Masks in a Post COVID-19 World: A Better Alternative to Curtailing Influenza?

  1. Henri Froese
  2. Angel G. A. Prempeh

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Abstract

Over the course of the coronavirus pandemic, it has become apparent that non-pharmaceutical interventions such as masks and social distancing are of great help in mitigating the transmission of airborne infectious diseases. Additionally, data from respiratory specimen analysis from the past year show that current mask mandates established for COVID-19 have inadvertently reduced the rates of other respiratory diseases, including influenza. Thus, the question arises as to whether comparatively mild measures should be kept in place after the pandemic to reduce the impact of influenza. In this study, we employed a series of differential equations to simulate past influenza seasons, assuming people wore face masks. This was achieved by introducing a variable to account for the efficacy and prevalence of masks and then analyzing its impact on influenza transmission rate in an SEIR model fit to the actual past seasons. We then compared influenza rates in this hypothetical scenario with the actual rates over the seasons. Our results show that several combinations of mask efficacy and prevalence can significantly reduce the burden of seasonal influenza. Particularly, our simulations suggest that a minority of individuals wearing masks greatly reduce the number of influenza infections. Considering the efficacy rates of masks and the relatively insignificant monetary cost, we highlight that it may be a viable alternative or complement to influenza vaccinations. We conclude with a brief discussion of our results and other practical aspects

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  1. ScreenIT

    SciScore for 10.1101/2021.07.03.21259943: (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

    Software and Algorithms
    SentencesResources
    2.2 Infection data: The CDC FluView application2 provides weekly number of positive flu tests (we do not separate between different strains) in public health and clinical laboratories for seasons 2010/11 to 2018/19.
    FluView
    suggested: None
    Least-Squares fitting using the LMFIT Python library ([10]) yields good fits on all seasons.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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 of our approach include no stratification by age or contact scenario, significant uncertainties in mask use and efficacy, and disregard of other non-pharmaceutical interventions. Currently, vaccinations are the prominent way to protect against influenza, having been available on a large scale since 1945 ([13]). Current influenza vaccination rates in the US are not high enough to provide herd immunity ([14]), and have averted around 15-20% of influenza illnesses over the seasons from 2011-12 to 2018-19 5. While, vaccines have to be newly manufactured each season with significant R&D investments, the vaccines of course only have to be administered once while face masks would need to be worn continuously, which might be seen as more burdensome by the general population. [15] estimates the economic burden of seasonal influenza in the United States at $6.3 -$25.3 billion. Assuming the economic cost scales linearly with the number of infections, a scenario in which at least 95% of infections are reduced (which includes both the ‘mask mandate’ and ‘masks suggested’ scenarios) saves $6.0 – $24.0 billion per season, at negligible cost. Similar to public opinion regarding potential health hazards such as smoking and driving without seatbelts shifting over time, and legislation being introduced, we can imagine the Coronavirus pandemic changing public (and expert) opinion towards everyday mask usage; then again, large parts of the population might be tired of wearing masks af...

    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.

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  2. Version published to 10.1101/2021.07.03.21259943v1 on medRxiv