Do masks stop you catching Covid?
WHAT’S THE ISSUE?
A review of research on reducing the spread of respiratory viruses, published in January by the prestigious Cochrane Library, has reignited the fight over whether masks work.
The authors found ‘‘little to no’’ evidence that masking at the population level reduced Covid-19 infections, concluding there’s ‘‘uncertainty about the effects of face masks’’. But a poorly worded summary meant the review has been widely misinterpreted, with some saying it’s proof masks are useless and others criticising the meta-analysis itself.
The editor-in-chief of the Cochrane Library, Karla SoaresWeiser, published a statement this month attempting to clarify its findings: ‘‘Given the limitations in the primary evidence, the review is not able to address the question of whether maskwearing itself reduces people’s risk of contracting or spreading respiratory viruses.’’
WHAT WE FOUND
There are two issues at play here: one is whether wearing a mask will help protect you, an individual, against Covid-19. Evidence suggests it will.
But as Covid-19 mathematical modeller Professor Michael Plank explains, that’s not the question the authors asked: ‘‘They’re not asking whether wearing a wellfitting, high-quality mask helps.
Undoubtedly the answer to that is, yes – although it won’t eliminate the risk entirely.’’
The review looked at whether the promotion of mask wearing – along with other ‘‘physical interventions’’ such as screening, isolation, hand hygiene and so on – helps slow the spread of respiratory viruses. And that’s where the data is inconclusive.
Masks during the Covid-19 pandemic have become a political issue in the United States and other Western countries in particular, where small but vocal groups see them as an attack on individual freedoms.
At the other end of the spectrum, it’s clear some have exaggerated the value of general maskwearing.
Cochrane is a British nonprofit organisation that is widely considered the gold standard for its reviews of healthcare data.
The review in question looked at data from 78 relevant studies. Most predated the coronavirus pandemic: only two were about Covid and masks.
It found that mask-wearing in the community ‘‘probably makes little or no difference to the outcome of influenza-like illness/
Covid-19-like illness compared to not wearing masks’’.
However, it said: ‘‘The high risk of bias in the trials, variation in outcome measurement, and relatively low adherence with the interventions during the studies hampers drawing firm conclusions.’’
Essentially, this means: Limited data inputs – that is the studies used – produces inconclusive results.
As Soares-Weiser said in her statement, the review asked whether interventions ‘‘to promote mask wearing’’ helped to slow the spread of respiratory viruses and ‘‘the results were inconclusive’’.
That means, for example, how humans wore masks mattered as much as masks themselves.
We all know that even when told to wear masks, some people won’t, and others won’t wear them correctly. Plus, mandates are messy.
Remember the policies around wearing masks indoors but taking them off to eat and drink? The challenges in evaluating them are obvious.
IN SUMMARY
The Cochrane review doesn’t tell us whether masking reduces Covid-19 transmission during a pandemic. Instead, it asks whether mask promotion slows the spread of respiratory viruses.
And the answer to that question is inconclusive.
The few studies included in the review that took place during the pandemic, including the study in Bangladesh, where interventions to encourage mask-wearing were rolled out over a six-week period, suggest these resulted in a modest (10% to 20%) reduction in Covid19 cases.
The best data we have suggests a mask will reduce an individual’s risk of catching Covid, but it’s unclear if mandates, or promotion of mask wearing, did that at a population level.
One key takeaway is we need more and better data on interventions such as mask-wearing.
Reporting disclosure statement: This article was written with expert advice from Michael Plank, a professor at the University of Canterbury’s school of mathematics and statistics.