Discerning Truth: COVID-19 Part 2

Face Masks as a Testable Science Question

Hey folks, welcome to Discerning Truth, the podcast of the Biblical Science Institute. I'm Dr. Lyle. We've been looking at coronavirus and some of the issues surrounding that, and I'd like to continue with that topic.

And so let's just get right into it. What about face masks? People have their opinions on masks, strong opinions. And you'll even see experts disagreeing on whether masks should be worn, whether they have any value or not.

And that may lead you to think that the question is unanswerable. But in reality, the effectiveness of face masks is scientifically testable. Of course, not everyone cares about the facts. Some people, they've got their opinion, and that's the end of the matter.

In fact, whenever I sense that someone is becoming very emotional and defensive, I always ask this question. I ask, is there any evidence I could present to you that would change your mind? And if they say no, then I know I'm dealing with someone who is irrational, at least on that issue, and there isn't any point in further conversation.

Rational people don't just believe what they want. They examine the evidence and are willing to change their mind in light of facts. But if people don't care about the facts, then there's really no point in having a conversation.

That's fine. That's fine. In reality, either masks provide some benefit or they don't, right? That might depend on the type of mask and so on, but it's a question. The question, do masks significantly reduce risk of viral infection?

That is a science question, isn't it? Because it's directly testable by experiment in the present. That's exactly the kind of question that the scientific method was developed to answer. Now previously, I've talked about science and how it is not well-suited for reconstructing past events.

It has a role to play, but the conclusion is never directly testable when you talk about the past. And so people tend to draw very different conclusions about the evidence. They draw different interpretations of the same evidence because they have different worldviews.

They have a different view of history. And so when reconstructing past events, they come up with different interpretations of the same evidence. Worldview makes a huge difference. But when it comes to things that are directly testable in the present, worldview issues are not as critical as long as your worldview at least minimally accepts the scientific.

Method.

And the reason is because you can test the claim. You say, I think this will result if you do this. And you test it. And it doesn't happen.

You're wrong.

I mean, that's just all there is to it. So the question, do masks effectively filter out viruses and aerosols containing those.

Viruses?

That's a science question. It's actually a physics question, isn't it? Because we're asking, given the size of the particles and the pressure involved in the flow velocity and the grid spacing of the mask, how do such particles move?

That's a fluid dynamics question, which is an aspect of physics. I've had graduate level training in fluid dynamics. Now common sense would suggest that a mask is not going to protect you from a virus that is a thousand times smaller than the holes in your mask.

Now I've heard all the counter arguments, but you know, well, it will protect people from the larger water droplets when they cough or sneeze. Two problems with that counter argument. First of all, what's the alternative?

You get better protection than what? Then sneezing directly into somebody's face? Yeah, I would say a mask would be better. If you're going to sneeze directly into my face, I'd rather you have a mask on than not.

But that's not the normal alternative. Polite people don't come up and sneeze and cough right in your face. You're supposed to cough or sneeze in your arm like that or your elbow. And that ought to block those particles pretty well, I would think.

I haven't seen any study that says that sneezing or coughing through a mask is better than coughing or sneezing into your arm. I haven't seen any study on that. And second, these large particles that the masks might potentially trap, that's not the.

Problem.

It's the millions of small ones. The large particles, by the way, those tend to, the large droplets tend to eventually settle to the ground due to gravity. The small ones don't because the force of gravity on them is negligible.

They're carried away by the current. It's the tiny ones that are the issue. And they're far smaller than the holes in your mask, especially if you have one of these cloth masks like this one. Some people say, oh, but I use an N95 mask.

Well, you probably don't because those are not real common. But in any case, and they block 95 of the particles. They block 95 of particles that are larger than 0 .3 microns. Viruses are smaller than that.

Coronavirus is particularly small. And so aerosols, and even aerosols that carry the viruses, they can go through that. So common sense would suggest that masks are no more effective than a screen door on a.

Submarine.

Experimental Evidence on Aerosols and Viral Load

But common sense, intuition is not always right. There's some things in this world that are true and yet contrary to our intuitive expectations. Some people say, well, I'm just going to live by my intuition.

This is my opinion and that's why I'm going to stick with it. Well, you're going to be wrong a lot because you see a rational person doesn't just believe what he wants to believe. Rather, he has good reasons for his belief.

He looks at the evidence and adjusts his beliefs accordingly. And when it comes to questions of how the universe operates today, the scientific method is a very powerful tool that the Lord has given to us to answer those kinds of questions.

