In April 2020, Physicist Denis Rancourt posted a short article to ResearchGate.net that was later taken down by the website’s administration because of its poor quality. In June, River City Reader posted it under the title “Masks Don’t Work: A Review of Science Relevant to COVID-19 Social Policy.” In it, River City Reader pledges “to publish all letters, guest commentaries, or studies refuting [Rancourt’s] general premise that this mask-wearing culture and shaming could be more harmful than helpful.” This is just such an article.
In his article, Rancourt concludes “there is no known benefit arising from wearing a mask in a viral respiratory illness epidemic.” The article is now widely cited by the “anti-mask” movement as proof that masks don’t work and thus laws requiring citizens to wear masks are ineffectual. But, to put it mildly, Rancourt’s argument is fraught with pseudoscience and logical mistakes, and it fails entirely to even provide evidence for (much less proof of) his thesis.
The heavy presence of pseudoscientific mistakes as well as the low academic quality of the work should not surprise those familiar with Rancourt or the issue at hand. Scientifically, the argument is already settled. And as a climate change denier, Rancourt has proven himself to be incapable of recognizing and avoiding mistakes common to pseudoscientists. As a physicist (who specialized in metals but no longer works in academia), not an epidemiologist (or climate scientist), Rancourt is completely outside of his area of expertise.
But to establish that his argument is faulty, I will have to go farther. So, although I do so recognizing the danger of giving legitimacy to his argument by engaging with it, I will now summarize and point out the many ways that Rancourt’s argument goes wrong. Although I am not an epidemiologist either, I am a logician who teaches entire courses on argumentation and medical pseudoscience. So, unlike with Rancourt, my writing of this article falls squarely within my area of expertise. Indeed, I already did these things in a debate I had with him on this very subject. But since he talked over me most of the time, and wouldn’t let me finish any argument I made, I felt it warranted to lay out everything clearly here.
Rancourt’s article is convoluted, and intentionally obtuse. But in the confusion, you can find four reasons that he thinks masks don’t work—indeed that they “cannot possibly work.”
- Not even wearing surgical or N95 masks reduces the risk of contracting a verified illness, so how could cloth masks do so?
- The seasonal nature of outbreaks of flu-like illnesses is due to varying humidity levels; thus masks can’t help prevent their spread.
- The particles that transmit the virus are too small to be blocked by even N95 masks, much less cloth masks.
- A single exposure will cause you to get infected, and masks can’t guarantee no exposure.
All four utterly fail. For those who don’t have time to read this 10,000 word article, you can find a quick refutation of it at the end of the article referenced in this endnote. But for those who would like to see a complete debunking of his entire argument, point by point, that is what follows. But first, I need to make clear how masks do work to help prevent the spread of COVID, and how we know that they do. This will be important for understanding the fallacies of Rancourt’s argument to the contrary. Then we will tackle each of his arguments in turn.
How Masks Help Prevent the Spread of COVID
The explanation is simple, but misinformation has confused the issue. It’s commonly believed that masks simply protect their wearer from becoming infected by filtering the air that a person inhales. While there is some evidence that cloth masks maybe offer some protection to their wearer in this regard, the primary way they help mitigate the spread is by filtering the air a person exhales—by sneezing, coughing, speaking, or breathing.
Why are masks effective in filtering viruses from the exhaled air? Because a virus doesn’t travel by itself; it travels in droplets of moisture propelled from the mouth that can be captured. The largest droplets are intercepted by the surface of the mask; smaller ones are stopped by impaction as they try to make it through the mask; and the smallest, including aerosols, are diffused by the mask because of something called Brownian motion–the erratic way they move. This lowers the number of infected droplets in the air, and thus reduces the risk of exposure for other people.
Now, it’s important to note that, while all masks filter exhalations, certain kinds of masks are better than others. The early woven cloth masks were effective, but not as effective as later non-woven ones—what we today call “medical” or “surgical masks.” (According to Davies, while both types are effective, surgical masks are about three times more effective.) But different kinds of cloth, layered or combined, can offer better filtration, by making the pathway particles would have to travel to get through the mask more convoluted. Aydin found that layering cotton fabrics can make homemade masks almost as effective as surgical masks, and Konda found that layering different kinds of fabrics (like cotton with flannel) could also increase their efficacy. Such masks filtered 80% of particles smaller than 300 nanometers (0.3 microns) and 90% of those larger. Filters can also improve mask efficacy.
Now if an infected droplet is already in the air that a masked person is about to inhale, the mask will be less likely to catch that particle. That might make one question how cloth masks can filter the air that someone exhales. But that question is easily answered. Part of it is due to air flow; when you are breathing in, you are not pushing the air directly through the mask. But also–the longer a droplet is in the air, the more opportunity it has to evaporate and become smaller (and even aerosolize)—and (unless it’s smaller than 0.3 microns) the smaller it is, the less likely a particle is to be caught by a mask. So infected droplets in the air that an unmasked person has exhaled has a better chance at making it through your mask. But most of the infected droplets exiting your mouth won’t, since they have not yet had a chance to evaporate. 
In other words, masks unquestionably work to help prevent the spread of COVID because they filter droplets (those on the right of the below picture), including most of them that would become aerosols (those in the middle), and they can even capture those that start out small (on the far left)—just a bit less efficiently.
So, if you are in a room with a non-masked infected person, you are pretty likely to be infected even if you are wearing a cloth mask. However, if that infected person is wearing a cloth mask, you are much less likely to be infected—even if you are not wearing a mask. This is why it is said “My mask protects you; your mask protects me.” Your choice to not wear a mask does not put you at risk; it puts others at risk.
Now, since the fact that the majority of the work that masks do in curbing the spread of COVID is done by the masks that infected persons are wearing, one might wonder: why don’t we just have infected people wear them? Indeed, this was part of the reasoning behind the traditional, years long, CDC and WHO recommendations that said mask wearing is not necessary for seemingly healthy individuals. With many diseases, it is not. But then experts realized just how long a person could be infected with COVID without knowing it and even that many infected never have any symptoms. Consequently, public mask mandates are the only way to ensure that infected persons—including those who are pre- or asymptomatic—are wearing a mask. Such mandates would thus reduce the number of infected people without masks, thus reduce the number of infected particles in the air, and thus reduce the probability of transmission. Once we realized this, mask wearing was recommended. Granted, the CDC and WHO lagged behind the experts in this regard, but scientists change their mind based on evidence all the time. That’s not unusual. It’s just usually not that public.
How We Know Masks Help Prevent the Spread Of COVID
So given what we know masks do, the fact that mandating them helps curb the spread of COVID is just common sense. But the evidence also bears this out.
For example, transmission rates slowed in hospitals, German cities, North Texas, and in US states after mandates went into effect. (In Germany, they reduced growth rates by 40%.) What’s more, U.S. States with mandates have seen much less spread than those without,  as have countries where mask use is popular. Now some will argue that such correlational studies can’t prove anything because “correlation doesn’t entail causation.” But this is a misuse of that logical rule. A single correlation does not guarantee causation, but enough of them can imply it strongly enough to produce knowledge. For example, deaths rates dropped 27% after seat belt mandates were enacted in New York State, and similar numbers were seen in all states after enacting such laws. Something similar happened for deaths in motorcycle accidents after helmet mandates were enacted. When the connection is obvious, and the correlation is repeated, it most definitely entails causation.
Modeling has also confirmed the effectiveness of mask mandates. According to Stutt and Eikenberry, if masks are just 50% effective, they could help bring down infection rates to non-epidemic levels and reduce the death rate by as much as 45%. Large reviews of observational and comparative studies have also concluded that mask mandates are highly effective, as have collections of collaborating experts. And, of course, there were those infected hairstylists in Missouri who didn’t pass it on to 140 of their clients because they were wearing a mask. The IHME found that mask mandates could save 33,000 by October 1st, and (according to Brooks) if everyone wore a mask, we could get the pandemic under control in four to eight weeks. 
Now, if one is being stubborn, one might demand that this is not good enough. We need randomized control trials (RCTs) for mask safety and efficacy—what Rancourt calls the “golden standard” in science. We actually do have some. The previously mentioned study by Leung, for example, which masked some people (but not others) with respiratory illness and tested for infected droplets an aerosols found that “Surgical face masks reduced detection of coronavirus RNA in both respiratory droplets and aerosols.” A lot of the other studies I mentioned find something similar. But Rancourt is likely to insist that this is not good enough. We need a RTC that measures how many other people got sick with the infected wearing, or not wearing, a mask. What Rancourt fails to recognize is that, while they are great (even necessary) for testing drugs and treatments, RCTs are not necessary or even appropriate for other scientific fields or questions.
To understand why, consider an example. Supposed you wanted to know about the safety and efficacy of Kevlar vests regarding their ability to protect people from bullets. So I explain the science—the physics of how Kevlar resists bullets—and show you how it works in a lab. Maybe I shoot bullets at plastic dummies, some wearing and some not wearing, Kevlar vests. I also show you correlational studies of how, say, death and injuries drop in army platoons after Kevlar vests were issued. That would be good enough right? Of course.
In fact, any RCT that anyone performed on Kevlar vests would be pretty much useless at that point. Why? Because a true RCT would involve lining a whole bunch of people up on a wall, giving some Kevlar vests and some not at random, and then shooting them. Obviously, that kind of study cannot ethically be done. At best—because you don’t take vests away for experimental purposes—an RCT could only compare, say, different groups of soldiers, already out in the field, who happen to be wearing vests or not (for all kinds of various reasons). If you found a significantly lower rate of injury among those wearing Kevlar, the study would be pretty useless because it would just tell you what you already know. But if it found no significant difference in the two groups, it would still be useless. Not only is not finding a difference not proof that it is not there, but you would immediately think that there was a random variable that skewed the results. The soldiers with the vests probably happened to find themselves in a much more dangerous situation than those without, and so it biased the study. It would tell you very little about the efficacy of vests.
