Quantifying Respiratory Airborne Particle Dispersion Control Through Improvised Reusable Masks: The Physics of Non-Pharmaceuptical Interventions for Reducing SARS-COV-2 (COVID-19) Airborne Transmision

  1. Nathan J. Edwards
  2. Rebecca Widrick
  3. Richard Potember
  4. Mike Gerschefske

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Abstract

Background

For much of the SARS-CoV-2 (COVID-19) pandemic, many countries have struggled to offer definitive guidance on the wearing of masks or face coverings to reduce the highly infectious disease transmission resulting from a lack of compelling evidence on the effectiveness of communities wearing masks, and slow acceptance that aerosols are a primary SARS-CoV-2 disease transmission mechanism. Recent studies have shown that masks have been effective in several countries and populations, leaving only a lack of quantitative data on the control of airborne dispersion from human exhalation. This current study specifically has the objective to quantify the effectiveness of non-medical grade washable masks or face coverings in controlling airborne dispersion from exhalation (both droplet and aerosol) by measuring changes in direction, particle cloud velocities, and concentration.

Design

This randomized effectiveness study used a 10% NaCl nebulized polydisperse particle solution (0.3 μm up to 10 μm in size) delivered by an exhalation simulator to conduct 94 experiment runs with combinations of 8 different fabrics, 5 mask designs, and airflows for both talking and coughing. Multiple particle sensors were instrumented to measure reduction in aerosol dispersion.

Results

Three-way multivariate analysis of variance establishes that fabric, mask design, and exhalation breath level have a statistically significant effect on changing direction, reducing velocity, or concentrations of airborne particles (Fabric: P = < .001, Wilks’ Λ = .000; Mask design: P = < .001, Wilks' Λ = .000; Breath level: P = < .001, Wilks' Λ = .004). There were also statistically significant interaction effects between combinations of all primary factors.

Conclusions and Relevance

The application of facial coverings or masks can significantly reduce the airborne dispersion of aerosolized particles from exhalation by diffusing the particle cloud direction and slow down its travel speed. Consequently, the results indicate that wearing masks when coupled with social distance can decrease the potentially inhaled dose of SARS-CoV-2 aerosols or droplets especially where infectious contaminants may exist in shared air spaces. The conclusion is well aligned with the concept of “time-distance-shielding” from hazardous materials emergency response. However, the effectiveness varies greatly between the specific fabrics and mask designs used.

Article activity feed

  1. Version published to 10.1101/2020.07.12.20152157v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.07.12.20152157: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationDesign: We conducted the effectiveness study using a randomized full factorial design of experiments with 10% NaCl nebulized solution and an exhalation simulator to conduct 94 experiment runs with combinations of 8 different fabrics, 5 mask designs, no-mask as a control, and exhalation airflows (PEF and FEV1) that represent both talking and coughing.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Randomization was created using a mathematical function in MATLAB with blocking on the two airflow settings (47 each).
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)
    SPSS version 1.0.0.1327 was used to perform MANOVA.
    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:
    Limitations: One limitation of this study is that it provides approximations of human exhalation using polydisperse NaCl solution rather than human exhalation which adds additional compositions of particles that can be smaller than 0.3μm in diameters, moisture, proteins, gases, and other bio material.[66] The effectiveness of masks for source or dispersion control from long term use (such as during a 4 hour or 8 hour workdays) cannot be directly established from this data, however this study utilizes industry and NIOSH accepted proxy for testing respiratory barriers of NaCl. Another limitation was the PMS sensor performance: measurement minimum of 0.3μm particles and a slower intake fan speed at 0.1 CFM limited its ability to accurately measure all characteristics of fast moving particle clouds from that of no-mask applied. Regardless, the sensor data and experiment design were sufficient to determine statistical conclusions on the effects of wearing masks and face coverings of different fabrics and designs. Future works should consider using a large test chamber and more sensors to result in more accurate measurement of airborne dispersion and turbulent airflows.

    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.

  3. Version published to 10.1101/2020.07.12.20152157v1 on medRxiv