We ought to rely on that rather than just our intuitive expectations. So do you want to know if masks filter out aerosols? Well, I got news for you. That's been tested. That's been tested. And we find that aerosols go right through and around masks.

Dr. Ted Noel demonstrates this using water vapor. Let's have a look.

And take a look at an ordinary surgical mask. And I'm using a vape. As you can see, that vape, which has aerosols the same size as COVID -19 or larger, goes through and around a surgical mask. Now, if we take a cup mask and have a good look at it, here we go.

Notice it goes right through the mask easily and goes in every direction. The aerosol is not affected by the mask in any material. Now we look at a surgical mask with a foam strip to protect above and keep my glasses from fogging.

Lo and behold, the aerosols go all around it. It has no effect on me spreading aerosols to you. Now a cloth mask I borrowed from my wife. Once again, here we go, boom, straight through and around. It has no effect on the spread of aerosols.

They go everywhere. And then I went and bought a guard mask with a high-efficiency filter material. That one, here we go. Watch for it, through and around. It had no effect on the vape aerosol, which remember is the same size or larger.

So keep that in mind when you think about, you know, where are these viruses going? Well, now you can visually see kind of where they just build up around you. They're carried away by the air currents and so on.

And of course, in that experiment, actually the water droplets are quite a bit larger than the aerosols you normally exhale because you can see those. And the ones that you exhale are normally invisible.

So do masks trap any viruses at all? Because mathematically, you'd think, well, they would almost have to trap some. So the question really is whether it has any real-world impact. And so now I think there is value in just looking at the raw numbers, and that's been tested.

So there was a recent experiment that measured the actual number of viruses that pass through a mask when a person, when an infected person is wearing the mask and another person is the receiver and you have masks on both or masks on one or the other and different types of masks, it's a wonderful study.

And let's take a look at this study. Effectiveness of face masks in preventing airborne transmission of SARS-CoV -2. And you can see the setup of the experiment here. It's a very clever setup. You have a machine over here that's pumping small samples of the virus contained in water droplets about five microns in size through our test dummy head here at a constant rate.

So that's not quite realistic, but that's okay. At least it's something. So he's constantly exhaling, and he's potentially wearing a mask. The other person then at a certain distance away, and they actually tried several different distances, and he's got a mask on too, potentially, or not.

They tested it both ways, and yeah, pretty clever. And then they measured the amount of viruses that are absorbed by the receiver. And the receiver, by the way, they have an air pump on him too. He's breathing normally.

He's inhaling and exhaling. And so that's pretty realistic. And so when we take a look at the results, what do we find? First of all, here's the result for the spreader not wearing a mask, but the receiver is wearing a mask.

And they try it for different types of masks. And the number of viruses that are received or detected are indicated by the brown bar there you see. So the first brown bar is without mask. So the spreader is not wearing a mask.

The receiver is not wearing a mask. That's the baseline. That's how many viruses you'd get without any intervention. Now, the receiver wears a cotton mask. That's the second line. And you can see it's virtually identical to the first line.

Wearing a cloth mask as the receiver made no difference, statistically made no difference at all. It's within the error bars of the original study. What if he wears a surgical mask? There's just a minuscule drop, but it's not much.

He's still getting the same virus load as if he weren't wearing a mask at all. Now you go to N95, there's a little bit of a dip there. N95 seems to help a little bit. And this is N95 without necessarily having it fitted.

And then the final bar is N95 fitted, which seems to be the same as the unfitted. Now there is a small drop. So the N95 mask does seem to reduce the virus load, but it's not by very much. Now the, it's probably a little more than it looks because the graph is logarithmic, but probably our response to exposure is logarithmic as well.

So do masks provide much benefit from the receiver? The cloth mask, I would say really none at all. Surgical mask, perhaps just a little bit. N95 masks do seem to have a little bit of a benefit. Okay, what if the spreader is wearing a mask, but not the receiver?

And here we do a little better. If the, so again, we start with the baseline where the spreader is not wearing a mask. And then we go to the second line where he's wearing a cloth mask. There is a slight drop, but boy is it slight.

Boy is it slight. And then if he's wearing a surgical mask, actually that is almost the same as the cloth mask, interestingly. And then when he gets to the N95 unfitted, there's a substantial drop. And if he wears N95 fitted, that's a substantial drop.

So if the spreader is wearing an N95 fitted mask, one that does not have a valve on it, by the way, because the, you know, there's some that have a valve that release everything into the air. That does nothing.

Yeah, there's a substantial drop.