That’s how it is with masks. We understand the science of how they work. We know they block droplets and aerosols; we know that is how COVID is spread; we know mask mandates make more people wear masks, and we know COVID is spread pre- and asymptomatically. We even have trials where their use reduces the number of infected particles in the air. Combine that with the above examples from around the world of rates dropping with mask use and mandates, and that’s all you need. We know they work. No ethically dubious RCTs, where we throw healthy people into rooms with COVID patients who may or may not be wearing masks, are necessary. And any other kind of limited RCT that we did in the field would be pretty useless. Even if it found no significant results, that wouldn’t tell us mask don’t work. Not finding something is not evidence that it is not there; random variables skewing the results would be more likely. If they are carefully designed enough, they might be able to point towards one kind of mask being more effective than the other; but proving they don’t work at all is going to be next to impossible. Field studies just can’t be controlled well enough to overturn something that is already well established.
With that understanding fully in place, let us turn to what is wrong with Rancourt’s first argument.
Failed Argument 1: N95 and Surgical Masks Don’t Work.
Rancourt states the major premise of his first argument plainly: “extensive scientific literature establishes that wearing surgical masks and respirators (e.g., “N95) does not reduce the risk of contracting a verified illness.” But there are essentially four problems with this argument.
Problem 1: Confirmation Bias
Rancourt gives the impression that he is doing a systematic review of the literature, but in reality, he is merely selecting and citing studies that (he thinks) support his conclusion while ignoring those that do not. The CDC, for example, lists 19 studies that Rancourt ignores, all of which not only contradict his conclusion but are more recent than any study he lists. He also ignores all the evidence I mentioned above, not to mention these four that directly find that N95 masks do reduce the risk of contracting a verified illness. In logic, we call this confirmation bias–only seeking out evidence that confirms what one wants to believe. And confirmation bias is most effective in leading one astray. Rancourt engaging in it clearly demonstrates he has failed to establish that the scientific consensus comports with his conclusion that by “making mask-wearing recommendations and policies for the general public, or by expressly condoning the practice, governments have…ignored the scientific evidence.”
Problem 2: The Point Is Irrelevant; He’s Equivocating
As I made clear in the last section, the scientists who have advocated for universal public mask-wearing during the COVID-19 pandemic have not claimed that by wearing a mask, an uninfected person protects himself or herself from becoming infected. Instead, scientists claim it helps prevent those who are infected from spreading their infection to others, by spraying infected droplets and aerosols into the environment—what is known as source contamination. The fact that they don’t protect wearers all that well is why it has not generally been recommended that healthy people need to wear masks in public during, say, flu season. Those who are sick should wear them, to keep from spreading whatever they have around, but for healthy people, it is overkill.
However, with most diseases it becomes clear, pretty early on, when a person is sick. Once we realized that with COVID, people could be infected and infectious for days without knowing (some even never developing symptoms), everything changed. It made sense to ask everyone to wear a mask, to make sure that everyone who didn’t know they were sick was wearing one.
If keeping the wearer from getting sick is how masks help prevent the spread of COVID, then the thesis of the entire first section of Rancourt’s article—that “wearing surgical masks and respirators (e.g., “N95”) does not reduce the risk of contracting a verified illness”—is completely irrelevant to the issue of whether mask mandates help reduce the spread of COVID. Even if it were true that masks do not protect those who wear them, it would still be true that public laws requiring masks help by mitigating the spread of COVID by helping prevent those who are infected (especially without knowing they are) from transmitting it to others. Thus, the evidence Rancourt provides here is completely irrelevant to the issue.
To help illustrate Rancourt’s mistake, let us return to our analogy. Suppose, to challenge your idea that Kevlar vests are safe and effective, a man named Dennis cited a study that showed that Kevlar vests can’t keep you warm in a blizzard. While that study might be accurate, it is irrelevant to the issue. The issue is whether they can stop bullets, not keep you warm. In the same way, studies about the effectiveness of mask to prevent infection in the wearer are irrelevant to the issue of whether they are able reduce source contamination. In other words, if public health officials say that you wearing a mask helps protect others, citing a study saying that you wearing a mask doesn’t protect you, is irrelevant. In logic, we call this a non-sequitur.
This error actually haunts Rancourt’s entire article because almost all the evidence he presents is about masks not protecting the wearer; he says very little that’s relevant to whether they protect others from the wearer. Indeed, the entire article is essentially one giant equivocation. He says masks “don’t work,” but what does he mean by “work?” If he means cloth masks don’t protect the wearer very much–yeah, we already suspected that (although, as I mentioned above, some new evidence points in a different direction). But if he means they don’t protect others, he needs to provide evidence. What “work” in the title means is the latter, but then all he really provides evidence for is the former. This is like titling an article “My Kids Don’t Work” to try to motivate your biological children to get a job, and then writing an article about how your young pet goats are unemployed.
Problem 3: The Studies Rancourt Cites about N95s Don’t Actually Support His Claim
Rancourt claims that the medical literature shows that “wearing surgical masks and respirators (e.g., “N95”) does not reduce the risk of contracting a verified illness.” Most of the studies he cites, however, are not only contradicted by many others,  but merely show that the effectiveness of N95 and surgical masks is roughly the same. Obviously, the fact that they work equally well doesn’t mean that they don’t work at all (or that cloth masks don’t work at all).
Now, in a way, Rancourt anticipates this objection when he states “if there were any benefit to wearing a mask, because of the blocking power against droplets and aerosol particles, then there should be more benefit from wearing a respirator (N95) compared to a surgical mask.” If that were true, then the studies he cites would be relevant to whether masks offer protection. But it is not. Even if N95 masks offer no more protection than surgical masks, it would not follow that cloth masks don’t offer protection. Why?
With most protective gear, as you increase the quality or quantity of the gear, there is a gradual increase in its effectiveness. But once you reach a certain point, increases in effectiveness slow and eventually become insignificant, such that there is no longer a benefit to having even higher quality. (It’s a bit like, but not exactly like, diminishing returns.) So if the quality of masks levels off at a certain point, in such a way that N95 masks don’t offer that much more protection than surgical masks, that would not be completely surprising–and it certainly wouldn’t show that cloth masks provide no protection.
To illustrate this logical error, let us return to the Kevlar vest example. A vest with Kevlar that is, say, 1mm thick will clearly be less effective than one with Kevlar 2mm thick; and 2mm will be less effective than 3mm, etc. But at some point, continuing to increase the thickness will be unhelpful. For example, 7mm of Kevlar will likely stop all the same bullets as 14mm. A study that showed that 7mm and 14mm thick vests offer the same protection might not be surprising—but it certainly wouldn’t entail that there is no protective benefit to wearing a bulletproof vest. In the same way, a study that shows N95 and surgical masks offer around the same amount of protection doesn’t indicate that there is no protective benefit to wearing a cloth mask.
To make matters worse, he basically just misrepresents the findings of all studies he cites. Consider Smith’s study. While this study does compare the effectiveness of N95 and surgical masks, it admits that it doesn’t prove that they do offer equal protection—just that the available evidence so far is inadequate for proving that N95 masks offer more protection in a clinical setting.
“Although N95 respirators appeared to have a protective advantage over surgical masks in laboratory settings, our meta-analysis showed that there were insufficient data to determine definitively whether N95 respirators are superior to surgical masks in protecting health care workers against transmissible acute respiratory infections in clinical settings.”
However, even though it was not enough to prove they were superior, they did find that “In general, compared with surgical masks, N95 respirators showed less filter penetration, less face-seal leakage and less total inward leakage under the laboratory experimental conditions described.” This study is far from the proof that N95’s don’t work better than surgical masks that Rancourt claims it is.
Or consider Offedu’s study. Again, this study is about whether N95 and surgical masks protect their wearer, but it found that N95 masks do protect better than surgical masks against clinical respiratory illness, just not against viral infections and influenza-like illness; N95s and surgical masks seem to protect equally well in that regard. Rancourt takes the quote about this, “Evidence of a protective effect of masks or respirators against verified respiratory infection (VRI) was not statistically significant,” out of context to make it seem like it is about the effectiveness of masks. What’s more, the study specifically found that masks and respirators do protect against SARS (which, again, is the closest thing to Covid-19). Indeed, it specifically stated that “This systematic review and meta-analysis supports the use of respiratory protection.”
Consider Radonovich’s study. While it too is about the effectiveness of N95 and medical masks, it’s about the flu—not SARS, so its findings really can’t be transferred over to COVID. Also, the author admits, the non-difference could just be due to the N95’s not being properly sealed or used. Something similar is true of Youlin’s study, which is also only about the flu—not SARS—and merely suggests that N95 masks should be reserved for health care workers in the most high risk situations—not that cloth masks can’t filter out droplets.
Problem 4: The Other Studies He Cites Actually Prove Him Wrong.
The other studies Rancourt cites actually contradict his thesis. Now, he says they support it–but to make it seem so, he takes quotes from them out of context and/or ignores findings in the paper that discredit his thesis. Take for example his quote from bin-Reza, the only one Rancourt mentions from that paper:
“None of the studies established a conclusive relationship between mask/respirator use and protection against influenza infection.”
Given that it appears in the section of his paper where he is arguing that masks don’t work, his quoting of this line from the study implies that the authors intended this statement to mean there is no benefit to wearing masks. In reality, however, the slash in the “mask/respirator” phrase is meant to indicate a comparison between the two types of facial coverings. The study is not lumping them together and declaring them both ineffective; the study actually concludes that masks and respirators are equally effective. Several of the sentences before and after the one he quotes demonstrate this. For example,
“Eight of nine retrospective observational studies found that mask and ⁄ or respirator use was independently associated with a reduced risk of severe acute respiratory syndrome (SARS).”
What’s more, the part of that study Rancourt cities is about influenza, not COVID—and the authors themselves specifically state that their findings about influenza cannot be extrapolated to SARS-CoV-1. “SARS is an unusual acute viral respiratory infection with a very different epidemiology to almost all other respiratory viral infections. It is fundamentally different from human inﬂuenza.” But SARS-CoV-1 is now know to be very similar to SARS-CoV-2 (the cause of COVID-19); and about SARS-CoV-1 this study “found that mask and ⁄or respirator use was independently associated with a reduced risk of severe acute respiratory syndrome.”
