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Review of "Global projections of potential lives saved from COVID-19 through universal mask use"

Reviewer: Noah Haber (Stanford University) 📒📒📒 ◻️◻️

Published onApr 14, 2022
Review of "Global projections of potential lives saved from COVID-19 through universal mask use"
key-enterThis Pub is a Review of
Global projections of lives saved from COVID-19 with universal mask use

ABSTRACTBACKGROUNDSocial distancing mandates (SDM) have reduced health impacts from COVID-19 but also resulted in economic downturns that have led many nations to relax SDM. Until deployment of an efficacious and equitable vaccine, intervention options to reduce COVID-19 mortality and minimize restrictive SDM are sought by society.METHODSA susceptible-exposed-infectious-recovered (SEIR) deterministic transmission model was parameterized with data on reported deaths, cases, and select covariates to predict infections and deaths from COVID-19 through March 01, 2021. We explore three scenarios: a “non-adaptive” scenario where neither mask use or SDM adapt to changing conditions, a “reference” where current national levels of mask use are maintained and SDM reintroduced when deaths rise, and an increase in mask use to 95% coverage levels (“universal mask”). We reviewed published studies to set priors on the magnitude of reduction in transmission through increasing mask use.RESULTSMask use was estimated at 59.0% of people globally on October 19, 2020. Universal mask use could avert 733,310 deaths (95% UI 385,981 to 1,107,759) between October 27, 2020 and March 01, 2021, the difference between the predicted 2.95 million deaths (95% UI 2.70 to 3.35) in the reference scenario and 2.22 million deaths (95% UI 2.00 to 2.45) in the universal mask scenario over this time period.CONCLUSIONSThe cumulative toll of the COVID-19 pandemic could be substantially reduced by the universal adoption of masks before the availability of a vaccine. This low-cost, low-barrier policy, whether customary or mandated, has enormous health benefits with presumed marginal economic costs.

To read the original manuscript, click the link above.

Reviewer 1 (Noah Haber) | 📒📒📒 ◻️◻️

RR:C19 Strength of Evidence Scale Key

📕 ◻️◻️◻️◻️ = Misleading

📙📙 ◻️◻️◻️ = Not Informative

📒📒📒 ◻️◻️ = Potentially Informative

📗📗📗📗◻️ = Reliable

📘📘📘📘📘 = Strong

To read the review, click the links below.

Dwight Turner:

You have contributed straightforward new aspects basket random to the article, which are appreciated.