Pretty good.

What if both of them wear masks? Because keep in mind, most people don't have N95 masks. Most people have either a cotton one or maybe they get a hold of a surgical one. If both people are wearing masks, and let's say the spreader is wearing a cotton mask, well, first of all, the first bar is no masks at all.

The second bar is the spreader is wearing a cotton mask, but the receiver is not wearing a mask. And the drop is just tiny. It's just, there is a drop, but boy, is it small. And then next, the, both of them are wearing cotton masks.

That's the third bar. And it's slightly lower than the no masks at all, but not much. Surgical mask, about the same as a cotton mask. N95, there's a little bit of a drop. And N95 fitted, there's a little bit more of a drop, but not much.

Okay, what if the spreader wears a surgical mask? Well, again, the baseline is without either of them wearing masks. The first bar after that is the spreader is wearing a surgical mask. The receiver is not wearing a mask.

There's a slight drop, but it's not much. He's getting just about the same number of viruses, really. If the receiver then wears a cotton mask, drops a little bit, but boy, is it tiny. If he wears a surgical mask, it's about the same as the cotton mask.

N95 drops a little more. N95 fitted drops a little bit more. But notice how small this effect is, though, even when both of them are wearing high-quality masks. Even when the spreader is wearing a surgical mask and the receiver is wearing a N95 fitted mask, look at the number of viruses he's getting.

That's, again, that's 10 to the power of 6, so that would be a million, that's a million viral RNAs that he's detected. So in that simulation, masks would not have prevented any of those people from getting sick.

But the highest-quality masks did reduce some of the viral load. But the more important question is, is there a real-world benefit? Because, I mean, it's one thing to say, yeah, theoretically this person will get fewer viruses, but does it really have a substantial effect on whether or not they'll get infected, right?

That's the question we want to know. Does it reduce my chance of getting an infection? Does it reduce the severity of the infection, of the symptoms, because I'm getting fewer viruses? Because some things that should work theoretically on paper, in the real world, don't work because there are other factors you didn't consider.

Let me give you an example of this. One of the studies we're going to look at here in a minute found that cloth masks like this have 97 penetration. Ninety-seven percent of the viruses go right through this thing.

Three percent are blocked. So for every 100 virus particles, 97 pass. And you say, well, that's not much, but, hey, I'll take that three percent blockage. I mean, it's better than nothing, right? But when you wear your mask, when I wear my mask, I have to breathe a little harder.

Suppose I have to, for the sake of hypothesis, suppose I have to breathe 4 harder. So whereas previously I would breathe in a unit of air with 100 viral particles, now I breathe 4 larger volume, which has 104 viral particles.

Three percent of them are blocked by the mask, which means 101 particles go through. So in that hypothetical scenario, the mask actually made things worse. And I'm not saying that that's, that those are the actual, the 97%, that's true.

The 4 was hypothetical. But you can see how under certain conditions, a mask might actually make things worse. So that's the question that we need to ask. Is there real-world application? Is there a real-world benefit to wearing masks?

Does it outweigh the risks of wearing masks? So just because masks may mathematically block some viral particles, that doesn't automatically translate to them being an effective deterrent to infection.

They might make things better. They might make things worse. Or it might be a wash. So how do we test the real-world effectiveness of masks? And this is where we get into the scientific method, or we're about to.

Because first of all, some people think that they are being very scientific. Because they've said to me, well, masks must work because, you know, in this particular state or in this particular county or in this particular nation, the leader introduced a mask mandate.

And sure enough, the number of cases dropped slightly. Okay? Well, of course, any student of logic would recognize that as an error in reasoning. It's a post hoc ergo proctor hoc fallacy. Just because event B happened after event A does not mean that event A caused event B.

Now, that could be the case. But there are other possibilities as well. It could be that event C caused event A and then event B as well. And event B just took a little longer. It could be that event A did not directly cause event B, but event A caused event C, which then caused event B.

That's a very plausible explanation in this instance. I mean, you can imagine your governor comes out and says, ah, the number of COVID cases is getting pretty high, so I'm going to have to insist all of you wear masks.

And you're watching that on the evening news, and you think, oh, I had no idea there were that many COVID cases. I think we should just stay home this week. And so you see the mask mandate did have a positive effect, but not because the masks themselves were doing anything, but because they induced behavior that genuinely does do something, isolation.

Maybe some people say, well, if I'm going to have to wear a mask, I'm just not going to go out. I hate wearing those things. And so, and not going out and not interacting with other people, that does reduce the number of cases.