Or take Cowling’s article. The part of that study Rancourt mentions is about whether masks (in this case, cloth masks) protect their wearer from infection, not whether they filter exhaled air and thus protect others. So it is irrelevant to his thesis. What’s more, the authors admit that the body of evidence they are examining is not sufficient to draw a conclusion, but they also suggest that the evidence that does exist at least suggests that cloth masks do provide some protection for their wearer—probably not enough for a healthcare setting but maybe enough for household use. They recommend further study on this topic. The part of the study that Rancourt doesn’t mention is the part that examines whether cloth provides protection to others by filtering air, and they conclude that they do. “There is some evidence to support the wearing of masks or respirators during illness to protect others, and public health emphasis on mask wearing during illness may help to reduce influenza virus transmission.” Again, in logic, we call this “confirmation bias.
Lastly, consider Jacobs’ article: This study showed that N95 masks cause headaches in some, and that (surgical) facemasks don’t protect their wearer. This only tells us what we already know: Wearing a tight banded mask on your face for 12 hours is bound to cause headache, and surgical masks don’t provide adequate protection in high risk environments. Since both findings are irrelevant to whether cloth masks filter outgoing particles, this study is irrelevant to his thesis. About Rancourt’s use of his study, in correspondence with me, Jacobs said
“Dr. Rancourt’s opinion piece mischaracterizes the research findings I reported in my 2009 peer-reviewed article…. It was not designed to examine mask effectiveness of preventing the mask-wearer from spreading a respiratory infection. My study has no bearing on addressing that recommendation. My study was statistically powered to detect a difference between the two groups. There was no such difference in number of colds detected, which is not the same as determining there is no difference. It was not sufficiently powered to conclude that the absence of a difference meant there is no difference. This is termed ‘non-inferiority’, and requires a much larger sample size and/or longer study duration.”
So, of the studies Rancourt cites, none of them provides any evidence to support his claim that masks do not work in reducing the spread of viruses, and several of them provide evidence that they do. This is important, not only because it shows his thesis to be unsupported, but because it establishes a pattern of academic recklessness that makes Rancourt untrustworthy.
Indeed, he did this again in my debate with him when he cited the Xiao. “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.” He left out the part where the study admits that the trials in looked at were flawed, and that conclusions can’t be drawn from them—which makes sense since they also entailed that handwashing is useless. And he also didn’t cite the part that says:
“There are still few uncertainties in the practice of face mask use, such as who should wear the mask and how long it should be used for. In theory, transmission should be reduced the most if both infected members and other contacts wear masks, but compliance in uninfected close contacts could be a problem. Proper use of face masks is essential because improper use might increase the risk for transmission. Thus, education on the proper use and disposal of used face masks, including hand hygiene, is also needed.”
The authors of the study were not convinced by it that masks don’t work, and Rancourt’s specialization in metals doesn’t qualify him to draw a different conclusion.
Consider our Kevlar vest analogy once again. Suppose, this time, to challenge the idea of Kevlar vest safety and effectiveness, our friend Dennis quotes a RCT which, he says, proves they don’t work. He even quotes from the conclusion: “Kevlar vest use did not reduce death or major traumatic injury in subjects after being shot in any randomized evaluation of this intervention.” What would you think? Like we discussed before, you would probably think it was flawed. “Did a random variable throw it off?” You’d want to take a closer look.
But suppose when you did, you found that—right after the sentence that Dennis quoted—was the sentence: “However, the trial was only able to enroll participants willing to be shot by rubber bullets at a distance of 50 yards; the authors causation against extrapolating from this study anything regarding real world use of Kevlar Vests.” Clearly, that explains it. This study proves nothing.
But now a new question arises. Why did Dennis leave that part out? Does he work for some lobby that has it out for Kevlar vests? Whatever the reason, you would rightly no longer trust him to provide reliable information about the results of studies. This would especially be true if he did this same kind of thing, seven or eight times over. He already gave you irrelevant studies; now he’s just blatantly misrepresenting them. I don’t care how many more studies he cites, at this point I’m not going to believe that they show or entail what he says they do.
In our debate, when I called him on this, and finally got to essentially admit that he had done it, he said that he was just “interpreting” the studies. But as a physicist who specialized in metals, he is not qualified to interpret the findings of medical studies—certainly not more qualified than the people who wrote the paper whose findings contradict his. What’s more, a study to determine X can only demonstrate X, not some other thing Y. It might suggest to you some other conclusion Y, but it cannot determine whether Y is true. For that, you would need to do a separate study on Y. Scientific studies are not short stories. You can’t “interpret” them to mean whatever you want them to mean.
Failed Argument 2: Humidity Causes Seasonal Variation, So Masks Can’t Help
Everyone knows that colds and the flu “go around” more in the winter. This is one reason flu shots are given in the fall. But explanations for this seasonal variation vary widely. Your mother perhaps told you that “being cold makes you get a cold.” This is why you were instructed not to go outside with wet hair. Since, of course, we now know that tiny organisms like viruses cause disease, we know that “being cold” does not. Other proposed explanations vary from “people are indoors more in the winter,” to “soft tissue irritation,” to “lack of sunlight (which causes a vitamin D deficiency).” But in 2010, Shaman suggested something else: variations in humidity. Air is humid in the summer, dry in the winter, and (so the theory goes) viruses spread more easily from person to person in dry conditions.
Now, I don’t know whether Shaman’s hypothesis has gained a consensus in the scientific community; I have not reviewed all the relevant research. What I do know is that, contrary to Rancourt’s suggestion, even if Shaman is right, it does not follow that masks don’t help prevent the spread of viral contagions—that a second wave of COVID could not be a “consequence of human sin regarding mask wearing and hand shaking [but instead] an inescapable consequence of an air-dryness-driven many-fold increase in disease contagiousness, in a population that has not yet attained immunity.” What’s more, Rancourt’s argument suggesting it does is fundamentally flawed. There are essentially two main problems to point out.
Problem 1: Oversimplified Cause
The first mistake is not easy to explain. Rancourt claims that, if Shaman’s humidity hypothesis is correct, then COVID’s basic reproduction number (R0) (which reflects how many people, on average, each sick person infects) is “highly or predominantly dependent on ambient absolute humidity.” Consequently, “all the epidemiological mathematical modeling of the benefits of mediating policies (such as social distancing [or masks]), which assumes humidity-independent R0 values, has a large likelihood of being of little value” because “the seasonal infectious viral respiratory diseases that plague temperate latitudes every year go from being intrinsically mildly contagious to virulently contagious, due simply to the bio-physical mode of transmission controlled by atmospheric humidity, irrespective of any other consideration.”
While that sounds convincing, it shouldn’t convince you. Why? That last phrase is key: “irrespective of any other consideration.” Not quite. Even if humidity has been the most causally efficacious factor when it comes to how fast viral infections in the past have spread, it does not follow that there are no other causal factors (even if those causal factors have been constant in the past). Consequently, it does not follow that guarding against other factors can’t reduce the infection rate—especially if we have not taken such precautions in the past.
To illustrate the cognitive mistake, consider a first-time skier. He goes out the first day and comes back soaked to the bone. Undeniably, it’s the snow that made him wet, but if he just shrugged his shoulders and said “Well, if I’m going to ski, there is going to be snow, so I guess I’ll just have to be soaked every day,” we would call him a fool. Of course the snow made him wet, but a simple pair of rubber ski pants will keep him dry. In the same way, even if humidity is a factor in transmissibility, so is droplet and aerosol spread. So you can limit transmissibility, even if you can’t change the humidity, by limited droplet and aerosol spread.
In giving the skier analogy, I was not trying to compare snow with viruses; I was demonstrating Rancourt’s logical mistake. The fact that some thing X is even the main cause of a problem Y doesn’t mean that the only way to solve Y is by removing or changing X; because causation is complex, usually the problem can be mitigated by taking some other precaution, or action, Z. For example, the fact that a river’s physical attributes are primarily what determine its speed doesn’t mean that you can stop it by building a dam. Likewise, even if a lack of humidity in the winter has been the main cause of the uptick in winter viral spread in the past (and you can’t change the humidity), that doesn’t mean that you can’t mitigate the spread of the virus by taking some other precaution (like mandating masks).
But if you would like a more direct analogy, suppose we tried to mitigate the spread of the flu by locking everyone in the world in their home, in separate rooms, for two months. This would, of course, be overly draconian, and a really bad idea for multiple reasons–but it undoubtedly would stop the spread, and indeed most likely wipe out the disease. It would run its course in all infected persons, either killing them or being killed by their immune systems, and then be done.
But notice how stupid someone would seem if they came out and said, “such efforts will have no effect at all on the spread of the disease at all because isolating people won’t affect the humidity.” Even if humidity is normally a major factor in transmission, there are other things at play: like how we are exposed to others who are infected. If we limit that exposure by locking everyone in their room—or, less drastically, we simply encourage people to social distance and wear masks—we will lessen the spread. even if the humidity levels are unaffected. So Rancourt’s argument here suffers from the most basic of logical flaws: he simply failed to recognize that there is more than one causal factor when it comes to viral spread. In logic, we call this the fallacy of oversimplified cause.
Problem 2: What’s Happened Since: Wide-spread Infection in Humid Months
The second problem with Rancourt’s humidity argument begins with realizing that Shaman himself has admitted that we don’t know enough about COVID to conclude that humidity is a factor in its transmission. Others, like Rachel Baker, who studies how climate affects infectious disease for a living, has argued that it likely is not—at least, not yet. From the same article:
“Rachel Baker, lead author of a new article in Science and a researcher at Princeton University who studies how climate affects infectious disease, said the main conclusion is that in a pandemic like the one we’re in now, what decides how quickly the new virus spreads is how many people are susceptible, or not immune, to it. Climate would play a bigger role only as more people become immune.”
And what has happened since Rancourt wrote his argument in April of 2020 seems to suggest that she is right. The infection rate in states that ignored social distancing and mask guidelines have skyrocketed in the hottest, most humid times and places (e.g., Florida and Texas in July). So either humidity doesn’t affect COVID at all, or it does and we really need to start wearing masks—because this winter is going to be brutal!
Failed Argument 3: Particles that transmit the virus are too small to be blocked by masks.
The major premise of this argument is that the COVID virus, or more specifically the droplets that carry it, are aerosol particles that are too small to be blocked by cloth masks and thus masks cannot provide protection. He tries to establish this by claiming that aerosols can’t even be blocked by N95 masks; if that’s true, how could cloth masks possibly provide any protection? But, as you might have guessed, there are serious flaws with this argument too—flaws so severe that each renders it impotent. I will explain four of them.
