Slight reduction in SARS-CoV-2 exposure viral load due to masking results in a significant reduction in transmission with widespread implementation

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

Masks are a vital tool for limiting SARS-CoV-2 spread in the population. Here we utilize a mathematical model to assess the impact of masking on transmission within individual transmission pairs and at the population level. Our model quantitatively links mask efficacy to reductions in viral load and subsequent transmission risk. Our results reinforce that the use of masks by both a potential transmitter and exposed person substantially reduces the probability of successful transmission, even if masks only lower exposure viral load by ~ 50%. Slight increases in mask adherence and/or efficacy above current levels would reduce the effective reproductive number (R e ) substantially below 1, particularly if implemented comprehensively in potential super-spreader environments. Our model predicts that moderately efficacious masks will also lower exposure viral load tenfold among people who get infected despite masking, potentially limiting infection severity. Because peak viral load tends to occur pre-symptomatically, we also identify that antiviral therapy targeting symptomatic individuals is unlikely to impact transmission risk. Instead, antiviral therapy would only lower R e if dosed as post-exposure prophylaxis and if given to ~ 50% of newly infected people within 3 days of an exposure. These results highlight the primacy of masking relative to other biomedical interventions under consideration for limiting the extent of the COVID-19 pandemic prior to widespread implementation of a vaccine. To confirm this prediction, we used a regression model of King County, Washington data and simulated the counterfactual scenario without mask wearing to estimate that in the absence of additional interventions, mask wearing decreased R e from 1.3–1.5 to ~ 1.0 between June and September 2020.

Article activity feed

  1. SciScore for 10.1101/2020.09.13.20193508: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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:
    Our work has key limitations. First, based on available data, it is impossible to know the true average efficacy of a mask worn by a transmitter or an exposed contact. Many epidemics at the state level have demonstrated a reduction in the effective reproductive number ranging from 0.2-0.5 when more widespread masking was implemented, even as physical distancing levels waxed and waned. Our model suggests that if 50-75% of people wear masks 50-75% of the time, which is roughly in accordance with state level observations of mask compliance, then a broad estimate for real world mask efficacy is ∼0.4-0.6, assuming that efficacy is equal between transmitters and exposed contact, and that masks are properly used to optimize their efficacy. If transmitter masking is more efficacious, while exposed contact masking is proportionally less efficacious, then similar results can be expected. The real-world estimate is inclusive of multiple factors including variability in mask type and masking technique. Regardless of the precise estimate, it is clear that wider implementation would yield significant reductions in spread of SARS-CoV-2 at the population level. Second, our generalized model is not region-specific for the current pandemic. The relative impact of super-spreader events, intensity of transmission and proportion of symptomatic cases may vary from region to region based on contact network structure and age demographics. Nevertheless, the general qualitative conclusions about maski...

    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.

  2. SciScore for 10.1101/2020.09.13.20193508: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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:

    Our work has key limitations. First, based on available data, it is impossible to know the true average efficacy of a mask worn by a transmitter or an exposed contact. Many epidemics at the state level have demonstrated a reduction in the effective reproductive number ranging from 0.2-0.5 when more widespread masking was implemented, even as physical distancing levels waxed and waned [24]. Our model suggests that if 50-75% of people wear masks 50-75% of the time, which is roughly in accordance with state level observations of mask compliance, then a broad estimate for real world mask efficacy is ~0.4-0.6, assuming that efficacy is equal between transmitters and exposed contact, and that masks are properly used to optimize their efficacy. If transmitter masking is more efficacious, while exposed contact masking is proportionally less efficacious, then similar results can be expected. The real-world estimate is inclusive of multiple factors including variability in mask type and masking technique. Regardless of the precise estimate, it is clear that wider implementation would yield significant reductions in spread of SARS-CoV-2 at the population level. Second, our generalized model is not region-specific for the current pandemic. The relative impact of super-spreader events, intensity of transmission and proportion of symptomatic cases may vary from region to region based on contact network structure and age demographics. Nevertheless, the general qualitative conclusions about ...


    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.


    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.