And so that's an example of where the masks in and of themselves did nothing, but the decree caused people to behave in a way that had a positive impact in reducing the number of cases. Then again, event B happens after event A.

It might just be a coincidence, right? I sneezed, and then it rained. Now, did my sneeze cause the rain? No, it's just a coincidence. So how do you distinguish a genuine causation relationship from a coincidence?

And the answer is you find many, many examples. If event A truly is the cause of event B, then B must follow necessarily from event A. That's the definition of causation. It's a necessary succession. And so I would find that many times when I sneeze, it doesn't rain.

And many times when it rains, I haven't sneezed. And so I would discover as I accumulated more examples that there really is no causal relationship between sneezing and raining. And likewise, we can do the same thing with masks.

When we look at many different examples of mask mandates and then coronavirus cases, do the mask mandates normally cause a drop? Well, there was a study that was done on this. Let's see here. This was done by Swiss Policy Research, and they actually produced some charts showing when the mask mandates were in place and the effect that it had or lack of effect on COVID -19 cases.

So let's have a look at this. Okay, so we start with Austria and look at its COVID -19 cases. Number of cases is on the vertical axis. The date is on the horizontal axis. And you can see when masks were implemented, required masks were implemented.

And you can see that the number of cases do drop after that, but then again, they were already dropping before that. It doesn't look like the mask mandates changed the slope of the line. It's almost as if they had no effect at all.

Belgium, you can see the number of cases there. Suddenly masks are required. There was no drop. The number of cases actually went up a little bit. California, and then they start requiring masks. And do the number of cases drop?

No, they actually increase when masks are mandated. France, and we have masks mandated. And did the number drop? Maybe a little bit, but then it just went right up. Germany, masks mandated. Now there, it looks like it might've dropped a little bit, but it's not a huge effect.

What about Hawaii? Masks are implemented, indoor masks, and it drops a little bit, but not much. And it was already dropping. Outdoor masks are implemented, and that doesn't seem to have any positive effect at all.

It seems like they just continue to go up. There was a little bit of a downturn there, but then they went up again. Ireland, masks are implemented. Did the numbers drop? No, they actually increased. Italy, masks required, and the number goes way up.

That's interesting. Spain, and so we have the masks required, and then it doesn't seem to have much of an effect at all. And of course, the cases are going up now as we enter into the winter months. That's what we would expect.

UK, masks required. It looks like it has no effect whatsoever. So the idea that a mask mandate's implemented, then the cases drop, that's not generally true. Generally, there's no effect on the number of COVID cases, none whatsoever when mask mandates are implemented.

So that's interesting. And that might suggest that masks really aren't doing that much. Of course, even that's, even that conclusion, we can't draw definitively because we don't know if people are complying with the mask mandate.

You could say, well, you know, the mask mandate goes in effect, but nobody cares. They don't obey that mandate. So how can we test if masks are effective? Well, that's where the scientific method comes in, doesn't it?

In an ideal situation, how would we scientifically test whether or not masks have the effect of reducing the number of COVID -19 infections? And the way you would do that scientifically, ideally under perfect circumstances, is you would have two groups of people.

You'd have one group of people that wear masks, and you'd have the other group of people that don't wear masks, and that's the control group, okay? And the control group is the baseline by which you can measure the effectiveness of masks in the other group, okay?

So you need to know what happens when masks aren't worn so that you can make the comparison. Then you expose both groups to the same environment in which there is some exposure to COVID -19, and you compare the number of people that became infected in the mask group versus those that became infected in the control group.

And assuming that all other conditions are identical, any difference between the two groups could only be due to masks, because that's the only variable. That's the way you do science. You reduce it to one variable, and you have a control group, and then you have the group that has that one variable difference, and you see if it makes any difference.

So that's why it's so important to keep all the conditions the same. If the other conditions weren't the same, then you wouldn't know anything, right? If, for example, the control group wore gloves, and the mask group didn't, and there's a difference in infection percentage, you wouldn't know if it's due to the masks, or the gloves, or some combination of the two.

So you try to keep all the conditions the same except for the one you wanna test. Now, in practice, it's impossible to keep all the conditions exactly the same between the two groups, because there are different people in different groups.

Some people in the mask group might have a natural immunity to the virus just by chance. And so their infection rate is lower, but not because of the masks, but because there's a few people that are naturally immune.

So how do you account for that? The only way to combat these unknown variables is to increase the number of people in each group. If you have 1 ,000 people in the unmasked group and 1 ,000 people in the masked group, the differences tend to cancel out, right?

