4 ms·

The fact that there is no CLEAR evidence that masks are effective at improving COVID outcomes tells you that if they do have an effect, the size must be small.

by tyho 4y ago

The fact that there is no CLEAR evidence that masks are effective at improving COVID outcomes tells you that if they do have an effect, the size must be small. If they worked well, anywhere near say preventing 50% of infections, then you would not need complicated statistical analysis to tease out marginal hazard ratios from massive data sets.

DoingIsLearning 4y ago
I think the biggest problem is putting _all_ masks in the same bucket. The selection criteria is too wide. I have used 'duck beak' ffp3 masks through several flights during peak pandemic, and I had to physically workout my chest muscles to take a full breath of air in. I have also bought disposable masks online that were paper mache level. Both cases are 'people wearing masks' but I can guarantee that these two masks are not having the same effect. We can argue logistics and feasibility of everyone using ffp3 masks, but claiming that masks don't have clear evidence is to ignore the whole physics of filtration.
- qeternity 4y ago
  And then you rub your eyes as you nod off for a nap on the plane. We know that airborne transmission has been a small piece of the puzzle. But masks are visible and so the only thing we could do for security theater. And we turned the response into this virtue signaling debate. Even this thread has people bending over backwards to defend their views...that's not how science works! I do not believe that masks _increase_ mortality. But I think it's pretty clear that masks have minimal, if any, impact on transmission.
  - DoingIsLearning 4y ago
    > We know that airborne transmission has been a small piece of the puzzle. Do you have a quote for this claim? Everything I read is claiming the exact opposite, that authorities overstated the contact surface transmission and that the majority of SARS-COV2 infections occur through droplets or aerosol.
  - lamontcg 4y ago
    > And we turned the response into this virtue signaling debate. By mentioning 'virtue signaling' you are virtue signaling that you share the views of a good chunk of the HN readership. Everyone now knows what side you lean towards, and can assume what affiliated views that you might have.
- manwe150 4y ago
  For what it is worth now, there a number of mask comparative analyses out there now (eg wirecutter) which measured the filtration and give recommendations on which masks are both easy to breathe through and good at filtering. It is not always the ones that are hardest to breathe through (though the counterfactual is generally true: being harder to breathe through generally corresponds to higher filtration)
- kingofpandora 4y ago
  Wow I can't even imagine a mask that is like papier mâché. Link to one of those so I can see what they look like?
Lutger 4y ago
Maybe, maybe not. First, efficacy below 50%, even at 10%, can be argued to be worthwhile from both an epidemiological point of view and from the purpose of individual protection. Second, I'm not convinced that your conclusion follows from the premise. I don't see why this must be so and you haven't given a reason. Confounding factors in other comments here are used as an argument against using the findings as evidence for mask efficacy. Note that if those arguments have any merit at all, they are also valid against your conclusion. It's really hard to prove some things scientifically. But that doesn't imply the effects are small, just that to move from correlation to causality is not easy at all.
- native_samples 4y ago
  It's really hard to prove some things scientifically. But that doesn't imply the effects are small, just that to move from correlation to causality is not easy at all. In this case it's easy because there's no effect. The sort of argument you're making above has become common in threads like these, but it's based on what looks a bit like template/pattern matching rather than logic. See also the comment below by ltbarcly3 which is correcting another instance of this. I noticed this problem crops up in COVID threads a lot. Confounding factors matter when there is a correlation and you're trying to explain causation, because it means you might infer causality wrongly when in reality there's a confounder that explains it differently. Confounding factors are irrelevant when there's no correlation to explain, unless you posit that there actually is an effect but a confounder perfectly balances it out in the opposite direction. If you go there you'd better have really good evidence of it because (a) that's quite unlikely a priori and (b) that evidence is all that would stand between you and hallucinating things that aren't real. In this case there is no effect to explain. Neither masks nor lockdowns have any observable effect on outcomes and this has been demonstrated six ways from Sunday, from the start of COVID. A lot of people desperately struggle to accept this because of what it implies about the honesty and competence of public health authorities, but the fact remains that these interventions had no effect and there are many studies showing this. You don't really need studies of course. Just looking at case graphs is enough to see this for yourself, because mask mandates were justified on the basis that they'd have a big impact on those graphs. When they don't do that reliably, it automatically means the policy is a failure. It's still nice to rigorously characterize the lack of effect, though. Because there's no effect that means "correlation doesn't imply causation" is an invalid argument, it means "but real world data can be confounded" is irrelevant because there's nothing to be confounded, and it means a whole lot of other arguments that crop up in discussions of bad science are irrelevant. All these things are common objections to bad science because academics are so keen to announce effects in data that aren't real. They're therefore possibly valid objections to studies where masks or lockdowns are claimed to create real effects, but they aren't valid objections to studies supporting the null hypothesis.