Problem 1: It’s Not Just Aerosols (And Even If It Is, Masks Still Work)
Rancourt’s argument in this section relies on the assumption that practically the only method of transmission for COVID is aerosols. Indeed, in the video that accompanies his article, he says:
“We have known for a decade now that the main transmission route of all of these types of viral respiratory diseases, is very fine aerosol particles, that are supported as part of the fluid air. … It’s not about droplets, it’s not about spitballs, it’s not about surfaces, and fomites, and all that kind of stuff –that has nothing to do with it. It’s all about buildings where you have fine aerosol particles suspended in the air of the building—they can be measured, they are in high concentration—that’s where the transmission occurs.”
This is most likely false. We certainly have not known this “for a decade now.” The role of droplets, aerosols, and fomites in the transmission of the flu is still hotly debated, much less COVID. These things are difficult to study. As Fineberg put it, “for no respiratory virus is the exact proportion of infections due to air droplet, aerosol, or fomite transmission fully established,
and many individual factors and situations may contribute to the importance of each route of transmission.” And there most certainly is no peer reviewed evidence (much less a RCT) that proves that aerosols even are a mode of transmission for COVID, much less the only one. As Dr. Josh Santarpia put it, “To my knowledge, there is no definitive evidence of transmission where aerosol was the only possible route.”
Now, there are some anecdotal studies which suggest that COVID might also be transmissible through aerosols. But first, those studies admit that it may only be to those who are susceptible—because the viral load in aerosols is so low. Only around 1 in 700 aerosols that leave an infected person’s mouth have a single virion in them. What’s more, because the assumption that droplets only travel around six feet is based on outdated studies, these anecdotes could be explained by droplet exposure. 
On top of that, while it is true that, numerically speaking, aerosols likely make up the majority of the particles that exit your mouth, they only make up a tiny fraction of the material that leaves you mouth. Most of that is droplets; that’s where most of the viral load is carried. Indeed, not do only 1 in 700 aerosols that leave an infected person’s mouth have even a single virus in them, but the only aerosols that could have more are those that started out as larger droplets (e.g., 50-100 microns, with a number higher virus load) that evaporated down (i.e., aerosolized) after they left your mouth. This is important because, as I explained in the first section, masks unquestionably capture such droplets. So even if aerosols are the only mode of transmission, contrary to what Rancourt says in this section of his paper, masks would greatly reduce the number of aerosols in the air, and thus reduce the risk of infection.
Think of it this way. Even if 10 micron and lower aerosols are the only mode of transmission, masks can reduce risk. Why? According to Dr. Jeffry Martin, “persons who have a member of their household infected with the virus have a higher probability of getting infected with COVID …This tells us that close contact is the most important factor.” If an infected person releasing aerosols is what makes such long personal interactions more risky, it would be because the more aerosols you are exposed to, the more likely you are to be infected—either because of increased viral load, or increased risk of inhalation. Since most masks can filter even the 10 micron particles to some degree, they reduce risk. And even if they can’t, they still block the larger more potent droplets and prevent them from evaporating and becoming more potent 10 micron aerosols. And since those particles would be what are carrying majority of the viral load, masks would still greatly reduce risk.
To be clear, I’m not saying aerosols are not a mode of transmission. They likely are. But they are almost certainly not the only mode (such that, all other modes are irrelevant); and even if they were, masks would still help. This is contrary to all the assumptions that Rancourt makes on this issue.
Problem 2: Rancourt’s Argument for Aerosols Being The Main Mode is Faulty
If humidity affects the transmission of viruses, it’s not clear how it does so. Two possibilities that Rancourt mentions are “viable decay” and “physical loss.” If it is viable decay, flu spreads less in the summer because humid air deactivates viral-pathogen-carrying droplets more quickly than dry air. If it’s physical loss, then the humidity physically removes such drops from the air (by keeping them from evaporating and aerosolizing as quickly).
The reason this matters is because Rancourt himself admits that his argument that masks can’t filter particles infected with COVID (because they are too small) is dependent on the “physical loss” explanation.
If my view of the mechanism is correct (i.e., “physical loss”), then Shaman’s work further necessarily implies that the dryness-driven high transmissibility (large R0) arises from small aerosol particles fluidly suspended in the air; as opposed to large droplets that are quickly gravitationally removed from the air.
The humidity hypothesis itself doesn’t turn on which mechanism it is, but his argument that the primary mode of transmissibility is aerosols does. But there is no good reason to think the physical loss explanation is right.
First, the author of the study that Rancourt himself cites (Harper, 1961) argues for the “viable decay” hypothesis and regards the physical decay hypothesis to merely be possible. And to think that something is true, merely because it is possible, is (cleverly called) the “appeal to possibility” fallacy. Possible things might be true, but the fact that they are possible doesn’t entail they are.
Second, Rancourt doesn’t actually provide any evidence for the physical loss theory. He merely states that it “seems more plausible” to him, and that he finds it “difficult to understand” how the viable decay hypothesis could be true. Needless to say, the fact that Rancourt can’t understand something is not a good reason to think that it is false. (By the way, thinking something is false because you can’t understand it is called the “appeal to personal incredulity” fallacy.)
So the assumption that Rancourt makes in this argument, that aerosols are the only significant mode of transmission for COVID—which, even if true, doesn’t mean that masks don’t work—is at best based on another unsupported assumption that the authors Rancourt himself cites consider implausible.
Problem 3: Either A Mistake in The Math or Basic Immunology
Rancourt’s argument is not well organized or well written, and it is difficult to parse sometimes; but it seems that he has made a fundamental mathematical mistake that completely invalidates his argument. To begin to see why, recall that one of the major premises of his third argument is that not even N95 masks can block viruses. To establish this, he argues that the pores in N95 masks are too big to block the virus. He says.
“…indoor airborne virus concentrations have been shown to exist (in day-care facilities, health centers, and on board airplanes) primarily as aerosol particles of diameters smaller than 2.5 μm [microns]…Such small particles (< 2.5 μm) are part of air fluidity, are not subject to gravitational sedimentation, and would not be stopped by long-range inertial impact. This means that the slightest (even momentary) facial misfit of a mask or respirator renders the design filtration norm of the mask or respirator entirely irrelevant. In any case, the filtration material itself of N95 (average pore size ~0.3−0.5 μm) does not block virion penetration, not to mention surgical masks.
Initially when I read this, I was confused. Clearly, a 2.5 μm particle is much bigger than a 0.3 (or 0.4, or 0.5) pore. So how can he possibly be claiming that the 0.3 μm pores in N95 masks are too big to block 2.5 μm particles? And then it dawned on me. Yes, 2.5 is greater than 0.3–but it’s less than 3! It seems he didn’t notice the decimal. He thinks that a 0.3 μm pore won’t block a 2.5 μm particle because 3 is a greater number than 2.5.
The only other possibility is that he is first saying that N95 masks can’t block particles smaller than 2.5 μm if they are misfit—which, of course is true; that’s why N95s are usually tested for proper fit. Then he makes a separate point that, even if they are properly fit, it doesn’t matter because the pore size of an N95 (which is approximately 0.3−0.5 microns) is bigger than the virus itself (which is about .125 microns). If so, there is no math error—but his point is entirely irrelevant because the virus never travels alone; it always travels in droplets! This is immunology 101. So either he is making a basic math error, or a basic immunology error.
What’s more, even a virus was traveling alone, N95s (and in fact cloth masks) would be exceedingly efficient at capturing them because of Brownian Motion. In other words, as I shall now show, Rancourt doesn’t even understand the physics behind how N95s work—which is ironic given that, if his academic training in physics is relevant to anything in this debate, it would be this.
Problem 4: Rancourt Doesn’t Understand How Masks Work
“Brownian Motion” refers to the erratic way that such small particles zig-zag around due to their interaction with the surrounding gas atoms and molecules in the air. Essentially, they are so light, that they are easily pushed around by such things. Since the motion of molecules and atoms in a gas is chaotic and random, particles smaller than 0.3 μm dance around in the air randomly as they interact with them.
This makes much easier to capture because they don’t travel in a straight line. If N95 masks were a woven porous sieve, and these particles just traveled in a straight line, yes they would be basically impossible to catch. But not only do they not travel in straight lines, N95 are not made sieve’s made of woven material; they are usually made of synthetic plastic fibers. Now, there are spaces between the fibers, but they are twisted and compressed together in such a way that it essentially creates a maze that most particles can’t pass through. Gasses, like 02 and CO2 can—that’s why you can still breathe while wearing one. But particles, especially those dominated by Brownian Motion, bouncing around like crazy, cannot.
The hardest particles to catch are those that are just big enough to not be dominated by Brownian Motion—that is, the smallest particles that aren’t bouncing around like crazy but do generally travel in a straight line. They are around 0.3 microns. But still, N95s have been shown to capture 95% of such particles; that’s where the “95” in their name comes from. Surgical masks, which are not woven, can also capture particle 0.3 microns and below—although yes, less efficiently. And so can cloth masks. Single layer cotton cloth masks don’t do very well with particles that small, but layering the cloths creates similar convoluted pathways for the particles to travel through, especially when you combine them with non-woven fabric, like flannel. As I pointed out in the first section, Konda found that such masks filtered 80% of particles smaller than 0.3 microns and 90% of those larger.
So Rancourt’s claim that the particles that the virus travel in are just too small to be stopped by a mask demonstrates a fundamental misunderstanding of the physics of how masks work. Thus it is a baseless claim.
Failed Argument 4: Masks Can’t Guarantee 0% Exposure, Thus They are Useless
In his final argument, Rancourt suggests that masks can’t work because they are not 100% effective at stopping infected droplets. Why must they do so? Because, he says, the minimal infective dose (MID) for COVID is really low; exposure to just one infected droplet, with only one virus in it, will make a person sick. And so, he says, “the studies that show partial stopping power of masks, or that show that masks can capture many large droplets produced by a sneezing or coughing mask-wearer…are irrelevant.” But, again, his argument is fundamentally flawed. There are essentially three problems with his argument.