Because the probability that all 1 ,000 people in the masked group would be immune and all the ones in the other are not is statistically absurd. It's negligible. So the more people you get, the better your statistics come out.

And in any of these studies, there are error bars. And so you say, here's the number of people who got infected, and there's a plus and minus because that plus and minus indicates some of these variables that you don't know about.

The fact that some people might have a natural immunity or some people might be prone to being sick anyway. And so that's what these error bars are for. And so the only way you could be sure that masks do make a difference is if the number of infections in the masked group versus the control group are outside the error bars of each other.

If the error bars overlap, then you don't really know anything. You can't say for certain if the masks had the effect or if these other random variables that we don't know about had the effect. But keep in mind, those random variables, the larger the number of people you have, statistically, the smaller the number of random variables because randomness tends to cancel out in large numbers.

So that's what you wanna do. Scientifically, ideally, is you randomly assign these people to each group and you keep all the other variables the same and you have as many people as possible. And then there will be error bars in your study.

So when you see these studies and they say this is 95 confidence interval, that's referring to those error bars. You can say we're 95 confident that the true value is within this range. And so if the true value is within this range and the true value is within that range, you don't know the true value could be the same between the two groups.

So confidence intervals or this is our two sigma or two standard deviation value, that's what that means. The people in each group should be chosen randomly because if you allow the people to choose which group they're gonna be in, that's a second variable because it might be that people in the mass group are more concerned with their health and therefore, they're likely to take other precautions.

They wash their hands more often and so on. That introduces a new variable that you can't control. So you want the group to be randomized. You want a randomized trial, a controlled randomized trial. Now in the real world, it's hard to do that.

It's rarely that neat, especially with experiments involving human beings because obviously, it would be unethical to expose human beings intentionally to something that could kill them for no reason.

So more realistically, we have to take a look at some of these studies where people are already in a high risk environment such as a hospital or the healthcare workers and you try to get as close to that ideal condition though as you can get.

And so what I'm gonna look at is a number of studies that this has been tested, the effectiveness of masks using this kind of method, using a control group and a mass group and there've been a number of these studies that have been done and I'm gonna look at studies primarily before 2020.

Randomized Trials and Systematic Reviews Before 2020

Why?

Because once the government gets involved, politics begins to obscure science. Think about it, once the government says you have to wear masks, masks are effective. Suppose you're a researcher and you're funded by the government, are you going to come to the conclusion, no, that's not true and lose your funding?

And I'm not saying, I'm not accusing anyone of being unethical, I'm just saying that they're people who suspect that masks maybe aren't so effective, would not be as likely to do the experiment because they might lose their funding.

You can understand these things, these are real world issues so we're gonna look at issues, we're gonna look at studies before 2020 when nobody had a dog in the fight and that's gonna reduce biases. You can't totally eliminate biases but it'll reduce it.

So one of the ones that I looked at, it's called a cluster randomized trial of cloth masks compared with medical masks in healthcare workers. This was published in 2015, the experiment was actually done in 2011 and it was reported in 2015.

Now one of the things they found in the study is that penetration of cloth masks by particles was almost 97%. So folks, these kind of cloth masks, the one I have, they don't block hardly anything, particles go right through those, microscopic particles the size of viruses and aerosols that carry this virus, they go right through.

They found medical masks however, have a penetration of 44%, not bad. So they're blocking about half the particles that go through, does that have an effect? Is that better than not wearing a mask or is the fact that you have to breathe harder and some of these other variables, does that shift things the other way?

Well, here's their result. They said a post hoc analysis adjusted for compliance and other potential confounders showed that the rate of influenza-like illness, ILI, was significantly higher in the cloth mask arm compared with the medical mask arm.

There was no significant difference between the medical mask arm and the control arm.

Interesting.

And by the way, I have to point out that in this study, the control arm ideally should be no masks, but they decided that it would be unethical to ask people not to wear masks at all. So the control group was masks optional.

It was sort of the, whatever you normally do. And many people in the control group did wear masks, either cloth or medical. So it's the control groups, it's hard to know what to make of that in this instance.

But I think it's interesting that nonetheless, the control group being as close as you can get to no masks actually had the same infection rate as those who were wearing the quality surgical masks, the medical masks.

And the cloth masks had a greater infection rate. You were more likely to get infected if you were wearing a cloth mask. They also say hand washing was significantly protective against laboratory confirmed viral infections.

