13 ms·

I've spent a lot of time reading the science over the last year and a half or so. These claims of gaslighting go both ways. I've seen numerous studies passed of

I've spent a lot of time reading the science over the last year and a half or so. These claims of gaslighting go both ways. I've seen numerous studies passed off as fact and that have been used to guide policy with unacceptably low sampling sizes or other sampling problems. I've seen very little 'good' science being conducted over the last year. You've got inadequately sampled studies throughout the duration of covid that have led to drastic policy decisions, I've seen biased studies coming from massive corporations being used to guide policy decisions and not one step along the way have I seen anyone who's gone... 'Hey wait a second, maybe we should check this data before we take drastic action' Be listened to or taken seriously.

newacct583 6y ago
Care to name some examples? I mean... the broad arc of the policy choices have been correct, right? Stay home. Wear a mask. That stuff works. We thought it worked last April and we were right. There's some genuine argument about the efficacy of specific facilities, like schools. But that's stuff at the margin. I guess I don't see any good candidates for the "drastic policy decisions" based on "biased studies from massive corporations"... Really most of what the world did was pretty textbook disease control stuff. What is it you mean?
- neilwilson 6y ago
  The reliance on unusual concepts - like asymptomatic transmission and the effect of wearing masks which have become semi-religious in their belief even though there isn’t really any actual solid RCT evidence they do that much good out in the field rather than in the lab (much like hydroxychloroquine which is similarly effective in a lab but not in the field). There is no blow out in Texas et al and Sweden has just tracked the same path as everybody else suffering much less than Belgium for example, and today isn’t anywhere near the top of the charts. There’s an awful lot of curve fitting to beliefs going on - because it is so difficult to do solid experiments.
  - watwut 6y ago
    How is symptomatic transmission unusual concept?
    - timr 6y ago
      Asymptomatic transmission is the concept in question. Symptomatic transmission is the typical case -- you cough, sneeze, etc., and give it to others. There's still quite a bit of debate over this question, despite the article's insistence that the matter is settled. The data supporting it comes mostly from modeling studies, and real-world data is thin on the ground. Mostly anecdotes. We have lots of examples of pre-symptomatic (or minimally-symptomatic) transmission for other illnesses, but these tend to be limited (e.g. spread within households), and it's always been a bit of a stretch to make the claim that completely healthy people are spreading diseases widely in "super-spreader" events via casual encounters. Does it happen? Sure. Is it common? Ehhhh. Even with Covid, we know that the majority of transmission (something like 80%) occurs within households. Of the remainder, as TFA notes, there's an "overdispersion", where a few people are responsible for most of the spread. Is it really likely that these "superspreader" people are mostly completely healthy, without symptoms, and yet unknowingly spreading it to vast numbers of people? Or is that just something that we've found a few times, and makes the most memorable anecdotes? It is certainly not the hypothesis you would favor based on parsimony alone. If you were a betting person, you'd probably put your money on the idea that someone is a little bit sick (but not so sick as to stay home in bed), and the disease can spread by aerosol or droplet with low probability. That's a much simpler explanation for the same pattern: someone has a tickle in their throat or a slight fever, but goes to the restaurant/office/wherever anyway. Set the probability of transmission to a low p-value, and let the poisson distribution do the rest. Just by chance alone, you will see rare occasions where large(r) groups of people get infected.
      - watwut 6y ago
        I had typo. But AFAIK, asymptomatic transmission is not novel concept. We have been learning about it in elementary school in the context of other diseases. There is absolutely nothing new about it as concept. It is not something that appeared with covid first time in history of diseases.
- erostrate 6y ago
  The WHO initially said there was no evidence supporting the need for masks in the general public. They only changed their stance in early June. In Europe many politicians were making the same claim, which was convenient because they didn't have enough masks.
  - 6gvONxR4sf7o 6y ago
    At the time, I thought the general guidance was “don’t hoard masks, we need them for healthcare workers” rather than “don’t wear masks they don’t work” (which through the game of telephone turned into everything imaginable).
