They're Still Trying To Sell The Lie That Masks Would Stop COVID If Everyone Wears Them

They're just never going to give up, are they? 

The mask fanatics spent years forcing their delusions onto others during the COVID-19 pandemic. From Anthony Fauci telling the country forcefully, and scientifically, that masks don't work, to flip-flopping when he realized his party had changed their mind, to the CDC altering national policy based on an entirely inaccurate article from a sociologist in The New York Times, to the endless list of politicians who demanded masking then were photographed enjoying maskless dinners at fancy restaurants. 

Not to mention the other politicians who stood around maskless at schools while young children were forced to wear them, based on the delusions of adults. 

But the real issue with the mask zealots is that they were never forced to admit they were wrong. Instead, years after masking comprehensively failed to stop COVID anywhere on earth, they've relied on an unfalsifiable premise: masks would have worked if everyone wore them. 

Now, a new paper, yes a new paper, has been released, making that case once again. And once again, it's disingenuous, inaccurate, and purposefully ignorant. Which means it's sure to grab the attention of a willing media desperate to protect itself. 

WASHINGTON, DC - NOVEMBER 29: Anthony Fauci (R), Director of the National Institute of Allergy and Infectious Diseases and Chief Medical Advisor to the President, speaks alongside U.S. President Joe Biden as he delivers remarks on the Omicron COVID-19 variant following a meeting of the COVID-19 response team at the White House on November 29, 2021 in Washington, DC. The World Health Organization designated it a variant of concern after South African officials discovered the variant last week. (Photo by Anna Moneymaker/Getty Images)

No, Masks Would Not Have Stopped COVID

The paper makes the claim that if everyone wore the correct type of masks, COVID transmission would have been effectively eliminated at a population level. 

Except, spoiler alert, it doesn't actually show that. Why? Because yet again, it's a model. A summary of the paper describes how the writer laundered his opinions and assumptions through ostensible scientific research.

Effectively, according to the study, previous examinations of masking efficacy against transmission were limited by a small sample size. In order to fix this, Richard Sear from the University of Surrey in the United Kingdom created, wait for it, a model. That model relied on data from the UK National Health Service COVID-19 app. We're already starting off great. A model based on data from an app created by the National Health Service. Sounds very representative and reliable.

This app, which was in place from 2020 to 2023, would collect information about the time period that users spent around each other. Not one user and one non-user, just two people who both had the app on their phones. Again, extremely representative sample, right? 

Sear makes assumption after assumption in his paper, about how infections are transmitted, the length of interaction required in order to transmit the virus and of course, the efficacy of masks. If any one of those assumptions are wrong, then the paper and its conclusions fall apart. And they are wrong. Oh boy, are they wrong.

His suggestion for reducing infections and transmission is for everyone in the UK, and around the world really, to wear N95 or FFP2 masks. And the assumption he bakes into his model is that those masks would have reduced transmission by a factor of 10. Ten! 10! There is no evidence on earth to support this. 

"One NPI is the wearing of masks such as N95 or FFP2 masks," he writes. "N95 masks have been assigned a protection factor of ten. The FFP2 standard is for a filtration efficiency of 92% as worn. Taking an FFP2/N95 to reduce the dose by a factor of 𝑓=0.1, I can estimate 𝑃𝑇⁡(𝑡) for a person who is a member of a population equivalent to that of the NHS app users when this person wears an FFP2/N95."

This is insanity. There's no justification for this estimation. Even the paper he links to as a reference doesn't support that claim. They admit that efficacy is almost entirely dependent on a perfect fit, which is virtually impossible to maintain without professional fit testing and consistent use under supervision. Still, the lower end of their filtration estimate was 43.8%. He simply took the highest number of efficacy for any particle size and included it as his overall estimate.

But here's what they actually write: "Mask performance is dominated by face seal leakage. Despite the additional filtering layers added to cloth masks, and the higher filtration efficiency of the materials used in disposable procedure and KN95 masks, the total inward leakage protection factor was only marginally improved."

And the only way to achieve any level of protection is by requiring "fit and seal" testing and having workers "trained in their use."

"Comparatively, the higher TILPF for the N95 FFR group, by a factor of 27 to 117, is directly related to their design and certification, which requires that they fit and seal to the face better, more sizes are available for wearers to choose from, and the wearers are generally trained in their use."

So Sear made an inaccurate assumption, based on his own linked paper, that members of the general public would be wearing fit-tested N95 masks after receiving training on how to use them. Then he baked that inaccurate assumption into a model and it spit out the results he wanted. 

He then goes on to admit that surgical masks are far less effective, while still saying that they reduce infection probability by 40%, and 60% at a population level.

"So I predict one person wearing a surgical mask gives a reduction in infection probability of about 40%, while a whole population wearing surgical masks reduces transmission by about 60%."

This should tell you how reliable his assumptions and modeling actually are. Every country tried surgical masks, and several tried N95's. They didn't work.

In his conclusion, Sear simply says that he believes masks would have lowered transmission by a "factor of nine" "In conclusion, I have predicted that for a population like that of the UK, wearing FFP2/N95-type masks should reduce the effective reproduction number 𝑅 by a factor of nine," he writes.

There is no evidence for this, no support for it. He simply assumed it based on an inaccurate reading of masking efficacy and the likelihood of proper fit testing and training and ignored contradictory evidence. Not to mention that relying on NHS app data is laughably absurd. We know nothing about who downloaded the app, their characteristics and mask-wearing habits. Those users might already have been wearing N95 masks, and still got infected, thoroughly disproving his claim. 

In fact, that's a more likely outcome because those who were concerned enough about COVID to download an NHS contact tracing app were almost certainly more likely to wear masks. 

This is the problem with modeling and with pro-maskers. Modeling is simply assumptions. If those assumptions are wrong, the model is wrong. Pro-maskers can't accept they were wrong, so they ignore how real world data contradicts their delusional fantasy. So we get continued "research" like this that's shared by experts and their media partners. It's endless.