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Un-masking Children: Part 3 of 4. Mask (In)Effectiveness in Limiting COVID-19 Transmission

Image of the internal layer of a medical mask, via scanning electron microscope. Overlaid with expected sizes of most-infectious COVID-19 aerosols.

This is part 3 of a 4-part series dedicated to un-masking children. Jump to other parts below.

Part one discussed a large amount of evidence that children do not play a significant role in the transmission of COVID-19, in school or elsewhere. It was also noted that this apparent fact has been misused as an argument for the effectiveness of masks in curbing transmission. The fallacy is obvious: If you say some measure is effective at stopping something from happening, then put it into action in a place where that thing doesn’t happen, it will look like the measure is effective. [This argument also applies to physical distancing and children, and may also apply to asymptomatic spread—not pre-symptomatic.] Thus, if children don’t really spread COVID, but you put masks on them, they still won’t spread COVID. But masks will look like they work—so long as you forget to ask whether children spread COVID in the first place.

Let’s return to the CDC study in Georgia, discussed in part one, which was with a masked group of students and teachers. Let’s see if the masks really make a difference relative to what was seen in the German study, also discussed in part one. In the German study, children were un-masked for the majority of the study—during the part where some portion of them were recommended to mask, cases increased. Over the whole arc of the German study, for every teacher case, there were 1.1 other cases. For every child case, there were 0.25 cases. Looking at the figure below, and considering only those clusters where it is clear which is the index case (B, E, I, F and H), we see that on average, each infected child infects 0.66 others. Each infected teacher infects an average of three others. Nearly the same 4:1 ratio seen in the German school, though in this masked setting, both teachers and children infected significantly (~4x) more people than in the German study where children were un-masked. It is also worth remembering, that in the Georgia CDC study, there is no clear case where a student indisputably infected a teacher. That study does not note whether the household contacts infected by students were children or adults.

Figure 1

Source: CDC

It is worth pointing out at this point, that in a randomized trial of healthcare workers in 2015, the arm wearing cloth masks contracted flu at more than 3x the rate as the control arm.

Taking these studies together, where cases spread at a higher rates in the masked scenario, and where the overall ratio of spread from teachers vs. students were similar, it seems hard to make the argument for masks in schools as a powerful tool in mitigating spread. That these results mimic results from a prior controlled trial showing increased incidence of flu in groups wearing cloth masks, makes this truly troubling.

Examining Mechanisms of Viral Transmission, and the Ability of Masks to Disrupt it: Mechanistic, and Empirical Investigations

The idea that masks would stop the spread of COVID “just makes sense” to most people. And yet they don’t. No amount of trial data or empirical evidence to the contrary seems capable of displacing this un-scientific notion. This is because displacing a simple notion that makes sense like, masks “catch” viruses, or the sun revolves around the earth, is extremely difficult. The type of math and astronomy that was required for Copernicus to prove that the earth revolved around the sun—and not the other way around—was not easily communicated, and contradicted an idea that made sense to people’s observed experiences. Similarly, getting people to understand fluid mechanics, and the relative size—let alone the physical behavior—of sub-micron particles, which is necessary to understanding why masks don’t work to stop viruses, is not easy. This is complicated by the fact that we don’t know how flu (or COVID) is actually spread, and by the CDC clinging to an out-moded understanding of both, which relies almost exclusively on large droplets or 5+ micron aerosols (the kinds that masks DO stop).

Nonetheless, let’s make the effort to understand why, if we knew a little more about respiratory viruses and their transmission, it might not “make sense” that masks would stop COVID. The science is there, let’s see if we can take the time to understand what it tells us.

The European CDC recently posted the following update to its masking guidance in February 2021 with the following—honest—statement.

“Evidence for the effectiveness of non-medical face masks, face shields/visors and respirators in the community is scarce and of very low certainty.”

The CDC itself published a report in May 2020 noting the following, with regard to the ability of masks to control the flu (which is similar in size, and appears to spread through similar mechanisms as COVID).

“Although mechanistic studies support the potential effect of hand hygiene or face masks, evidence from 14 randomized controlled trials of these measures did not support a substantial effect on transmission of laboratory-confirmed influenza. We similarly found limited evidence on the effectiveness of improved hygiene and environmental cleaning.”