    - EmbeddedLight 6y ago
      The outrage comes from government and other health officials making claims early on that masks were not as effective, and that maintaining social distance and isolation was better (which I agree). But this was merely used as distraction to allow healthcare facilities to snatch up the existing supplies of high quality n95 masks before the public could (see toilet paper apocalypse 2020). Then the government changed their statements and said that masks were effective, and everyone should use them. It's the switching and lying to the public that leads to a lack of trustworthiness. You can argue that they didn't know the efficacy of mask usage, but that isn't the point here. It's that they lied to the American public for an ulterior motive, which is wrong.
  - viklove 6y ago
    The WHO is a political organization, not a scientific one.
- mike_hearn 6y ago
  I've read a lot of public health papers in the past year, probably more than 50. Here are some of the problems that cropped up in papers that were used by governments to support policy decisions. Many of those policy decisions later turned out to be incorrect, like lockdowns and mask mandates, both of which easily count as drastic and neither were textbook. In fact pre-COVID pandemic control plans by the WHO explicitly recommended against lockdowns. By the way, be careful to separate the question of mask mandates from masks themselves. Mask mandates don't work: just look at case curves when mandates were introduced or removed and observe the lack of inflection points. If they worked people would have hundreds of examples by now of case curves which obviously inflected right after a mask mandate was changed, but no such graphs are ever cited because those inflections don't reliably happen. Texas provides a recent example (mandate removed, curve continues prior trend) but this problem was obvious from within a week of the first mandates being introduced. Look at [1] for some case graphs with mandate change dates drawn on them to see the problem. Anyway, errors seen in public health papers: 1. Circular reasoning. 2. Invalid citations. 3. Programming errors in models. 4. Use of extremely out of date numbers. 5. Absurd or obviously invalid assumptions and results in models being ignored. That's not a comprehensive list. Unfortunately these aren't rare problems. Virtually every public health paper I've read has had at least one of these issues, often multiple. Circular logic in particular is mind-numbingly common, to an extent I've never seen before. For example, a common "validation" technique for models is to compare them to other models and declare their outputs to be similar (e.g. [2] or [3]). It's almost unheard of to compare model outputs to actual observed data, probably because doing validation right would invalidate virtually all public health models (this problem was admitted in a 2012 paper [4]). For a specific example of these problems see the paper by Flaxman et al from Imperial College London [5]. This paper argued that lockdowns work using a statistical model, but they actually don't work, so to get this result required a combination of: 1. Circular logic: the model took as a starting assumption that case curves could only be changed by government intervention. In other words the paper encoded its own conclusions in its assumptions. The assumption epidemics can only be affected by lockdowns has no rational basis given the long history of epidemics starting and ending naturally. 2. The paper included Sweden in its data set, which attracted attention because Sweden appears to prove that the models generating the counterfactual were wrong. It managed to conclude lockdowns worked despite this because it concluded Sweden was a freak coincidence with an only 1 in 2000 chance of existing at all; in the graph that showed the different per-country fudge factors the model was allowed to calculate, Sweden was simply hidden to obscure what had happened. The truth was discovered later by people who studied the tables of prior probabilities uploaded to GitHub. 3. The paper admitted half way through that its scenario was "illustrative only" and that "in reality" the results would be different. There were other problems too, but none of them stopped the authors telling the press that lockdowns had "saved millions of lives" (i.e. the drastic policy pushed for by that very same research team). Nor did it stop international press agencies citing this paper in "fact checks". After reading so many papers with really basic and blatant problems, it's hard not to conclude that open access is going to seriously damage academia's credibility. Being able to just download and read the output of academic scientists is a very new thing, and one of the few highlights of the time I've spent reading COVID research is that open access is real now: I've hardly ever hit paywalls. Only for old papers. Unfortunately open access is a double edged sword. Now we can all read what we're paying for and observe the dangerously low quality. The outcome will probably be a large expansion of the battle between "science believers" and "science skeptics". Up until now that has been mostly restricted to debates on climatology, but now I think it will widen considerably. There's just no way to read the literature and retain your confidence in academic science when so much of it is entirely un-scientific. [1] https://rationalground.com/mask-charts/ https://rationalground.com/mask-charts/ [2] https://github.com/ptti/ptti/blob/master/README.md https://github.com/ptti/ptti/blob/master/README.md (see the paragraph starting with "Formalism-agnostic"). [3] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001435/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001435/ ("There is agreement in the literature that comparing the results of different models provides important evidence of validity and increases model credibility") [4] ibid; ("few models in healthcare could ever be validated for predictive use. This, however, does not disqualify such models from being used as aids to decision making") [5] https://nicholaslewis.org/did-lockdowns-really-save-3-million-covid-19-deaths-as-flaxman-et-al-claim/ https://nicholaslewis.org/did-lockdowns-really-save-3-millio...
