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Comment by mnw21cam | Hacker News Reader

While this is a very interesting study, it absolutely cannot show that masks are or are not effective at reducing covid transmission. There are so many confounding factors, the results are basically meaningless.

The most obvious confounding factor is of course that as covid rates rise, people are more likely to wear a mask. This by itself explains the positive correlation between mask compliance and covid rates.

The paper says that the positive correlation is surprising. It is not.

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it absolutely cannot show that masks are or are not effective at reducing covid transmission. There are so many confounding factors, the results are basically meaningless.

It can show that. If masks were effective there would be visible inflection points in the data that correlate with mandates being added and removed, as those make a huge difference to mask wearing. Where I lived before the first mask mandate, almost nobody was wearing them. The day the law changed, nearly 100% were wearing them and it remained that way until the mandates were removed.

We're not talking tiny effect sizes here. These were massive, overnight changes. To justify the impositions on people, there should have been correspondingly massive effects. There were none.

The most obvious confounding factor is of course that as covid rates rise, people are more likely to wear a mask.

Why people wear them is irrelevant to the question of whether they work or not.

There should be an inflection in the exponent of the rate (eg changing only the magnitude of the peak), not necessarily in the direction of the graph, and not necessarily even changing the timing (aka flatten the curve). The difficulty of analyzing the data is what makes studies and articles like this still interesting and relevant to consider.

There's also a long delay between any actions taken and the actual effect on infection rates, and especially hospitalisation and death rates, which makes analysing it even more tricky.

The serial interval of SARS-CoV-2 is/was claimed to be at the start ~3 days. So the delay is very short and this is one reason why we can be so sure masks had no effect. If they did, you would expect to see a sharp and visible inflection point in the graph three days later.

However no such inflection points are visible and this happens repeatedly.

Why do you expect an inflection point? At steady-state, there should be a change of that sort described. But the hypothetical intent was to establish these masking policies while still in the early, exponential portion of the graph. When the spread is doubling every 3 days, shouldn’t we expect it to be hard to visually observe a change to the number of days it takes to double the cases? That thus rhetorically leaves us stuck with a significant difference between “no effect” and “moderate-but impossible-to-quantify effect” however

The serial interval is/was three days, that's not the same thing as doubling time. Serial interval is how long it takes someone who just got infected to become infectious and pass it on.

Regardless, the answer is no. Inflection points should be clearly visible because the underlying dynamic is organic, and mass-scale human intervention is inorganic/synchronized. Remember - the policy is justified exclusively on the basis of creating those inflection points. Nothing else. If no such points are visible the policy is a failure and we're left with only the downsides (of which there are many!).

I think you are thinking of the term discontinuities? Inflection points are notoriously not easily visible in graphs. Here’s an inflection point for example: https://www.calculushowto.com/inflection-point/

>The most obvious confounding factor is of course that as covid rates rise, people are more likely to wear a mask.

Another confounding factor is that the West has many densely populated cities AND good record-keeping regarding mortality. As you get into poorer and poorer countries, you must also take into account the likelihood of error in their mortality statistics.

You must also consider that those who are less likely to wear a mask (even with a mandate) may also be otherwise more likely to contract and spread covid in the first place, and as long as there is a sufficiently large network of those people for the virus to operate in, mask mandates may make no overall difference in the mortality even if it were 100% effective in preventing death. Ie, if the virus was always primarily circulating among people unlikely to wear a mask, a mask mandate would make little difference. Mask mandates affect public behavior, but it may very well be that what people do in private is much more significant for transmission.

We shouldn't rush to trust the numbers from Western nations.

Consider the counting approach used in Toronto, which is Canada's most populous city, and the fourth most populous city in North America.

According to Toronto Public Health:

"Individuals who have died with COVID-19, but not as a result of COVID-19 are included in the case counts for COVID-19 deaths in Toronto."

https://twitter.com/TOPublicHealth/status/127588839006028596...

That seems like a fundamentally flawed counting approach to me.