Yet both of these organizations continue to recommend face masks in the face of large numbers of extant studies, and an increasingly large (some would say overwhelming) body of empirical evidence that they do not work to limit transmission of viral respiratory diseases. But why, why wouldn’t face masks work, based on what we know about the spread of viral respiratory diseases?

This really is at the root of the problem. We don’t know how these viruses are transmitted from human to human—not even flu.

In mid-2020, one of the world's foremost influenza researchers, Dr. Donald Milton was quoted in The New York Times as follows:

“We’ve been studying the flu for 102 years and still don’t know for sure how it’s transmitted.” In the study itself he makes the following observation.

Influenza virus is a pathogen of global health significance, but human-to-human transmission remains poorly understood. In particular, the relative importance of the different modes of transmission (direct and indirect contact, large droplet, and aerosols (airborne droplet nuclei)) remains uncertain during symptomatic and asymptomatic infection.

Infection control guidance for pandemic and seasonal influenza assumes that most transmission occurs during symptomatic infection, predominantly via large droplet spread at short range. Thus, social distancing measures are often proposed to mitigate the spread and impact of a pandemic; and hand washing and respiratory etiquette are promoted to reduce transmission. Evidence to support the possibility of aerosol transmission has grown over recent years and leads to controversies about when and if filtering facepiece respirators (and other precautions designed to prevent inhalation of aerosols) versus surgical masks (mainly capable of reducing large droplets and some fine particles) should be used to protect healthcare workers, particularly during a severe pandemic.

The first studies suggesting that aerosol spread might be the primary means of transmission of influenza started to appear around 2008. Since then, they have continued apace.

The CDC still states the following, clinging to what increasingly appears to be an out-moded understanding of flu transmission:

People with flu can spread it to others up to about 6 feet away. Most experts think that flu viruses spread mainly by droplets made when people with flu cough, sneeze or talk. These droplets can land in the mouths or noses of people who are nearby or possibly be inhaled into the lungs.

At around the same time that the studies suggesting aerosol transmission might potentially be a “big thing,” a raft of studies designed to test the efficacy of non-pharmaceutical interventions (NPIs) like social distancing and masking—both predicated on the droplet/fomite model of transmission embraced by the CDC—started to appear. In many ways these studies, which were designed to prove the efficacy of these NPIs in curbing flu, added as much to the body of evidence supporting aerosol transmission as a major transmission route as the aerosol studies themselves. Indeed, if we were actually using the petabytes of data that have been generated over the course of this pandemic, the droplet/fomite model of transmission would likely be totally scrapped. Because if that were the dominant transmission route for respiratory disease (and especially COVID), there would be no more COVID.

The evidence that droplets were not a major source of spread for COVID was also hard for the world’s public health agencies to swallow. In fact, it took a significant push from a large number of scientists to force the WHO, the CDC and the ECDC look the evidence in the face and acknowledge that it was impossible that aerosol transmission was not a major, if not the dominant method of transmission for COVID. Some have suggested that this was due to politicization of science due to the Trump white house, but the letter linked above is targeted at the WHO. It is also clear from the CDC’s stance above on flu, that it is reluctant to admit aerosol transmission as a major transmission route for any respiratory virus.

Aerosol transmission for COVID (and presumably flu) has now been widely accepted. But there remain questions as to how large the aerosols are (aerosols range in size from <.01 microns to 10 microns). This is of paramount importance. In another study by Dr. Milton, he notes the following:

“Together the studies show that surgical masks can limit the emission of large droplet spray and aerosol droplets larger than 5 µm. However, surgical masks are not as efficient at preventing release of very small particles. It is well known that surgical masks are not effective for preventing exposure to fine particles when worn as personal protection. We had hypothesized that when used as source control, exhaled droplets might be large enough prior to evaporation to be effectively captured, primarily through impaction. This appears to be true for virus carried in coarse particles. But the majority of virus in the exhaled aerosol appear to be in the fine fraction that is not well contained.”

Thus, if aerosols droplets are smaller than 5 microns, he notes “It is well known that surgical masks are not effective for preventing exposure to fine particles when worn as personal protection.” He notes later on that “the majority of virus in the exhaled aerosol appear to be in the fine fraction that is not well-contained.”

From this point, the question is, how small are COVID aerosols, and how much of the infectious virus is contained in the smallest aerosols? Building on Dr. Milton’s work, various groups have been able to shed light on both of these questions, as they pertain to flu. This study shows that 87% of infectious aerosols were less than 4.7 microns—smaller than what is effectively trapped by a surgical mask, and that these aerosols were created in the absence of an “aerosol-generating” procedure—either natural (like sneezing), or through some kind of medical interventions. That study did not identify the size distribution below 4.7 microns—but subsequent ones did.