- vondur 6y ago
  I’m pretty skeptical at this point that masks made any difference. Here in Southern California where everyone wears masks indoors, and even the majority of people wear them outdoors. Yet we still ended up with some of the highest infection rates in the country. I’d wager if we gave the people who are most susceptible to the disease N95 masks, we’d have seen a much lower hospitalization and death rates.
  - higeorge13 6y ago
    It might have made a difference, but we do not have a stable reference case to observe the difference. It might have reduced 1, 2, 10, 20% the number of infections, who knows? In the end it's just a piece of paper/cloth in our faces; i personally don't get this anti-mask sentiment as if we are placing something really bad in our mouths.
    - xxxxhhhh 6y ago
      > In the end it's just a piece of paper/cloth in our faces Humans are social creatures as the result of millions of years of evolution. There’s profound effects when facial social cues are erased and people are widely deprived of socialization.
  - hello_moto 6y ago
    I observed many people around me use ineffective mask or don't wear it properly. Basic health hygiene requires discipline that may take years to develop if not mandated and enforced/practiced. Too many variables to be a mask skeptic given Cali situation...
- graeme 6y ago
  Some mistaken policy choices: * Not requiring masks at workplaces or schools once seated (common in many areas) * Not aiming for ventilation and denying aerosol spread * Denying asymptomatic and presymptomatic spread. Giving health/testing advice mainly based on symptoms * Not using and blocking rapid tests * Not scaling testing capacity with cases Japan had a more coherent approach on some of these with their three C’s approach: avoid closed spaces, crowded rooms, and close contact. The West generally just emphasized the latter. (The west did have capacity limits, but only to space people out within rooms, not for aerosols)
redis_mlc 6y ago
> I've spent a lot of time reading the science over the last year and a half or so. Pro tip: there wasn't any science to read. Pro tip 2: when a pandemic's origin contains a lab that studies and publishes that virus, it's from the lab.
throwawaysea 6y ago
I think the word “science” itself has lost meaning. Many people I know have yard signs that say “science is real” but in practice these same people can be easily manipulated by bad studies that are cycled through news media and social media. They also often listen to science only when it agrees with their views. I think like what came before, popular science is turning into an act of blind faith. We certainly see this with blind belief in “scientific authorities” who can get things very wrong (like the WHO). We also see it with fact checkers - as an example, I remember reading a (factually correct) article on Facebook yesterday about COVID lockdowns, which mentioned the infection fatality rate. This post had a fact check content warning, from a fact checker who incorrectly quoted the case fatality rate for COVID-19 as evidence that the article was misinformation. I’m not sure what the fix is. It feels like there is too much information out there for the public to handle and process properly. Or maybe we need a new word that is not “science”, that captures more of the critical thought that is needed, and moves us away from blind faith.
- gher-shyu3i 6y ago
  Scientism is basically a religion nowadays. This has lead to the rise of certain figures, such as Neil deGrasse Tyson, who start talking way beyond their fields - and rarely questioned, and then start judging others and imposing their own morality.

newacct583 6y ago

Care to name some examples? I mean... the broad arc of the policy choices have been correct, right? Stay home. Wear a mask. That stuff works. We thought it worked last April and we were right. There's some genuine argument about the efficacy of specific facilities, like schools. But that's stuff at the margin. I guess I don't see any good candidates for the "drastic policy decisions" based on "biased studies from massive corporations"... Really most of what the world did was pretty textbook disease control stuff. What is it you mean?

neilwilson 6y ago
The reliance on unusual concepts - like asymptomatic transmission and the effect of wearing masks which have become semi-religious in their belief even though there isn’t really any actual solid RCT evidence they do that much good out in the field rather than in the lab (much like hydroxychloroquine which is similarly effective in a lab but not in the field). There is no blow out in Texas et al and Sweden has just tracked the same path as everybody else suffering much less than Belgium for example, and today isn’t anywhere near the top of the charts. There’s an awful lot of curve fitting to beliefs going on - because it is so difficult to do solid experiments.
