That Study of Face Masks Does Not Show What the CDC Claims

According to a new study by the Centers for Disease Control and Prevention, wearing a face-mask in public areas dramatically lowers the chance of getting COVID-19. The CDC summarized the findings in a shared graphic. It found that cloth masks lower the chances of getting COVID-19. This is in contrast to the risk reduction of surgical masks, which reduced the risk by 66 per cent and N95 or 95 respirators’ risk reductions at 83.

You will notice that the results for cloth masks were not statistically significant if you look at the footnotes. This study was not statistically significant even though it appeared in The CDC. Weekly Report on Morbidity & Mortality on Friday, did not validate the protective effect of the most commonly used face coverings—a striking fact that the authors do not mention until the end of the sixth paragraph. If you look at the data, the findings for N95s and surgical masks are statistically significant but do not show a cause-and effect relationship. This is contrary to what the CDC has presented.

The framing of this issue is just one part of a wider pattern. The CDC changed its mind in 2020. It no longer dismissed the importance of wearing general masks. They now consider it “the most powerful and important public health tool that we have.” In September 2020, then–CDC Director Robert Redfield asserted, without any evidence, that masks were more effective at preventing infection than vaccines would prove to be. Rochelle Walensky (redfield’s successor), implied that masks were more effective at preventing infection than vaccines, even though the highly contagious variant of omicron was already widely spread.

The CDC is always willing to go the extra mile in order to support its recommendation that all people, even children under 2, should wear masks. By distorted information, it is undermining already damaged credibility. The CDC claims a causal link in this instance, but does not consider other explanations.

Researchers identified 1,528 Californians who had tested positive for COVID-19 from February 18 to December 1, 2021. They then matched them with 1,511 Californians who were negative. Although the “controls”, were identical to the cases in terms of their age, gender, and whereabouts, they were different in ways that might affect the chances of them being positive. It is difficult to know if masking accounts or not for differences noted by the CDC.

Only 652 of the 1,176 control subjects and 1176 cases were included in the mask analysis. They “self-reported having been indoors public during the 2 week preceding testing, and had no contact with any person with SARS-CoV-2 confirmed or suspected during that time. The subjects who claimed they “always” used masks indoors were 56 percent more likely to be positive than those who stated they did not. The CDC graphic shows a comparison based on 534 subjects, who each “specified which type of mask they usually used.”

People who wear masks indoors are much more likely to have COVID concerns than those who do not. Researchers adjusted for the possibility of infection, and found that vaccination was less common in people with negative results. However, researchers “didn’t account for any other prevention behaviors that may affect risk.” If mask wearers tend to avoid crowded spaces, spend less time indoors with strangers, and/or are more likely to keep their distance from other people—all of which are plausible—those precautions could partly or fully explain the differences that the CDC attributes to masking.

Study data show that subjects tested negative were not necessarily different from those who had tested positive. Only 17 percent of COVID negative subjects were motivated by symptoms that are consistent with the disease. 78 percent sought out testing for COVID positives because of their condition. People in the latter group were nearly 50 percent more likely to say they had sought testing simply because they were curious about whether they had been infected—a motivation that suggests greater concern and caution. COVID-negative patients were three times more likely than the COVID-positive subjects to claim that they sought testing because of a medical procedure. Perhaps this motivated them to be cautious and avoid getting infected.

Although the possibility of systematic variations in “other preventive behaviours” may be enough cause to be suspicious of how the CDC presents these results, there are several problems with the study.

Only 13% of people who tested positive answered the telephone and only 9% of those who tested negative did so. These low participation rates leave one wondering about how representative those interviewed by researchers are.

The COVID-positive people who did not answer the phone may have been especially ill, for example, while the COVID-negative people who did participate may have been especially eager to discuss their experiences—perhaps because they had dodged the virus and attributed that outcome to precautions such as masking. Researchers note that the study’s generalizability is restricted to people who are seeking SARS-CoV-2 test and were open to a phone interview. Other protective behavior might also be considered.

Another bias could have been introduced by the fact that test results were known to each individual. COVID-19 can be detected in people who wear masks, but still get COVID-19. This could lead to them reporting that they weren’t as vigilant as they ought to have been. People who were negative for COVID-19 may have exaggerated their use of masks.

Vinayprasad is an University of California San Francisco epidemiologist. She discusses the weaknesses of this study and others in a Substack blog post. Vinay also points out that the CDC’s claimed effects are not “implausible.” A September 2017 report from Bangladesh on a randomised trial showed a 11% reduction in the chance of developing symptomatic infections among villagers who had surgical masks. Now the CDC is claiming that surgical masks “lowered the odds of testing positive” by 66 percent—an effect six times as large. Walensky has claimed that wearing a mask can “reduce” the chance of a positive test.[es]”Your chance of being infected is greater than 80 percent,” however, the CDC did not provide any evidence.

Prasad states, “The paper has been irredeemably and completely flawed.” Its flaws should have never been published, Prasad concludes. [or] promoted. Publishing bad science is not a good idea when an issue becomes deeply polarizing. You can’t convince people to believe it, but proponents won’t have to prove their case, which increases mistrust of institutions.

Prasad is skeptical about the importance of general masking with cloth covers, particularly when it comes to virus transmission. Prasad co-authored a review of literature which described evidence that supports the CDC recommendations as weak.

Eyewitness studies are subject to bias and observational studies with confounding. Mechanistic studies rely on surrogate endpoints, such as droplet distribution, as indicators of disease transmission. There is little clinical evidence to support facemask effectiveness. The best clinical evidence that exists has been largely ineffective. In fact, fourteen out of 16 randomized controlled trials which compared facemasks with no mask controls failed to demonstrate statistically significant benefits for the intended-to-treat population. Eighteen of sixteen meta-analyses were critical or ambiguous about whether there is evidence to support recommending public facemasks. The remaining eight supported public intervention based on limited evidence, mainly on the precautionary principle. While weak evidence does not necessarily preclude the possibility of taking preventive actions against unprecedented events like the COVID-19 pandemics, ethical principles demand that all information including the strongest evidence and the best estimate of the benefit to be disclosed to the public.

In his Substack post, Prasad laments that the CDC has not sponsored any randomized controlled trials to verify the effectiveness of face masks, which he calls “a catastrophic research failure,” especially when it comes to “universal masking” in K–12 schools and day care centers. Prasad may find existing evidence to be more convincing than Prasad, but the CDC’s feigned glee is alarming. Flagrantly, the agency failed to “truthfully inform” the public about this matter.

Although “well-fitting masks and respirators effectively filter virus sized particles in laboratory conditions,” California’s case-control researchers note that “few studies” have evaluated their effectiveness in protecting against SARS-CoV-2. The study is limited in many ways, eight of which were explicitly mentioned by the researchers. This does little to address that. However, the CDC states that it shows “consistently wearing a comfortably-fitting mask or respirator indoors protects against SARS-2 infection.”

The Bangladesh study as well this research suggest cloth masks. Not effective in real-world settings—or at least that their benefits are not big enough to generate statistically significant results. Even so, the CDC has been a bit evasive in acknowledging that N95s work better than cloth masks. Although the CDC admits that a respirator provides the most protection, it isn’t the same thing as acknowledging that cloth masks might not provide adequate protection from infection by omicron.

This study’s management by the CDC has implications beyond just how masks actually work. The agency’s handling of this and other instances has shown that they cannot be trusted to provide honest scientific information. Americans now distrust everything that the CDC has to say, even if it’s well-grounded. Despite trying to defend its credibility and reputation, the CDC’s desperate efforts at backing up the decisions it already made have had the contrary effect.