Suppose a person is infected, but he's showing no symptoms, and doesn't even realize he's infected.

He feels just fine, and goes for a long-distance bike ride. Near the end of it, he's hit by a transport truck that runs a red light, and he suffers severe head injuries.

He's taken to the hospital, where he is tested as a precaution, and his test returns a positive result. Due to the severity of his head injuries, he dies a few hours later.

If that happened in Toronto, then he'd apparently be counted as a "COVID-19 death", despite the infection having absolutely nothing to do with his death.

Of course, that's just one of many ways that somebody infected could die in a way that has absolutely nothing to do with an infection.

Any count that includes things completely unrelated to that which are meant to be counted is a count that shouldn't be trusted.

> Suppose a person is infected, but he's showing no symptoms, and doesn't even realize he's infected ... hit by a transport truck

It's easy to invent a scenario that wouldn't get counted correctly.

Here's one that wouldn't get counted correctly with your method:

"Suppose a person is hospitalized for diabetes and would have a 95% chance of surviving, except that she also has covid which reduces her survival probability to 40%."

There are two or three orders of magnitude more hospitalizations for [diabetes + covid] than [massive head trauma when hit by a truck + covid].

So maybe we should use the counting method that is least inaccurate overall, and not try to optimize for rare events?

In this case, a systematic error wouldn't change the conclusion as long as the same method was used for all countries.

As for the broader argument about people dying with COVID vs people dying of COVID, the excess mortality rates are consistent with the assumption that the reported death rate from COVID in Western nations is pretty accurate, and may even undercount the true figure (see e.g. https://www.nature.com/articles/d41586-022-00104-8).

Suppose a person is your average overweight middle aged sedentary American and they die of a stroke and happen to test positive for the virus.

There's a pretty good chance they died of COVID-19-associated immune thrombocytopenia, even though they may not have been symptomatic when they died.

A lot of those cardiac events are going to go uncounted if a country isn't testing for the virus, or isn't attributing CVAs to the virus when the person didn't really have any respiratory complications / pneumonia.

Of course you can’t always see direct causality in a complex system, but aren’t there already controlled experiments that showed that face masks reduce risk of transmission? Those were the basis for health experts to recommend the measure in the first place.

So there were no experiments that could definitely say whether masks help against flu or SARS but with Covid-19 the science is settled?

The fact that we've had prior "events" and didn't /don't understand the strengths and weaknesses of the public health tools (e.g., various types of masks) is worrisome.

Looking at what medical professional said during the beginning on the pandemic, the general understanding of the strengths and weaknesses of mask seemed to have been fairly good. Mask are classified and tested based on medical criteria, and hospital and other industries use them during high risk situations since it has been proven effective in such scenarios. The lack of understanding was primarily when mask got taken outside the context of high risk situations and into general use in outdoor and indoor environments, and for purposes which the masks classifications don't consider. Everything from an airplane with circulated air, to people outside on a beach in the fresh breeze. On top of that we have politicians making the decision rather than medical professionals.

There are however fairly low understanding of other public health tools that is outside the scope of what medical professionals can do. Shutting down mass transportation, restricting travel, shutting down social activities. Finland as an example fully closed down their capital during the start of the pandemic, preventing almost all movement in and out of the city. Looking at the graphs, that alone might have been what attribute the low case and death rates, and its not something that the medical profession has many studies on.

It wasn't until deep into the pandemic (18+ months) that, in the USA, the CDC emphasized the KN95 masks or better.

That doesn't say there was a clear understanding. So not only were many effectively not wearing masks, we now can't make reliable heads or tails of the "post match" data.

If that's not negligence, then it was intentional. Neither is a good explanation.

Maybe it was because of unavailability of that much masks of suitable properties (KN95/FFP2) for all people, and inertia to realize that situation?

And then, saying at least Duck&Cover! in case of a thermonuclear explosion, because SDI/Iron Dome/Someshinyshield failed. Better late than never? Or nothing at all?