Problem 1: No Evidence for COVID’s Minimal Infective Dose (MID)
First of all, he provides no direct evidence for COVID’s MID. He, instead, cites a study from 2011 (by Yezli and Otter) about influenza. But, as we have discussed, COVID is a very different disease that affects those it infects in many different ways (for example, it seems to affect blood vessels and cause blood clots). So influenza’s MID can really only point in the direction of COVID’s MID, at best.
Second, he merely states that “It is believed that a single virion can be enough to induce illness in the host.” But of course a belief is not evidence. He quotes Zwart et al. (2009), saying his study on a virus-insect system showed that “the action of a single virion can be sufficient to cause disease.” However, the fact that something can be sufficient to cause something, doesn’t mean that it is or will in all or even most cases.
And the other evidence he provides, like from Baccam et al. (2006) and Brooke et al. (2013), only talk about how quickly or efficiently viruses reproduce in cells once they are infected–not the probability of cells becoming infected once exposed. So, once again, Rancourt is “interpreting” studies to make them show what they don’t.
Problem 2: He Overestimates Viral Load and its Threat
Rancourt’s paper is so poorly written, it’s sometimes difficult to tell what exactly he is saying or suggesting. For example, to “point out the relevant features” for his statements about the MID of COVID, he provides a bulleted list from Yezli and Otter. But he does not provide page numbers or quotation marks, so it is impossible to tell whether these are direct quotes or summaries of their work. For example, point number six is just “For further background:” and then the next points mention other authors. Are these other authors mentioned by Yezli and Otter? Or is he just summarizing other sources? It’s impossible to tell.
So when he says, in point four of this list, that “There are typically 10 to 3rd power − 10 to 7th power virions per aerolized [sic] influenza droplet with diameter 1 μm − 10 μm,” it’s impossible to know whether he is quoting Yezli and Otter, summarizing them, or doing his own calculations based on information they provided. But in layman’s terms, this means that there are 1000 to 10 million viral particles, in each infected microdroplet 1 to 10 microns in size. And while it is a statistic about the flu, it is clear that we are meant to infer from it that roughly the same numbers hold for COVID. Not only is Rancourt adamant about how similar the two viruses are, but why else would he bring this statistic up? Indeed, it’s clear that he thinks that every droplet a COVID infected person emits is going to have at least 1000 viruses in it. Hey says that the information in this bulleted list means that, “If anything gets through (and it always does, irrespective of the mask), then you are going to be infected.” (emphasis added). The only way that is true is if every aerosolized droplet is potently infected.
But this is simply not true. Even when coming from an infected person, microdroplets of that size are mostly empty of viruses and contain at most a single viral particle. Why? Because it’s difficult to get coronavirus into a concentration much higher than 10 million per mL. And a 10micron droplet is 0.167 picoliters (4/3 * 5^3 * 10^-18 m^3). A mL is 1 billion picoliters. So for every 1,000 micron droplets that an infected person spews out, only at most 2 (1.67) will have a single virion in it—that’s roughly 1 out of every 600 (which is quite close to the 1 out of every 700 number I cited before). Granted, infected aerosols can hang in the air for a few hours, but given how few of them there are, a person’s mask inability to filter them all doesn’t entail that they “don’t work”—especially if we are talking about the low concentration of infected aerosols there would be in a public space. Add this to the fact that, according to Heneghan, the symptoms that someone suffers is likely proportional to the amount of their viral exposure,  and it becomes painfully clear that the amount that Rancourt is overstating worries about a single infected aerosol making it through is absurd.
Problem 3: The All or Nothing Fallacy
The all or nothing fallacy is a variety of the false dilemma fallacy. One commits the false dilemma fallacy when one suggests that there are fewer options than there actually are. “You are either for us, or against us.” No, actually, I could just be neutral, or not care. The all or nothing fallacy presents a false dilemma by suggesting that there are only two options—either all or nothing—when in fact there are many more options in the middle ground between those two extremes.
The fallacy is very common when talking about the effectiveness of laws. Take seat belt laws, for example. Some people ignore them, and other times they are not enough to save the person’s life. But they undoubtably decrease the number fatal accidents. The same is true of speed limits. They do not prevent everyone from speeding and cannot eliminate all car crashes. But no one would argue that speed limits are useless and that we should not even bother with them because they do no good. They reduce the amount of speeding and thus make the roads safer. Or think again about our Kevlar vests. They are fall from perfect; they leave your head exposed, and can be pierced by “armor piercing bullets. That doesn’t mean they aren’t safe and effective, or that they don’t offer protection.
In the same way, masks cannot eliminate COVID infections; even if everyone is wearing a mask, some people will still get infected, because masks are not perfect. They do let some particles through. Some people will ignore the ordinance, or wear them improperly, for example, by leaving their nose hanging out the top. But if masks are mandated, more people will be wearing them, and wearing them properly. This will reduce the number of infected droplets in the air. And if you still happen to be exposed to one in the air, wearing one can reduce your chance of exposure (although it would depend on the mask). Thus, even though they cannot eliminate it, mask mandates will reduce the probability of infection, and thus the number of people infected.
Or to put it another way—covering your mouth when you sneeze is imperfect, too. Droplets will still escape. That doesn’t mean that you shouldn’t do it or that it doesn’t reduce the chance of infection.
Rancourt’s Concluding Arguments: Biases and Mask Risk
Rancourt finishes his article by claiming that no “bias free” study could ever show that mask mandates are effective. But that “bias free” phrase is doing a lot of work. Notice that, if any such study ever came out, he would just claim that it was biased and dismiss it. He has just built into his argument what logicians call an “ad hoc” excuse–an unfalsifiable way to excuse away any contrary evidence. It is a telltale sign of pseudoscience and irrationality.
Now if by “bias free” he just means RCT, as in any study that is not a RCT is biased, he is simply misunderstanding the nature of science and scientific reasoning. As I mentioned before, RCTs are neither needed or appropriate to answer all scientific questions.  Indeed, they have amazing limits, can be very misleading, and (as Rancourt has himself proved) they are also very easy to cherry pick in nefarious ways to make them seem like they support conclusions they don’t.  When it comes to things like masks and bullet proof vests, which we already know work, more RTC’s would be basically useless.
He also suggests that no such study could be done because “Mask-wearing is associated (correlated) with several other health behaviors” and “The results would not be transferable, because of differing cultural habits.” But, of course, these are simply things that such studies would have to take into account and control for. It does not mean they cannot be done. Indeed, you could say the same thing about cigarettes—but that doesn’t mean we can’t know that they increase the risk of cancer.
He also lists a number of “unknown risks” to mask wearing, suggesting that the risks of a mask mandate would outweigh its benefits. But not only are the supposed risks he lists miniscule compared to the tens of thousands of lives that mask mandates could save, and the enormous economic benefit that masks could generate by allowing businesses to open up without major risk; these worries are also completely unfounded. In my debate, as evidence of their dangers, he mentioned a story he heard about someone passing out while driving and wearing a mask. For someone who demands RCT’s before believing anything, it certainly seems strange to trust such anecdotal evidence. (People pass out while driving everyday; with mask wearing now common, such a story is no surprise.) Essentially, his epistemic standards are backwards. He demands impossible evidence for what he doesn’t want to believe, and no evidence for what he does. This is like refusing to believe that Kevlar vests are safe and effective because no RCT’s have been performed, but then believing they are dangerous because you heard a story about a guy who died while wearing one. It’s absurd.
What’s more, his worries about mask dangers completely contradict his thesis. You can’t think masks are not effective but at the same time they are dangerous. Why? Because gases are finer than particles. If a mask is so porous or loose-fitting that it lets disease carrying aerosols into the air as freely as if you were not wearing it at all, there is no way that it can trap CO2 or keep you from taking in Oxygen. If it is so tight and non-porous that it traps CO2 and won’t let in oxygen, there is no way it is letting even a single aerosol into the air.
Ironically, Rancourt accuses those advocating for masks of manipulating people’s fear. But, at the same time, he is arguing that having a cloth over your face is deadly and dangerous. There have been, as of this writing, 648,000 confirmed deaths from COVID worldwide. The real number is likely higher. There have been zero confirmed deaths from people wearing masks. And healthcare workers have been wearing them, for hours a day, for a century. But Rancourt wants you to be afraid of masks? Who, I ask you, is stoking irrational fears?
Before the debate, I half expected Rancourt to argue that masks can’t help stop the pandemic because there is no pandemic. As he said in a YouTube video.
This year, this winter, under COVID 19, there have not been more deaths than usual…Is something special happening? It’s not. That’s the first point I want to make. This is not a killer pathogen that is unusual in terms of how many deaths it causes.”
Of course, the fact that COVID didn’t really take off with gusto until the winter was almost over (for example, the first 100 deaths didn’t happen in the U.S. North America until March 17, and winter ends on March 20) makes his claim about there being no “winter burden” completely irrelevant to whether or not there truly is a pandemic. There was a huge winter burden, in places were the virus took hold early, and there was a huge number of excess deaths elsewhere in the spring. But that doesn’t keep him from concluding that…
Nothing special happened. It was a fake event, if you like, in the sense that it was given a special name and used in propaganda to frighten us to make us think that there was a particularly dangerous thing happening, that was very unusual, that was unseen previously. That’s all a big lie. I’m personally very convinced of this. I’ve looked at all the data…this has been a huge fabrication.
Now he is willing to admit there was a peak of deaths, in some places, after the pandemic was declared. This is what he calls “the COVID peak.” But about these peaks he says two things. First, it’s never big enough to actually make the total number of excess deaths rise.
“The area of the peak [of deaths] is not big, because it’s so narrow, so you don’t have a total number of extra deaths that’s significant.”
According to Rancourt, a few people who would have died later just died a little bit sooner. So there is no pandemic.
What’s more, the peak was not due to COVID, but instead was the result of government lockdowns. We isolated them, stressed them out, and compromised their immune system. Never mind, of course, that states which didn’t do lockdowns are now seeing much worse outbreaks than those who did. Rancourt wants you to believe that the government only wants you to wear a mask to “hide its crimes.”
“How do you cover that up? You convince everyone that this was a really dangerous pandemic. What’s the best way to convince everyone that we really had a killer here?…well, convince them that they have to wear a face mask. If you as an individual are so frightened that you are going to put a face mask on in the middle of summer, you are personally investing in the belief of that lie. And that’s a powerful psychological way of convincing you that there was this danger….and [that] the government didn’t do anything wrong.”