One of the first studies to demonstrate that large amounts of viral RNA were carried in extremely small aerosols was completed in 2008. This study showed that during normal breathing significant amount of virus was shed, and that “over 87% of the exhaled particles were under 1 µm and less than 0.1% were larger than 5 µm.” The authors estimated that the majority of the aerosols were less than 0.5 µm (10x less than the 5 µm level that Dr. Milton notes as being the threshold below which surgical masks are no longer effective). The authors note that this makes sense, because the size of particles exhaled during normal breathing is 0.1-0.5 µm—the surprise came in seeing that these sub-microscopic particles could be the major carriers of infectious virus. The question remained whether this virus was infectious.

A 2018 study further demonstrated that the majority of infectious virus was found in fine aerosols, that the primary source of generation for those aerosols was simply breathing—not speaking—and showed “that sneezing is rare and not important for—and that coughing is not required for—influenza virus aerosolization.”

The more skeptical among you will be saying, “OK, but that’s flu, what above for COVID?” In fact, as early as June 2020, it was reported that COVID virus was found in aerosols between 0.2 and 0.5 microns. This is, likely not coincidentally, the exact size range of the particles where it is now widely believed that the majority of infectious flu is found, as well as nearly the exact size of the aerosol particles we exhale during normal breathing—0.1-0.5 microns—again, also not likely a coincidence.

If this is true for COVID as for flu, and a large portion of infectious virus is carried in the 0.1-0.5 micron aerosols that we emit during normal breathing--particles that are generated deep within the alveoli of our lungs--this would explain why masks have had so little impact on COVID-19 cases.

The aerosol particles that we exhale through normal breathing are in the range of 0.1-0.5 microns. This is the most difficult size to filter out of the air. Leave it to evolution to come up with a delivery mechanism that is the best at evading our efforts to catch it…Particles in this size range actually have a name, Most Penetrating Particles (MPPs). They are notorious because of our inability to filter them out of the air.

There are only 4 mechanisms through which we can eliminate particles from a room. The first, Brownian motion, works only for the very smallest particles, those up to 100 nm (or 0.1 micron). The second mechanism is through gravity—sedimentation. This works for particles between 0.5 and 1 micron. Unfortunately, for particles between 0.2 and 0.5 microns, they settle at a rate of 72 microns-0.5 mm/minute. Thus, the largest of these virus-carrying breath aerosols (0.5 microns) would take approximately 400 minutes (or nearly 7 hours) to travel the 200 mm to the ground when exhaled from a normal-sized adult—meaning they are just wafting around in the air. The third mechanism is separation by impaction, where particles are removed from the air by “running into” something—think of the dust on your air filter. Unfortunately, this kind of filtration only works for particles that are more than 1 micron (about twice the size of the largest aerosol particles that we breath). In fact, even when we breathe in particles of this size (0.2-0.5 microns), they only deposit within our respiratory tract at a rate of 30%--the other 70% are expelled. These things just don’t like to settle—anywhere. The final method of filtration is electrostatic filtration, which works for electrically charged particles, but is not expected to play a major role in exhaled aerosol particles. If indeed flu and SARS-CoV-2 particles are carried predominantly by the respiratory aerosols that we exhale through normal breathing, then they would have managed to find the exact size that we are nearly incapable of filtering out. Which sounds like just about what you would expect from an evolutionary track, given that both of these viruses were and are able to spread across the globe in a matter of week to months.

With this background, let’s return to the mechanistic studies that the CDC notes as being promising, but for which the empirical evidence does not provide support. The CDC notes that while mechanist studies suggest promise in our ability to limit transmission, when put into practice, the results do not show any benefit. What do they mean when they say mechanistic studies? They mean studies like the double-masked mannequins that have NaCl sprayed from their mouths. There are several flaws with these studies (catalogued here). The first is that these studies (including the most recent CDC one) do not use actual virus, or people to create the virus. The second is that they effectively measure how much “spit” (or NaCl in this case) is “caught” by the mask (they weigh it after). If virus were evenly distributed in respiratory secretions, this would not be such a bad way to look at things. But, increasingly, it is looking like this is not the case—almost certainly not for flu—and that the majority of infectious virus is in the smallest aerosols, which are generated deep within the lungs. This would mimic tuberculosis, where the most infectious particles are the smallest. In this case, a mechanistic study that “weighed the spit,” while catching 100% of the liquid, would also miss nearly 100% of the infectious virus, which would still be wafting through the air on those most penetrating particles, not to settle for another 6-12 hours.

