Midshipmen wearing face masks stand and salute before the Navy Midshipmen play against the Houston Cougars on Saturday in Annapolis, Md. Researchers have tried to estimate how many lives would be saved by universal mask-wearing. Patrick Smith/Getty Images
Universal mask wearing in public could greatly reduce the number of Americans who die by COVID-19 by February, a study published Friday in the journal Nature Medicine projects.
Researchers at the University of Washington's Institute for Health Metrics and Evaluation made estimates based on some assumptions under different scenarios.
In what they describe as the worst-case scenario, they project that COVID-19 deaths could exceed a million between September 2020 and February 2021 if what they call "the current pattern of easing" restrictions continues in states.
In a second scenario that they think is more likely, they say 511,000 could die between September and February under the assumption that "states would once again shut down social interaction and some economic activity" for six weeks once deaths reach a certain threshold per million residents.
But in a third scenario where 95% of the population dons face coverings and social restrictions are in place, the projection is for deaths to be about 381,000 — or about 130,000 fewer than under the second scenario.
If that mask percentage changes to 85% of Americans with restrictions, it could still save some 96,000 lives, they say.
The study analyzed previous COVID-19 deaths and cases between Feb. 1 and Sept. 21. Researchers also pulled information from various surveys — including ones by Facebook and YouGov — to estimate that as of Sept. 21, only 49% of Americans reported always wearing a mask.
The study also assumed a 40% reduction in risk of COVID transmission due to a mask usage. Earlier studies estimated masks can reduce transmission by at least 30%.
Researchers also noted that changes in policies and behavior could affect outcomes and that epidemics progress in a way that is are "difficult to observe directly and at scale."
"It is unreasonable to expect any model to do everything well, so each model makes compromises to serve a purpose, while maintaining computational tractability," researchers wrote.
According to data from Johns Hopkins University, more than 224,000 Americans have died from the coronavirus.
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