Given the kind of thinker that such statements demonstrate Rancourt to be, I have no illusion about convincing him that that he is wrong. You can’t reason someone out of a position they didn’t reason themselves into. Doubting the scientific consensus is clearly part of his identity, and when a belief is tied to someone’s identity, presenting evidence against is likely just going to backfire. Indeed, Rancourt seems to be the poster child for the Dunning-Kruger effect, and the fact that intelligence alone doesn’t make one adept at avoiding bad arguments–but instead, makes one better at creating fallacious (but seemingly convincing) arguments for false conclusions. As an old philosophy professor once said of a fellow student of mine, “He’s just smart enough to be dangerous.” Indeed, I don’t want him to read this. All he will do is produce a whole list of ad hoc excuses to explain away his errors, or go on to mischaracterize a list of other studies.
My hope is simply that others will see this article, realize how clear cut the case for masks is, and how dishonest the arguments against them are—and then wear them until the pandemic is over. But if you are still not convinced, just think of it this way:
If you wear a mask but they don’t work, who have you hurt?
But if you don’t and they do—you are risking other people’s lives.
Don’t be that person.
Oh, and make sure your mask covers your nose.
 David Kyle Johnson, “Resolved: Public Mask Mandates Assist in Curbing the Spread of Covid-19,” Another Logical Take, July 24, 2020, https://davidkylejohnson.wordpress.com/2020/07/24/resolved-public-mask-mandates-assist-in-curbing-the-spread-of-COVID-19/.
 See Rick Kushman, “Your Mask Cuts Own Risk by 65 Percent,” UC Davis, July 6, 2020, https://www.ucdavis.edu/coronavirus/news/your-mask-cuts-own-risk-65-percent/. Caitlin McCabe, “Face Masks Really Do Matter. The Scientific Evidence Is Growing,” The Wall Street Journal, July 18, 2020, https://www.wsj.com/articles/face-masks-really-do-matter-the-scientific-evidence-is-growing-11595083298 See WH Seto,et al., “Effectiveness of Precautions Against Droplets and Contact in Prevention of Nosocomial Transmission of Severe Acute Respiratory Syndrome (SARS),” The Lancet 361, no 9368 (May 3, 2003): 1519-20, https://doi.org/10.1016/S0140-6736(03)13168-6. and Hiroshi Nishiura, et al., “Rapid Awareness and Transmission of Severe Acute Respiratory Syndrome in Hanoi French Hospital, Vietnam,” Am J Trop Med Hyg 73, no. 1 (July 2005): 17-25, https://pubmed.ncbi.nlm.nih.gov/16014825/. Lijie Zhang, et al., “Protection by Face Masks against Influenza A(H1N1)pdm09 Virus on Trans-Pacific Passenger Aircraft, 2009,” Emerging Infectious Diseases 19, no. 9 (September 2013): 1403-10, https://doi.org/10.3201/eid1909.121765. See Christian J. Kähler and Rainer Hain, “Fundamental Protective Mechanisms of Face Masks Against Droplet Infections,” Journal of Aerosol Science 148 (2020) https://doi.org/10.1016/j.jaerosci.2020.105617. C. Raina MacIntyre, et al. “A Cluster Randomised Trial of Cloth Masks Compared with Medical Masks in Healthcare 1Workers,” BMJ Open 5 no. 4, (2015) https://doi.org/10.1136/bmjopen-2014-006577. This study suggested that 95% of viruses in aerosols could be blocked by homemade masks, and 97% could be blocked by surgical masks: Qing-Xia Ma, et al, “Potential Utilities of Mask-Wearing and Instant Hand Hygiene for Fighting SARS-CoV-2” Journal of Medical Virology (2020) https://doi.org/10.1002/jmv.25805. This is a study out of Hong Kong which suggested that people wearing a mask was very effective at reducing transmission of alpha coronaviruses”; Nancy H. L. Leung, et al., “Respiratory Virus Shedding in Exhaled Breath and Efficacy of Face Masks,” Nature Medicine 26 (2020): 676-80, https://doi.org/10.1038/s41591-020-0843-2.
 See also WH Seto, et al., “Effectiveness of Precautions Against Droplets and Contact in Prevention of Nosocomial Transmission of Severe Acute Respiratory Syndrome (SARS),” The Lancet 361, no 9368 (May 3, 2003): 1519-20, https://doi.org/10.1016/S0140-6736(03)13168-6; see also Hiroshi Nishiura, et al., “Rapid Awareness and Transmission of Severe Acute Respiratory Syndrome in Hanoi French Hospital, Vietnam,” Am J Trop Med Hyg 73, no. 1 (July 2005): 17-25; Harvey Fineberg, Rapid Expert Consultation on the Possibility of Bioaerosol Spread of SARS-CoV-2 for the COVID-19 Pandemic (April 1, 2020), (The National Academies Press, 2020), chapter 1 and 2, https://www.nap.edu/read/25769/chapter/1#2.
 Depending on your definition, aerosols range from around 100 microns to 0.1 micron. “Various sources will put the cutoff at 2 µm, 5 µm, 10 µm, 20 µm, or even 100 µm.” Justin Morgenstern, “Aerosols, Droplets, and Airborne Spread: Everything You Could Possibly Want to Know,” First10EM, April 6, 2020, https://first10em.com/aerosols-droplets-and-airborne-spread/. For simplicity, I’ll define aerosol as a droplet that is 10 µm in size. Brownian motion dominates in particles less than 0.3 µm in size.
 Talib Dbouk and Dimitris Drikakis, “On Respiratory Droplets and Face Masks,” Physics of Fluids 32, no. 063303, published electronically June 16, 2020, https://doi.org/10.1063/5.0015044. Bhanu Bhakta Neupane, Sangita Mainali, Amita Sharma, and Basant Giri, “Optical Microscopic Study of Surface Morphology and Filtering Efficiency of Face Masks,” PeerJ 7,no. e7142 (2019), https://doi.org/10.7717/peerj.7142.
 Cloth masks of only one material seem to have very little effectiveness: Samy Rengasamy, Benjamin Eimer, and Ronald E. Shaffer, “Simple Respiratory Protection – Evaluation of the Filtration Performance of Cloth Masks and Common Fabric Materials Against 20-1000 nm Size Particles,” Annals of Occupational Hygiene 54, no. 7 (October 2010): 789-98, https://doi.org/10.1093/annhyg/meq044. This is why those who are just wearing bandanas or pulling their t-shirt over their mouth, are not doing anyone much good.
 Both types “significantly reduced the number of microorganisms expelled by volunteers,” “the surgical mask was 3 times more effective.”) Anna Davies, et al., “Testing the Efficacy of Homemade Masks: Would They Protect in an Influenza Pandemic?” Disaster Medicine and Public Health Preparedness 7, no. 4 (August 2013): 413-8, https://doi.org/10.1017/dmp.2013.43; Milton (2013) found that surgical masks decreased emission of large particles by 25 fold, and aerosols by 3 fold in flu patients. See Donald K Milton, et al., “Influenza Virus Aerosols in Human Exhaled Breath: Particle Size, Culturability, and Effect of Surgical Masks,” PLoS Pathogens 9, no. 3 (March 2013): 1-7, https://doi.org/10.1371/journal.ppat.1003205.
 Aydin et al. (2020), suggests that layering greatly increases the filtering efficiency of cloth masks while also maintaining some breathability, Onur Aydin, et al., “Performance of Fabrics for Home-Made Masks Against the Spread of Respiratory Infections through Droplets: A Quantitative Mechanistic Study,” medRxiv,preprint, submitted July 8, 2020 https://doi.org/10.1101/2020.04.19.20071779.
 Abhiteja Konda, Abhinav Prakash, Gregory A. Moss, Michael Schmoldt, Gregory D. Grant, and Supratik Guha, “Aerosol Filtration Efficiency of Common Fabrics Used in Respiratory Cloth Masks,” ACS Nano 14, no. 5 (2020): 6339-47, https://doi.org/10.1021/acsnano.0c03252.
 “Overall, we find that combinations of various commonly available fabrics used in cloth masks can potentially provide significant protection against the transmission of aerosol particles.” Konda, “Aerosol Filtration Efficiency of Common Fabrics Used in Respiratory Cloth Masks.”
 Dr. Marty, a professor of infectious diseases at Florida International University told Good Morning America “But if you add that filter, then you’re also adding a really good protection for yourself.” See Becky Worley, Anthon Kane, Robyn Weil, and Angeline Jane Bernabe, “Face Masks With Filter add Another Layer of Protection, Experts Say,” GMA, July 16, 2020, https://abcnews.go.com/GMA/Wellness/face-masks-filters-add-layer-protection-experts/story?id=71811792.
 This is actually what N95 masks are named for; they protect their wearer by being 95% effective at filtering the air that a person breathes in. And because they often have unfiltered exhaust vents, they usually don’t filter the air a person breathes out. Combine that with the fact that they don’t even perform their intended function well unless they are perfectly fit, and you can realize why they should likely only be worn by health care workers in high risk environments.
 Some clarification here is useful. Technically, depending on how you classify “aerosols” (definitions range from 5 microns to 100 microns), most of the particles you breath out could be classified as aerosols–and depending on their size, the mask will filter them with different efficiencies. Even cloth masks are very good at filtering down to 10 microns, pretty good down to 5 microns, but not great below 5. Neupane, “Optical Microscopic Study of Surface Morphology and Filtering Efficiency of Face Masks.”
In one way, this is concerning because according to Burch (2020), the average size for aerosols leaving your mouth is 3 microns. The good news is, despite the fact that they make up the largest number, they only represent 0.00024% of the liquid leaving your mouth during a cough. Consequently, very few of them are infected (at worst 1 out of every 700). A full 99.99976% of the viruses sprayed during a cough are carried in droplets — not aerosols.’) So the majority of transmission happens from droplets. What’s more, the deadliest aerosols are those that started out as droplets, but then evaporated down; they have higher concentrations of the virus. Masks catch those. So the inability of masks to filter out 0.3 micron particles does not greatly hinder their ability to keep infected particles out of the air, and thus does not prevent them from efficiently preventing the spread of COVID.