At some point they had to say something.

So they knowingly "exaggerated" the effectiveness of the masks most ppl were using, and to cover their ass there has been - sans the CDC announcement - zero effort to update that narrative? And these are the same ppl and entities insisisting "trust us" and "trust the science"?

This ^^^ isn't a conspiracy theory. This is what happened and is still happening. How am I, or anyone, supposed to truth that architecture?

Masks reduce the risk of transmission a lot that is pretty clear as far as I know but

* Are they used correctly by the majority?

* Are the situations where masks are/were used actually the main contributors to infections overall?

* How well do masks work in situations with long time of contact and wearing (public transport, on the job site, ...)?

* + Probably a lot of other questions

So it can very well be that the impact of masks overall and in comparison with other measures is lower than controlled experiments suggest. If that's the case it does not mean wearing a mask is a bad idea but knowing this could influence decisions on mandating doing it.

I’m not aware of any RCT that could control for the variables to measure transmission. That would be very hard. But two RCT studies have been done to measure infection on the individual wearing it and they show cloth and surgical masks as not significant. Of course there’s a lot of nuance to the results but it’s obvious the signal isn’t there unlike say the vaccine during its RCT.

I sincerely suggest you to read the history instead, starting from the scandals who have followed all recent pandemic declaration by the WHO: H2N2 (1957), H3N2 (1968), SARS-CoV (2003), H5N1 (2004), H1N1 (2009), MERS-CoV (2012) ALL OF THEM ended with inquiries about their nature, all of those conclude that NO SUCH MEASURE suggested by WHO have had positive effects except for the private lenders of the WHO.

I think that's enough to conclude that on one side peoples are to fragile to Bernaysian propaganda, on the others there are criminals who need to be evicted for the sake of humanity. Sorry for the rude tone, but that's is.

I downvoted this comment because you provide no actual references to support your argument.

I avoided that on purpose: we are so trained to find answers on click that we forgot how and why search. If you are interested and you look for you'll see that some filters bubble around you have made you only see a certain narrative. Looking for something else, you'll break the bubble discovering on your own something new, something you do not expect.

Anyway, few starting points:

- the famous, for those who have searched official sources and collected evidence along years to grab that when needed in the future, intervention to the European Council from the May 26, 2010 just an year after the H1N1 pandemic declaration: https://assembly.coe.int/CommitteeDocs/2010/20100126_Stateme... or if you prefer the press https://www.pharmatimes.com/news/eu_to_probe_pharma_over_fal... you might also like some other sources like the British Medical Journal https://doi.org/10.1136/bmj.c2912 for the pdf https://www.bmj.com/bmj/section-pdf/186584?path=/bmj/340/775...

- something from a bit more past https://www.ema.europa.eu/en/documents/product-information/p... while just in the meantime something have already emerged https://doi.org/10.1086/652719 and just check the press at that time https://www.nytimes.com/2006/02/12/weekinreview/greetings-ki...

Is it enough to stimulate your appetite and dig yourself? If you do for all pandemic declaration I cited you'll find the same press coverage just-before, during, after, same patterns and same scandals. Again from OFFICIAL, governmental sources, of course.

If you dig a bit more you'll discover various WHO publications about how flu vaccines, vaccines in general are the future of drug BUSINESS because they target healthy people, so the vastest cohort of consumers of drugs possible concluding that those will the the future earning for Big Pharma.

You really have to dig yourself though because you'll see how hard is finding things without the right keywords and so how easy is to convince even skilled and acculturated people of something thanks to modern way of "consuming" news. Only with that discovering you'll start to dig in anything else.

For instance just to add something "hot" right now: try digging about Ukraine, you can start from https://www.osce.org/files/f/documents/e/7/233896.pdf and https://www.rand.org/pubs/research_briefs/RB10014.html after having read the old DNI report 2004 (who also talk about pandemics) https://www.dni.gov/files/documents/Global%20Trends_Mapping%...

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