- watwut 6y ago
  How is symptomatic transmission unusual concept?
  - timr 6y ago
    Asymptomatic transmission is the concept in question. Symptomatic transmission is the typical case -- you cough, sneeze, etc., and give it to others. There's still quite a bit of debate over this question, despite the article's insistence that the matter is settled. The data supporting it comes mostly from modeling studies, and real-world data is thin on the ground. Mostly anecdotes. We have lots of examples of pre-symptomatic (or minimally-symptomatic) transmission for other illnesses, but these tend to be limited (e.g. spread within households), and it's always been a bit of a stretch to make the claim that completely healthy people are spreading diseases widely in "super-spreader" events via casual encounters. Does it happen? Sure. Is it common? Ehhhh. Even with Covid, we know that the majority of transmission (something like 80%) occurs within households. Of the remainder, as TFA notes, there's an "overdispersion", where a few people are responsible for most of the spread. Is it really likely that these "superspreader" people are mostly completely healthy, without symptoms, and yet unknowingly spreading it to vast numbers of people? Or is that just something that we've found a few times, and makes the most memorable anecdotes? It is certainly not the hypothesis you would favor based on parsimony alone. If you were a betting person, you'd probably put your money on the idea that someone is a little bit sick (but not so sick as to stay home in bed), and the disease can spread by aerosol or droplet with low probability. That's a much simpler explanation for the same pattern: someone has a tickle in their throat or a slight fever, but goes to the restaurant/office/wherever anyway. Set the probability of transmission to a low p-value, and let the poisson distribution do the rest. Just by chance alone, you will see rare occasions where large(r) groups of people get infected.
    - watwut 6y ago
      I had typo. But AFAIK, asymptomatic transmission is not novel concept. We have been learning about it in elementary school in the context of other diseases. There is absolutely nothing new about it as concept. It is not something that appeared with covid first time in history of diseases.
erostrate 6y ago
The WHO initially said there was no evidence supporting the need for masks in the general public. They only changed their stance in early June. In Europe many politicians were making the same claim, which was convenient because they didn't have enough masks.
- 6gvONxR4sf7o 6y ago
  At the time, I thought the general guidance was “don’t hoard masks, we need them for healthcare workers” rather than “don’t wear masks they don’t work” (which through the game of telephone turned into everything imaginable).
  - EmbeddedLight 6y ago
    The outrage comes from government and other health officials making claims early on that masks were not as effective, and that maintaining social distance and isolation was better (which I agree). But this was merely used as distraction to allow healthcare facilities to snatch up the existing supplies of high quality n95 masks before the public could (see toilet paper apocalypse 2020). Then the government changed their statements and said that masks were effective, and everyone should use them. It's the switching and lying to the public that leads to a lack of trustworthiness. You can argue that they didn't know the efficacy of mask usage, but that isn't the point here. It's that they lied to the American public for an ulterior motive, which is wrong.
- viklove 6y ago
  The WHO is a political organization, not a scientific one.