The mechanistic study that gave the CDC the double-masking idea—as well as the multi-layer home-made mask recommendation—was almost certainly this one from the American Chemical Society. They performed a series of mechanistic studies on NaCl (not COVID) particles down to 10 nm (.01 micron). The results are below.

Figure 2: Filtration Efficiency of Various Materials, by Size

What you notice, is that in the 0.1-0.3 micron range (just below where N-95s are expected to filter), the range of breath aerosols, there is a decrease in filtration efficiency for every material—showing us just how aptly named those “most penetrating particles” are. Looking at the graph above, you would assume that a cotton/silk homemade mask would provide the best protection—but there is a catch, and that is the gap. With a gap—which is present in every mask that is not fitted (and even some that are), these mask drop down to roughly 20% efficiency.

What this mechanistic study did that makes it better than others, was to perform all of the tests with AND without a gap. The size of the gap was 1% of the surface area. The red area below corresponds to 1% of the surface area of the “mask” below. At this point, we’ve all been wearing masks long enough to know that this would qualify as a pretty well-fitting mask.

Figure 3: Visualization of what a 1% gap in surface area looks like. Red areas are 1% of the total surface area

The following picture shows a real mask on a mannequin. These gaps square pretty well with what one sees even on healthcare workers—except that often the area on either side of the nose is also bowed out. These gaps are significantly larger than the red area shown above.

Figure 4: Gaps in a mask, relative to size of particles carrying SARS-CoV-2

Source: @Birb_k

In the ACS study, with only 1% gaps (again much smaller than what is observed in real life--the gaps in the picture above are roughly 1/4) the reduction of filtration efficiency is stunning. N-95s drop down between 12% and 34% depending on particle size, surgical drop down to 44-50%, and the homemade cotton/silk, down to ~20%.

Some people will argue that “even a little protection” is good. This does not really square with what we have seen empirically. It remains to be seen, for instance, whether infectious dose has any impact on disease severity for COVID-19. The direction that research is trending for both flu and TB, suggests that it is the smallest particles, carrying the least amount of virus which are the most infectious and cause the most severe disease as they deposit deep within the lungs, and that they can be infectious at very low doses—as little as 300-3000 viral copies. The same study that demonstrated that sneezing was not associated with infectious influenza virus, also demonstrated that normal breathing would produce roughly 38,000 viral copies within the fine aerosols in a half hour.

Given this, it seems that a leaky condom might be a better analogy. We understand that condoms are not 100% effective, but it is not that they are ALWAYS only 20-50% effective. Rather, they are designed to be 100% effective, but misapplication, or an occasional rupture might render them ineffective, if it corresponded with ovulation. If ovulation were a constant, the failure rate for condoms would render them useless, because, as we know, it only takes one sperm to fertilize an egg. 300 copies of a virus, is not dissimilar to this. It’s not a lot, and over the course of even a small amount of time, masks will gap, and because particles in this range don’t get “caught” on the mask via impact, the accumulated virus will then be released into the broader environment, where it will stay aloft for 6-12 hours (if it hasn’t already wafted through the 5-10 micron holes of the mask).

Which it almost certainly has. Below is a highly zoomed-in image from a scanning electron microscope of the interior layer of a surgical mask, as well as three particle sizes: the largest is 1 micron, the two smaller ones are the size of respiratory aerosols, increasingly demonstrated to carry the majority of infectious flu virus, and which have also been demonstrated to carry SARS-CoV-2 as well. The inner layer of a surgical mask is by far the tightest weave. Thus, looking at this image, it seems fairly apt when people say wearing a mask to keep COVID in (or out) is like putting up a chain link fence to keep out mosquitoes. A 1 millimeter gap is like having a hole in your fence that is 1,000 – 5,000x wider than the virus-carrying aerosol (in human terms, this would be like something that is 1000-5000 feet wide (1/5 to a mile wide). And as a reminder, if the virus-carrying particles are in this 0.2-0.5 micron range as has been seen, these don’t deposit on the mask—thus, with every exhalation, if they didn’t just go out through the gaps, they would simply be pushed further through the mesh.

