aerosol-generating procedures (AGPs) are crucial to the practice of dentistry; it is imperative to understand the inherent risks of viral dispersion associated with AGPs and the efficacy of available mitigation strategies. In a dental surgery setting, crown preparation and root canal access procedures were performed with an air turbine or high-speed contra-angle handpiece (HSCAH), with mitigation via rubber dam or high-volume aspiration and a no-mitigation control. A phantom head was used with a 1.5-mL min −1 flow of artificial saliva infected with Φ6-bacteriophage (a surrogate virus for SARS-CoV-2) at ~10 8 plaque-forming units mL −1 , reflecting the upper limits of reported salivary SARS-CoV-2 levels. Bioaerosol dispersal was measured using agar settle plates lawned with the Φ6-bacteriophage host, Pseudomonas syringae. Viral air concentrations were assessed using MicroBio MB2 air sampling and particle quantities using Kanomax 3889 GEOα counters. Compared to an air turbine, the HSCAH reduced settled bioaerosols by 99.72%, 100.00%, and 100.00% for no mitigation, aspiration, and rubber dam, respectively. Bacteriophage concentrations in the air were reduced by 99.98%, 100.00%, and 100.00% with the same mitigations. Use of the HSCAH with high-volume aspiration resulted in no detectable bacteriophage, both on nonsplatter settle plates and in air samples taken 6 to 10 min postprocedure. To our knowledge, this study is the first to report the aerosolization in a dental clinic of active virus as a marker for risk determination. While this model represents a worst-case scenario for possible SARS-CoV-2 dispersal, these data showed that the use of HSCAHs can vastly reduce the risk of viral aerosolization and therefore remove the need for clinic fallow time. Furthermore, our findings indicate that the use of particle analysis alone cannot provide sufficient insight to understand bioaerosol infection risk.

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  1. Version published to 10.1177/00220345211032885
  2. ScreenIT

    SciScore for 10.1101/2021.03.24.21254254: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical Analyses: Statistical analyses were performed using IBM SPSS Statistics 26.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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:
    Whilst an improvement on models reported in the literature, it is not without its limitations. The model uses artificial teeth, which lack the anatomical intricacies of human teeth. However, particle analysis by Shahdad et al reported little difference between plastic and real teeth. [32] Our model does not imitate the effects of a patient breathing, or other patient behaviours, such as talking or coughing which would likely contribute considerably to bioaerosol production. Nonetheless, by demonstrating reductions in active biological marker dispersal, we can make robust indications as to the value of dental mitigation approaches. Whilst other approaches to bioaerosol measurements, such as the Gesundheit II, [33] are available, this device does not permit the assessment of dispersal throughout a room. The requirement for, and length of, a period of fallow time is far from clear, with estimates ranging from two to 180 minutes. [32, 34, 35] However, this is often based on particle data alone. When based on particle count data, Ehtezazi et al suggested that with no mitigation the average time to return to baseline levels was between 28 and 34 minutes. [35] However, this study had no salivary element, which potentially contributes significantly to particle levels. In this study, we determined a wide variation in the time it took for particles levels of all sizes to return to pre-AGP levels, although the larger particles required less time with the electric hand-piece procedures. ...

    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

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  3. Version published to 10.1101/2021.03.24.21254254v1 on medRxiv