Adrien Burch, “A Microscopic Perspective on Airborne COVID-19,” The Medium, March 31, 2020, https://medium.com/better-humans/should-you-be-worried-about-catching-COVID-19-from-aerosols-6c97d023bb6d.
 From the abstract of: Richard O. J. H. Stutt, Renata Retkute, Michael Bradley, Christopher A. Gilligan, and John Colvin, “A Modelling Framework to Assess the Likely Effectiveness of Facemasks in Combination with ‘Lock-down’ in Managing the COVID-19 Pandemic,” Proceedings of the Royal Society A (2020) https://doi.org/10.1098/rspa.2020.0376.
 Wycliffe E Wei, Zongbin Li, Calvin J Chiew, Sarah E Yong, Matthias P Toh, and Vernon J Lee, ”Presymptomatic Transmission of SARS-CoV-2-Singapore, January 23-March 16, 2020,” MMWR Morb Mortal Wkly Rep. 69, no. 14 (April 2020): 411-5, https://doi.org/10.15585/mmwr.mm6914e1.
Anthony D Sung, et al. “Universal Mask Usage for Reduction of Respiratory Viral Infections after Stem Cell Transplant: a Prospective Trial,” Clin Infect Dis 63, no. 8 (October 2016): 999-1006, https://doi.org/10.1093/cid/ciw451. Xiaowen Wang, Enrico G. Ferro, Guohai Zhou, et al., “Association Between universal Masking in a Health Care System and SARS-CoV-2 Positivity Among Health Care Workers,” JAMA,published electronically July 14, 2020, https://doi.org/ 10.1001/jama.2020.12897. In this study, cases of COVID-19 declined after mask mandates were put into effect in hospitals (that required all health care workers and patients to mask up). The study concluded that such mandates reduce the transmission of SARS-CoV-2.
 Timo Mitze, Reinhold Kosfeld, Johannes Rode, and Klaus Wälde, “Face Masks Considerably Reduce COVID-19 Cases in Germany: A Synthetic Control Method Approach,” IZA (June 2020) http://ftp.iza.org/dp13319.pdf.
This study shows the impact of mask mandates in Germany. In Jena, for example, the first German city to enact such a mandate, COVID-19 cases fell by almost 25% in 20 days. The study concluded that similar mandates could ruse the daily growth rate by 40% in the long term, although it did acknowledge that, outside Germany, different norms and climatic conditions in other countries might result in different protective outcomes.
 “HSC COVID-19 Report #5 – July 20, 2020,” University of North Texas Health Science Center at Fort Worth, https://www.scribd.com/presentation/469858261/COVID-19-Report-July-20-Updated?fbclid=IwAR1ta8C-x5yYfpqQ5eghmiPFr42ndbA6rYCmTv3WbcGU9tDt3a_RU1BOIL0.
 In those 15 US States, they likely prevented up to 450,000 cases in under two months. Wei Lyu and George L. Wehby, “Community Use of Face Masks and COVID-19: Evidence from a Natural Experiment of State Mandates in the US,” Health Affair 39, no. 8 (2020): 1-7, https://doi.org/ 10.1377/hlthaff.2020.00818.
This was a retrospective analysis which examined the effects that different governmental orders to wear face masks had on COVID-19 growth rates, from April 9-May 15, 2020. It estimated that they prevented between 230,000 and 450,000 cases by May 22 (a reduction of 14-27%).
 Kasra Zarei and John Duchneskie, “Coronavirus Cases Rise in States with Relaxed Face Mask Policies,” The Philadelphia Inquirer, June 24, 2020, https://www.inquirer.com/health/coronavirus/COVID-19-coronavirus-face-masks-infection-rates-20200624.html.
 American Thoracic Society, “Countries with Early Adoption of Face Masks Showed Modest COVID-19 Infection Rates,” Medical Xpress, June 24, 2020, https://medicalxpress.com/news/2020-06-countries-early-masks-modest-COVID-.html.
 Joseph Berger, “Death Drops 27% With State’s Seat-belt Law, The New York Times, May 1, 1985, https://www.nytimes.com/1985/05/01/nyregion/death-drops-27-with-state-s-seat-belt-law.html.
 Samantha M. Tracht, Sara Y. Del Valle, and James M. Hyman, “Mathematical Modeling of the Effectiveness of Facemasks in Reducing the Spread of Novel Influenza A (H1N1),” Plos One 5, no. 2 (February 2010): 1-12, doi.org/10.1371/journal.pone.0009018.
 Stutt, et al., “A Modelling Framework to Assess the Likely Effectiveness of Facemasks in Combination with ‘Lock-down’ in Managing the COVID-19 Pandemic.”
To keep the infection rate (R0) below 1.0, the authors argue for widespread use of face masks. “[F]acemask adoption by entire populations would have a significant impact on reducing COVID-19 spread.” “[I]n summary, our modelling analyses provide support for the immediate, universal adoption of facemasks by the public.”
 Derek K Chu, et al., “Physical Distancing, Face Masks, and Eye Protection to Prevent Person-to-person Transmission of SARS-CoV-2 and COVID-19: A Systematic Review and Meta-analysis,” The Lancet 395, no. 10242 (2020): 1973-87, https://doi.org/10.1016/S0140-6736(20)31142-9.
This was a review of 172 observational studies and 44 relevant comparative studies. The authors concluded “Face mask use could result in a large reduction in risk of infection.”
 Kimberly A. Prather, Chia C. Wang, and Robert T. Schooley, “Reducing Transmission of SARS-CoV-2,” Science 368, no. 6498 (June 2020): 1422-24, https://doi.org/10.1126/science.abc6197. In this paper, aerosol chemists and an infectious disease specialist argue that, because “airborne spread from undiagnosed infections will continuously undermine the effectiveness of even the most vigorous testing, tracing and social distancing programs,” the widespread use of masks are necessary to help prevent the spread of COVID. Both analytical information about the virus and information about countries where masks are commonplace was used.
Catherine M. Clase, et al., “Cloth Masks May Prevent Transmission of COVID-19: An Evidence-Based, Risk-Based Approach,” Annals of Internal Medicine, published electronically May 22, 2020, https://doi.org/10.7326/M20-2567. This study, done by an international research team of medical doctors and other medical specialists not only concluded that cloth masks worn by the public will reduce COVID-19 transmission rates but that the benefits of widespread mask use outweigh any risks that may be brought about by wearing masks (such as improper use).
 M. Joshua Hendrix, Charles Walde, Kendra Findley, and Robin Trotman, “Absence of Apparent Transmission of SARS-CoV-2 from Two Stylists After Exposure at a Hair Salon with a Universal Face Covering Policy – Springfield, Missouri, May 2020,” Weekly 69, no. 28 (July 1, 2020): 930-32, http://dx.doi.org/10.15585/mmwr.mm6928e2.
 “New IHME COVID-19 Model Projects Nearly 180,000 US Deaths,” IHME,June 24, 2020, http://www.healthdata.org/news-release/new-ihme-COVID-19-model-projects-nearly-180000-us-deaths.
 For the quote, see McCabe, “Face Masks Really Do Matter.” For the evidence behind it, see John T. Brooks, Jay C. Butler, Robert R. Redfield, “Universal Masking to Prevent SARS-CoV-2 Transmission – The Time is Now,” Jama, published online July 14, 2020, https://doi.org/10.1001/jama.2020.13107.
 For more such evidence, see “Face Masks – A Summary of Relevant Research Papers for COVID-19,” Sound Reason & More,June 11, 2020, https://soundreasonandmore.wordpress.com/2020/06/11/face-masks-a-summary-of-relevant-research-papers-for-COVID-19/.
 Leung et al. 2020. Respiratory virus shedding in exhaled breath and efficacy of
face masks. Under review. DOI: 10.21203/rs.3.rs-16836/v1.
 Markus MacGill, “What is a Randomized Controlled Trial?” Medical News Today, December 4, 2018, https://www.medicalnewstoday.com/articles/280574.
 Rebecca A. Clay, “More than One Way to Measure,” American Psychological Association 41, no. 8 (September 2010): 52, https://www.apa.org/monitor/2010/09/trials; Roger Mulder, et al., “The Limitations of Using Randomised Controlled Trials as a Basis for Developing Treatment Guidelines,” Evidence-Based Mental Health 21, no. 1 (2018): 4-6, http://dx.doi.org/10.1136/eb-2017-102701.
 See Sergey A. Grinshpun, et al., “Performance of an N95 Filtering Facepiece Particulate Respirator and a Surgical Mask During Human Breathing: Two Pathways for Particle Penetration,” Journal of Occupational and Environmental Hygiene 6, no. 10 (2009): 593-603, https://doi.org/10.1080/15459620903120086. See also C. Raina MacIntyre, et al., “The Efficacy of Medical Masks and Respirators Against Respiratory Infection in Healthcare Workers,” Influenza and Other Respir Viruses 11, no. 6 (November 2017): 511-17, https://doi.org/10.1111/irv.12474. See also Mark Loeb, et al., “SARS among critical care nurses Toronto,” Emerg Infect Dis 10, no. 2 (Feb 2004):251-5, https://doi.org/10.3201/eid1002.030838; C. Raina MacIntyre and Abrar Ahmad Chughtai, “A Rapid Systematic Review of the Efficacy of Face Masks and Respirators Against Coronaviruses and Other Respiratory Transmissible Viruses for the Community, Healthcare Workers and Sick Patients,” Int J Nurs Stud, published online April 30, 3030, https://doi.org/10.1016/j.ijnurstu.2020.103629.
 David Kyle Johnson, “Confirmation Bias,” in Bad Arguments: 100 of the Most Important Fallacies in Western Philosophy, eds. Robert Arp, Steven Barbone, and Michael Bruce (Wiley Online Library, May 2018), https://doi.org/10.1002/9781119165811.ch17.
 Rancourt, “Masks Don’t Work.”
 See Sergey A. Grinshpun, et al., “Performance of an N95 Filtering Facepiece Particulate Respirator and a Surgical Mask During Human Breathing: Two Pathways for Particle Penetration,” Journal of Occupational and Environmental Hygiene 6, no. 10 (2009): 593-603, https://doi.org/10.1080/15459620903120086. See also MacIntyre, et al., “The Efficacy of Medical Masks and Respirators Against Respiratory Infection in Healthcare Workers.” See also Loeb, “SARS among critical care nurses, Toronto.”