Figure 5: Image of the internal layer of a medical mask, via scanning electron microscope. Overlaid with expected sizes of most-infectious COVID-19 aerosols.

Interestingly, a study performed back in the 80’s to assess the effectiveness of surgical masks at containing particles during surgery, found that when placing “tracer” particles on the inside of the mask, in every single case (not some of the time—ALL OF THE TIME), these particles were subsequently found in the wound. So much for the “some protection has got to be better than none” argument. Note, these particles were MUCH larger than the aerosols believed to carry COVID—we know this because they found them with a microscope. The aerosols that appear to carry COVID and flu are substantially smaller than what can be seen with a microscope (one of the reasons it is so hard to pin viral aerosol transmission down, is that we don’t have good, inexpensive ways to identify particles below 0.5 microns).

Let us now return to the idea of masking children. As was noted at the beginning of this section, masks appear to “work” to stop transmission from children. Increasingly, it seems likely this is because children are not major sources of transmission—not because the children are wearing masks. Given the way children wear masks—almost always with large gaps, constantly up-and-down—and seeing the impact of gapping or removing masks on particle capture, it is nearly impossible to think that the reason schools have not been major sources of transmission is due to masks. Rather, it seems far more likely that children are not major sources of transmission, and that teachers have been protected, not by they or their children being masked, but by the relative good health conferred by their youth, as well as the strong immune systems they have developed thanks to extended and repeated exposure to children.

The fact that the transmission was significantly higher between teachers and other teachers, teachers and students, and students and students in the masked school studied in the Georgia school vs. the un-masked schools in Germany makes this argument even more persuasively.

Ultimately, when our understanding of how a disease is spread is so nascent, and increasingly appears to have been on the wrong track entirely—we must rely on empirical evidence to guide our decision, and inform our research priorities. Doing so is the only way we can improve our understanding of disease transmission routes. If we ignore the empirical evidence, we will certainly continue to bark up the wrong tree (see, California). The empirical evidence is very strong that there is no positive impact on universal masking reducing COVID-19 transmission. Looking at the emerging physical and mechanistic data we have, this makes sense.

Rational Ground performed a county-by-county analysis of case growth for those counties with mask mandates, and those without, between 5/15 and 12/15. The results are shown below. Nationally, cases were roughly 40% higher, 27 cases/day/100,000, in those counties with mask mandates, vs. 17 cases/day/100,000 in those counties without. Being able to compare within a given state controls for testing variability by state, and the analysis also corrected for population-density of the counties. Still—a negative correlation.

Figure 6: Comparing COVID-19 Cases/day/100K by counties with and without mask mandates--a state-by-state analysis

The purpose of this post is not to argue that masks increase spread—though there is increasingly data suggesting that they may (using the birth control analogy, if we told people something was an effective birth control method that was not, we would certainly expect a lot more babies), which is supported by controlled trials showing a significant increase in flu incidence in masked health care workers. The purpose is to argue that children are not a major source of COVD transmission, and current “successes” in keeping COVID at bay in schools has little to do with masking.

Many continue to take a “what’s the harm” approach to masking. There is harm. First, those states with the strictest mask mandates also happen to be the states with the fewest children learning in-person. The myth being perpetuated by the CDC that they know how to control COVID, has robbed roughly half of the children in the U.S. of a year’s education.

Figure 7: States Without Mask Mandates are Fare More likely to have 100% In-person, traditional school

In fact, looking across all 50 states, while there is no correlation between COVID stringency and deaths, there is a strong correlation between lack of in-person learning, and high levels of unemployment.

Figure 8

These are the big-picture harms of our non-pharmaceutical interventions. They are of such a magnitude, and the benefits so manifestly absent, that they ought to be instantly abandoned.

That they have not been, after failing so spectacularly--just as epidemic theory and the randomized controlled trials suggested they would--tells us that the motives of those in public health, politics and the media who continue to espouse these measures do not include public health. Quite the contrary. It has become clear that the greater the misery inflicted upon the most vulnerable members of our community--children, the elderly, minorities, the poor--the more these groups double down on the policies causing it

It is a painful irony, that the states whose populations claim to care the most about social justice are the ones that have most wholeheartedly embraced these deeply unjust policies. Continue to Part 4:A Plan to Un-mask Children. Or go back to Part 3: Understanding Relative Risk.

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