So wash your hands, wash your hands, that does work. They go on to say cloth masks resulted in significantly higher rates of infection than medical masks, and also performed worse than the control arm.

They go on to say the trend for all outcomes showed the lowest rates of infection in the medical mask group and the highest rate in the cloth mask arm. So according to this study, the worst thing you could possibly do is put one of these things on, one of these cloth masks.

You're actually more likely to get infected according to that study. They say this study is the first randomized control trial of cloth masks, and the results caution against the use of cloth masks. This is an important finding to inform occupational health and safety.

Now, I do have to point out that the viruses in this study were influenza-like viruses, influenza and similar viruses. Influenza viruses are actually larger than COVID -19 viruses. And so if masks don't keep you, protect you from influenza viruses, then they certainly aren't gonna protect you from COVID -19 viruses.

Obviously they can't do an experiment on COVID -19 at this time, it hadn't been discovered yet. And so most of these studies are studying influenza-like viruses, which is a good proxy for COVID -19, because influenza viruses are just a little bit bigger than COVID -19.

Okay, here's another one. Face mask use and control of respiratory virus transmission in households. We conducted a prospective cluster randomized trial comparing surgical masks, non-fit tested P2 masks, and no masks in prevention of influenza-like illness in households.

So they have three groups, and they say during the 2006 and 2007 winter seasons, 286 exposed adults from 143 households who had been exposed to a child with clinical respiratory illness were recruited.

Intent to treat analysis showed no significant difference in the relative risks of ILI, influenza-like illness, in the mask use groups compared with the control group. You mean the surgical masks didn't improve your odds?

Nope.

The non-fitted P2 masks didn't improve your odds of not getting infected?

Nope.

Now, of course, it's possible that there's some small effect, but it's apparently outside the error bars, and therefore it's not statistically significant. There could be a small effect, but there can't be a large effect, not according to that study.

Okay, here's another one that's published in 2009. Use of surgical face masks to reduce the incidence of the common cold among healthcare workers in Japan, a randomized control trial. Now, of course, the common cold is caused by a virus, rhinovirus, most of them, some of them coronaviruses, albeit not the SARS-CoV -2 virus.

So what did they find? Here's their conclusion. Face mask use in healthcare workers has not been demonstrated to provide benefit in terms of cold symptoms or getting colds. So you wore the surgical mask, you were just as likely to get a cold, and the symptoms were just as severe.

Made no difference at all. And these are surgical masks, these are the good ones, not the cloth masks. Okay, here's another study. Face masks to prevent transmission of influenza, a systematic review that was done in 2010.

What do they conclude? There is little evidence to support the effectiveness of face masks to reduce the risk of infection. Interesting, and of course, they're comparing a number of different studies there.

Another one from 2011, the use of masks and respirators to prevent transmission of influenza, a systematic review of the scientific evidence. And so they're looking at a bunch of different studies. What do they conclude?

None of the studies established a conclusive relationship between masks, respirator use, and protection against influenza infection. Here's another study from December, this is 2017. Effectiveness of masks and respirators against respiratory infections in healthcare workers, a systematic review and meta-analysis.

Okay, what do they find? Compared to masks, N95 respirators conferred superior protection against CRI and laboratory-confirmed bacterial, but not viral infections or influenza-like illnesses. So these things help when you're, they can block bacteria, because bacteria are much larger than viruses.

So masks do provide some benefit against bacteria, at least for some period of time, until the bacteria build up to a certain point. They go on to say, meta-analysis suggested a protective, but non-statistically significant effect against laboratory-confirmed viral infections.

So they did see just a little bit of a bump, but it was not outside the error bars. You can't say that these masks convert any kind of positive benefit in reducing viral infections. So here's another one.

Preliminary findings of a randomized trial of non-pharmaceutical interventions to prevent influenza transmission in households. And so they actually looked at a few things. They're looking at the influenza virus.

So after influenza was confirmed in an index case, by, and they have a particular test they used for that, the household of the index subject was randomized to one, control, two, surgical face mask, or three, hand hygiene.

What conclusion did they find? The laboratory-based or clinical secondary attack ratios did not significantly differ across the intervention arms. Isn't that interesting? Didn't seem to have much of an effect.

What about, here's another one. The role of face masks and hand hygiene in the prevention of influenza transmission in households results from a cluster randomized trial. And this was done in Berlin, Germany.

So now they start by saying previous control studies on the effect of non-pharmaceutical intervention, NPI, namely the use of face masks and intensified hand hygiene in preventing household transmission of influenza have not produced definitive results.