• Eurosurveillance · Dec 2020

    Review

    Community use of face masks and similar barriers to prevent respiratory illness such as COVID-19: a rapid scoping review.

    • Julii Brainard, Natalia R Jones, Iain R Lake, Lee Hooper, and Paul R Hunter.
    • The Norwich School of Medicine, University of East Anglia, Norwich, Norfolk, United Kingdom.
    • Eurosurveillance. 2020 Dec 1; 25 (49).

    AbstractBackgroundEvidence for face-mask wearing in the community to protect against respiratory disease is unclear.AimTo assess effectiveness of wearing face masks in the community to prevent respiratory disease, and recommend improvements to this evidence base.MethodsWe systematically searched Scopus, Embase and MEDLINE for studies evaluating respiratory disease incidence after face-mask wearing (or not). Narrative synthesis and random-effects meta-analysis of attack rates for primary and secondary prevention were performed, subgrouped by design, setting, face barrier type, and who wore the mask. Preferred outcome was influenza-like illness. Grading of Recommendations, Assessment, Development and Evaluations (GRADE) quality assessment was undertaken and evidence base deficits described.Results33 studies (12 randomised control trials (RCTs)) were included. Mask wearing reduced primary infection by 6% (odds ratio (OR): 0.94; 95% CI: 0.75-1.19 for RCTs) to 61% (OR: 0.85; 95% CI: 0.32-2.27; OR: 0.39; 95% CI: 0.18-0.84 and OR: 0.61; 95% CI: 0.45-0.85 for cohort, case-control and cross-sectional studies respectively). RCTs suggested lowest secondary attack rates when both well and ill household members wore masks (OR: 0.81; 95% CI: 0.48-1.37). While RCTs might underestimate effects due to poor compliance and controls wearing masks, observational studies likely overestimate effects, as mask wearing might be associated with other risk-averse behaviours. GRADE was low or very low quality.ConclusionWearing face masks may reduce primary respiratory infection risk, probably by 6-15%. It is important to balance evidence from RCTs and observational studies when their conclusions widely differ and both are at risk of significant bias. COVID-19-specific studies are required.

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