IDEAS home Printed from https://ideas.repec.org/a/ibn/ijspjl/v12y2025i4p1.html
   My bibliography  Save this article

Statistical Reproducibility of Meta-Analysis for Medical Mask Use in Community Settings to Prevent Airborne Respiratory Virus Infection

Author

Listed:
  • S. Stanley Young
  • Warren B. Kindzierski

Abstract

Many US states, cities, and counties implemented public masking orders during the coronavirus (COVID) pandemic on the notion that this intervention would delay and flatten the epidemic peak and largely benefit public health outcomes. A p-value plot can provide insights into possible inappropriateness (incorrectness) of assumptions of a statistical model. It can be used to confirm, disprove, or identify ambiguity (uncertainty) in a meta-analytic finding and research claim. P-value plotting was used to evaluate statistical reproducibility of meta-analysis studies for disposable medical (surgical) mask use in community settings to prevent airborne respiratory virus infection. Eight studies (seven meta-analysis, one systematic review) published between 1 January 2020 and 7 December 2022 were evaluated. Base studies were randomized control trials with outcomes of medical diagnosis or laboratory-confirmed diagnosis of viral (Influenza or COVID) illness. Self-reported viral illness outcomes were excluded from the evaluation because of awareness bias. No evidence was observed for a medical mask benefit to prevent respiratory virus infection in six p-value plots (five meta-analysis and one systematic review). Research claims of no benefit in three meta-analysis and the systematic review were reproduced in p-value plots. Research claims of a benefit in two other meta-analysis were not reproduced in p-value plots suggesting irreproducibility of these claims. Insufficient data was available to construct p-value plots for two other meta-analysis because of over-reliance on self-reported outcomes. Independent findings of p-value plotting show that meta-analysis of existing randomized control trials fail to demonstrate a benefit of medical mask use in community settings to prevent airborne respiratory virus infection.

Suggested Citation

  • S. Stanley Young & Warren B. Kindzierski, 2025. "Statistical Reproducibility of Meta-Analysis for Medical Mask Use in Community Settings to Prevent Airborne Respiratory Virus Infection," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 12(4), pages 1-1, January.
  • Handle: RePEc:ibn:ijspjl:v:12:y:2025:i:4:p:1
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/ijsp/article/download/0/0/49011/52846
    Download Restriction: no

    File URL: https://ccsenet.org/journal/index.php/ijsp/article/view/0/49011
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:ijspjl:v:12:y:2025:i:4:p:1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.