 Adam Hayes, “Law of Diminishing Marginal Returns,” Investopedia, June 14, 2020, https://www.investopedia.com/terms/l/lawofdiminishingmarginalreturn.asp.
 Jeffrey D. Smith, et al., “Effectiveness of N95 Respirators Versus Surgical Masks in Protecting Health Care Workers from Acute Respiratory Infection: a Systematic Review and Meta-analysis,” CMAJ 188, no. 8 (May 2016): 567-74, https://doi.org/10.1503/cmaj.150835.
 Vittoria Offedu, et al., “Effectiveness of Masks and Respirators Against Respiratory Infections in Healthcare Workers: A Systematic Review and Meta-Analysis,” Clinical Infectious Diseases 65 no. 11, (December 2017): 1934–42, https://doi.org/10.1093/cid/cix681.
 Lewis J. Radonovich, Michael S. Simberkoff, and Mary T. Bessessen, “N95 Respirators vs Medical Masks for Preventing Influenza Among Health Care Personnel: A Randomized Clinical Trial,” JAMA 322, no. 9 (2019): 824–833, https://doi.org/10.1001/jama.2019.11645.
 Youlin Long, et al., “Effectiveness of N95 respirators versus surgical masks against influenza: A systematic review and meta-analysis,” J Evid Based Med 13 (2020): 93-101, https://doi.org/0.1111/jebm.12381.
 Faisal bin-Reza, Vicente Lopez Chavarrias, Angus Nicoll, Mary E. Chamberland, “The use of masks and respirators to prevent transmission of influenza: a systematic review of the scientific evidence,” Influenza and Other Respiratory Viruses 6, no. 4 (December 2011): 257, https://do8i.org/ 0.1111/j.1750-2659.2011.00307.x.
 B.J. Cowling, Y. Zhou, D.K.M.Ip, G.M.Leung, and A.E. Aiello, “Face Masks to Prevent Transmission of Influenza Virus: A Systematic Review,” Epidemiology & Infection 138, no. 4 (January 2010): 449-56, https://doi.org/10.1017/S0950268809991658.
 B.J. Cowling, et al., “Face Masks to Prevent Transmission of Influenza Virus: A Systematic Review.”.
 You can find a very similar conclusion in this “study” on parachute effectiveness. Robert W Yeh, et al., “Parachute Use to Prevent Death and Major Trauma when Jumping from Aircraft: Randomized Controlled Trail,” BMJ 363 (December 2018) https://doi.org/10.1136/bmj.k5094.
 Jeffrey Shaman, Virginia E. Pitzer, Cécile Viboud, Bryan T. Grenfell, and Marc Lipsitch, “Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States,” PLOS Biology 8, no. 2 (February 2010) https://doi.org/10.1371/journal.pbio.1000316.
 Rancourt, “Masks Don’t Work.”
 Bo Bennett, “Oversimplified Cause,” Logically Fallacious, https://www.logicallyfallacious.com/logicalfallacies/Oversimplified-Cause-Fallacy.
 For her study on this, see Rachel E. Baker, Wenchang Yang, Gabriel A. Vecchi, C. Jessica E. Metcalf, and Bryan T. Grenfell, “Susceptible Supply Limits the Role of Climate in the Early SARS-CoV-2 Pandemic,” Science 369, no. 6501 (July 17, 2020): 315-19, https://doi.org/10.1126/science.abc2535.
 Derek Hawkins, Michael Birnbaum, Meryl Kornfield, Siobhán O’Grady, Kareem Copeland, Marisa Iati, and Felicia Sonmez, “Arizona, Florida, Texas are Latest Coronavirus Epicenters,” The Washington Post, June 29, 2020, https://www.washingtonpost.com/nation/2020/06/28/coronavirus-live-updates-us/.
 Harvey Fineberg, Rapid Expert Consultation on the Possibility of Bioaerosol Spread of SARS-CoV-2 for the COVID-19 Pandemic (April 1, 2020), (The National Academies Press, 2020), chapter 1 and 2, https://www.nap.edu/read/25769/chapter/1#2.
 See Zeshan Qureshi, et al., “What is the Evidence to Support the 2-metre Social Distancing Rule to Reduce COVID-19 Transmission?” CEBM, June 22, 2020, https://www.cebm.net/COVID-19/what-is-the-evidence-to-support-the-2-metre-social-distancing-rule-to-reduce-COVID-19-transmission/.
 It is also important to understand that although the majority of the droplets produced by a cough may be small enough to stay airborne, their small size means that collectively they add up to only a tiny fraction of the volume produced (perhaps less than 0.1%), and therefore only a tiny fraction of the total virus spread.
 Adrien Burch, “A Microscopic Perspective on Airborne COVID-19,” Medium, March 31, 2020, https://medium.com/better-humans/should-you-be-worried-about-catching-COVID-19-from-aerosols-6c97d023bb6d.
 Erin Bromage, “The Risks – Know Them – Avoid Them,” Erin Bromage, May 6, 2020, https://www.erinbromage.com/post/the-risks-know-them-avoid-them.
 Rancourt, “Masks Don’t Work.”
 Harper does not appear in his bibliography, so I was unable to verify if Rancourt was misrepresenting his research.
 Bo Bennett, “Appeal to Possibility,” Logically Fallacious, https://www.logicallyfallacious.com/logicalfallacies/Appeal-to-Possibility.
 Rancourt, “Masks Don’t Work.”
 Tuomas W. Manninen, “Appeal to Personal Incredulity,” in Bad Arguments: 100 of the Most Important Fallacies in Western Philosophy, eds. Robert Arp, Steven Barbone, and Michael Bruce (Wiley Online Library, May 2018), doi: 10.1002/9781119165811.ch17.
 Rancourt, “Masks Don’t Work.”
 Eric Litke, “Fact Check: No, N95 Filters are Not Too Large to Stop COVID-19 Particles,” USA Today, June 11, 2020, https://www.usatoday.com/story/news/factcheck/2020/06/11/fact-check-n-95-filters-not-too-large-stop-COVID-19-particles/5343537002/.
 Abhiteja Konda, Abhinav Prakash, Gregory A. Moss, Michael Schmoldt, Gregory D. Grant, and Supratik Guha, “Aerosol Filtration Efficiency of Common Fabrics Used in Respiratory Cloth Masks,” ACS Nano 14, no. 5 (2020): 6339-47, https://doi.org/10.1021/acsnano.0c03252.
 Rancourt, “Masks Don’t Work.”
 Saber Yezli and Jonathan A. Otter, “Minimum Infective Dose of the Major Human Respiratory and Enteric Viruses Transmitted Through Food and the Environment” Food and Environmental Virology 3 (2011): 1-30, https://doi.org/10.1007/s12560-011-9056-7.
 Mark P. Zwart, Lia Hemerik, Jenny S. Cory, J. Arjan G.M. de Visser, Felix J.J.A. Bianchi, Monique M. Van Oers, Just M. Vlak, Rolf F. Hoekstra, and Wopke Van der Werf, “An Experimental Test of the Independent Action Hypothesis in Virus– Insect Pathosystems,” Proceedings of the Royal Society B (March 2009) http://doi.org/10.1098/rspb.2009.0064.
 Prasith Baccam, Catherine Beauchein, Catherine A Macken, Frederick G Hayden, and Alan S Perelson, “Kinetics of Influenza A Virus Infection in Humans,” Journal of Virology 80, no. 15 (August 2006): 7590-99, https://doi.org/ 10.1128/JVI.01623-05; Christopher B Brooke, William L Ince, Jens Wrammert, Rafi Ahmed, Patrick C Wilson, Jack R Bennink, and Jonathan W Yewdell, “Most Influenza A Virions Fail To Express at Least One Essential Viral Protein,” Journal of Virology 87, no. 6 (March 2013): 3155-62, https://doi.org/10.1128/JVI.02284-12.
 Burch, “A Microscopic Perspective on Airborne COVID-19.”
 Carl Heneghan, Jon Brassey, and Tom Jefferson, “SARS-CoV-2 Viral Load and the Severity of COVID-19,” CEBM, March 26, 2020, https://www.cebm.net/COVID-19/sars-cov-2-viral-load-and-the-severity-of-COVID-19/.
 Bo Bennett, “False Dilemma,” Logically Fallacious, https://www.logicallyfallacious.com/logicalfallacies/False-Dilemma.
 Rancourt, “Masks Don’t Work.”
 Angus Deaton and Nancy Cartwright, “The Limitations of Randomised Controlled Trials,” VoxEU CEPR, November 9, 2016, https://voxeu.org/article/limitations-randomised-controlled-trials; Dennis Zeilstra, Jessica A. Younes, Robert J. Brummer, and Michiel Kleerebezem, “Perspective: Fundamental Limitations of the Randomised Controlled Trial Method in Nutritional Research: The Example of Probiotics,” Advances in Nutrition 9, no. 5 (September 2018): 561-71, https://doi.org/10.1093/advances/nmy046.
 Clay, “More than One Way to Measure”; Alexander Krauss, “Trials and Errors: The Limits of Randomised Controlled Trials,” Campbell Collaboration, May 16, 2018,https://campbellcollaboration.org/blog/trials-and-errors-the-limits-of-randomised-controlled-trials.html.
 Holly Secon, ”If Everyone in the US Wears a Mask in Public, 33,000 Lives Could Be Saved Over the Next 3 Months, One Model Suggests,” Business Insider, June 26, 2020, https://www.businessinsider.com/wearing-face-masks-could-save-33000-us-lives-2020-6; Megan Cerullo, “Everyone Wearing Face Masks Could Save America From a $1 Trillion GDP Loss,” CBS News, July 9, 2020, https://www.cbsnews.com/news/face-mask-wearing-save-money/.
 Steven Novella, “COVID-19 and Excess Deaths,” Science-Based Medicine, July 22, 2020, https://sciencebasedmedicine.org/COVID-19-and-excess-deaths/.
 “Backfire Effect,” RationalWIki, https://rationalwiki.org/wiki/Backfire_effect.
 “Dunning-Kruger Effect,” Rational Wiki, https://rationalwiki.org/wiki/Dunning-Kruger_effect/.