by tyho 4y ago

DoingIsLearning 4y ago

I think the biggest problem is putting _all_ masks in the same bucket. The selection criteria is too wide. I have used 'duck beak' ffp3 masks through several flights during peak pandemic, and I had to physically workout my chest muscles to take a full breath of air in. I have also bought disposable masks online that were paper mache level. Both cases are 'people wearing masks' but I can guarantee that these two masks are not having the same effect. We can argue logistics and feasibility of everyone using ffp3 masks, but claiming that masks don't have clear evidence is to ignore the whole physics of filtration.

qeternity 4y ago
And then you rub your eyes as you nod off for a nap on the plane. We know that airborne transmission has been a small piece of the puzzle. But masks are visible and so the only thing we could do for security theater. And we turned the response into this virtue signaling debate. Even this thread has people bending over backwards to defend their views...that's not how science works! I do not believe that masks _increase_ mortality. But I think it's pretty clear that masks have minimal, if any, impact on transmission.
- DoingIsLearning 4y ago
  > We know that airborne transmission has been a small piece of the puzzle. Do you have a quote for this claim? Everything I read is claiming the exact opposite, that authorities overstated the contact surface transmission and that the majority of SARS-COV2 infections occur through droplets or aerosol.
- lamontcg 4y ago
  > And we turned the response into this virtue signaling debate. By mentioning 'virtue signaling' you are virtue signaling that you share the views of a good chunk of the HN readership. Everyone now knows what side you lean towards, and can assume what affiliated views that you might have.
manwe150 4y ago
For what it is worth now, there a number of mask comparative analyses out there now (eg wirecutter) which measured the filtration and give recommendations on which masks are both easy to breathe through and good at filtering. It is not always the ones that are hardest to breathe through (though the counterfactual is generally true: being harder to breathe through generally corresponds to higher filtration)
kingofpandora 4y ago
Wow I can't even imagine a mask that is like papier mâché. Link to one of those so I can see what they look like?

Lutger 4y ago

Maybe, maybe not. First, efficacy below 50%, even at 10%, can be argued to be worthwhile from both an epidemiological point of view and from the purpose of individual protection. Second, I'm not convinced that your conclusion follows from the premise. I don't see why this must be so and you haven't given a reason. Confounding factors in other comments here are used as an argument against using the findings as evidence for mask efficacy. Note that if those arguments have any merit at all, they are also valid against your conclusion. It's really hard to prove some things scientifically. But that doesn't imply the effects are small, just that to move from correlation to causality is not easy at all.

native_samples 4y ago
It's really hard to prove some things scientifically. But that doesn't imply the effects are small, just that to move from correlation to causality is not easy at all. In this case it's easy because there's no effect. The sort of argument you're making above has become common in threads like these, but it's based on what looks a bit like template/pattern matching rather than logic. See also the comment below by ltbarcly3 which is correcting another instance of this. I noticed this problem crops up in COVID threads a lot. Confounding factors matter when there is a correlation and you're trying to explain causation, because it means you might infer causality wrongly when in reality there's a confounder that explains it differently. Confounding factors are irrelevant when there's no correlation to explain, unless you posit that there actually is an effect but a confounder perfectly balances it out in the opposite direction. If you go there you'd better have really good evidence of it because (a) that's quite unlikely a priori and (b) that evidence is all that would stand between you and hallucinating things that aren't real. In this case there is no effect to explain. Neither masks nor lockdowns have any observable effect on outcomes and this has been demonstrated six ways from Sunday, from the start of COVID. A lot of people desperately struggle to accept this because of what it implies about the honesty and competence of public health authorities, but the fact remains that these interventions had no effect and there are many studies showing this. You don't really need studies of course. Just looking at case graphs is enough to see this for yourself, because mask mandates were justified on the basis that they'd have a big impact on those graphs. When they don't do that reliably, it automatically means the policy is a failure. It's still nice to rigorously characterize the lack of effect, though. Because there's no effect that means "correlation doesn't imply causation" is an invalid argument, it means "but real world data can be confounded" is irrelevant because there's nothing to be confounded, and it means a whole lot of other arguments that crop up in discussions of bad science are irrelevant. All these things are common objections to bad science because academics are so keen to announce effects in data that aren't real. They're therefore possibly valid objections to studies where masks or lockdowns are claimed to create real effects, but they aren't valid objections to studies supporting the null hypothesis.