mike_hearn 6y ago
I've read a lot of public health papers in the past year, probably more than 50. Here are some of the problems that cropped up in papers that were used by governments to support policy decisions. Many of those policy decisions later turned out to be incorrect, like lockdowns and mask mandates, both of which easily count as drastic and neither were textbook. In fact pre-COVID pandemic control plans by the WHO explicitly recommended against lockdowns. By the way, be careful to separate the question of mask mandates from masks themselves. Mask mandates don't work: just look at case curves when mandates were introduced or removed and observe the lack of inflection points. If they worked people would have hundreds of examples by now of case curves which obviously inflected right after a mask mandate was changed, but no such graphs are ever cited because those inflections don't reliably happen. Texas provides a recent example (mandate removed, curve continues prior trend) but this problem was obvious from within a week of the first mandates being introduced. Look at [1] for some case graphs with mandate change dates drawn on them to see the problem. Anyway, errors seen in public health papers: 1. Circular reasoning. 2. Invalid citations. 3. Programming errors in models. 4. Use of extremely out of date numbers. 5. Absurd or obviously invalid assumptions and results in models being ignored. That's not a comprehensive list. Unfortunately these aren't rare problems. Virtually every public health paper I've read has had at least one of these issues, often multiple. Circular logic in particular is mind-numbingly common, to an extent I've never seen before. For example, a common "validation" technique for models is to compare them to other models and declare their outputs to be similar (e.g. [2] or [3]). It's almost unheard of to compare model outputs to actual observed data, probably because doing validation right would invalidate virtually all public health models (this problem was admitted in a 2012 paper [4]). For a specific example of these problems see the paper by Flaxman et al from Imperial College London [5]. This paper argued that lockdowns work using a statistical model, but they actually don't work, so to get this result required a combination of: 1. Circular logic: the model took as a starting assumption that case curves could only be changed by government intervention. In other words the paper encoded its own conclusions in its assumptions. The assumption epidemics can only be affected by lockdowns has no rational basis given the long history of epidemics starting and ending naturally. 2. The paper included Sweden in its data set, which attracted attention because Sweden appears to prove that the models generating the counterfactual were wrong. It managed to conclude lockdowns worked despite this because it concluded Sweden was a freak coincidence with an only 1 in 2000 chance of existing at all; in the graph that showed the different per-country fudge factors the model was allowed to calculate, Sweden was simply hidden to obscure what had happened. The truth was discovered later by people who studied the tables of prior probabilities uploaded to GitHub. 3. The paper admitted half way through that its scenario was "illustrative only" and that "in reality" the results would be different. There were other problems too, but none of them stopped the authors telling the press that lockdowns had "saved millions of lives" (i.e. the drastic policy pushed for by that very same research team). Nor did it stop international press agencies citing this paper in "fact checks". After reading so many papers with really basic and blatant problems, it's hard not to conclude that open access is going to seriously damage academia's credibility. Being able to just download and read the output of academic scientists is a very new thing, and one of the few highlights of the time I've spent reading COVID research is that open access is real now: I've hardly ever hit paywalls. Only for old papers. Unfortunately open access is a double edged sword. Now we can all read what we're paying for and observe the dangerously low quality. The outcome will probably be a large expansion of the battle between "science believers" and "science skeptics". Up until now that has been mostly restricted to debates on climatology, but now I think it will widen considerably. There's just no way to read the literature and retain your confidence in academic science when so much of it is entirely un-scientific. [1] https://rationalground.com/mask-charts/ https://rationalground.com/mask-charts/ [2] https://github.com/ptti/ptti/blob/master/README.md https://github.com/ptti/ptti/blob/master/README.md (see the paragraph starting with "Formalism-agnostic"). [3] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001435/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001435/ ("There is agreement in the literature that comparing the results of different models provides important evidence of validity and increases model credibility") [4] ibid; ("few models in healthcare could ever be validated for predictive use. This, however, does not disqualify such models from being used as aids to decision making") [5] https://nicholaslewis.org/did-lockdowns-really-save-3-million-covid-19-deaths-as-flaxman-et-al-claim/ https://nicholaslewis.org/did-lockdowns-really-save-3-millio...
vondur 6y ago
I’m pretty skeptical at this point that masks made any difference. Here in Southern California where everyone wears masks indoors, and even the majority of people wear them outdoors. Yet we still ended up with some of the highest infection rates in the country. I’d wager if we gave the people who are most susceptible to the disease N95 masks, we’d have seen a much lower hospitalization and death rates.
- higeorge13 6y ago
  It might have made a difference, but we do not have a stable reference case to observe the difference. It might have reduced 1, 2, 10, 20% the number of infections, who knows? In the end it's just a piece of paper/cloth in our faces; i personally don't get this anti-mask sentiment as if we are placing something really bad in our mouths.
  - xxxxhhhh 6y ago
    > In the end it's just a piece of paper/cloth in our faces Humans are social creatures as the result of millions of years of evolution. There’s profound effects when facial social cues are erased and people are widely deprived of socialization.
- hello_moto 6y ago
  I observed many people around me use ineffective mask or don't wear it properly. Basic health hygiene requires discipline that may take years to develop if not mandated and enforced/practiced. Too many variables to be a mask skeptic given Cali situation...
graeme 6y ago
Some mistaken policy choices: * Not requiring masks at workplaces or schools once seated (common in many areas) * Not aiming for ventilation and denying aerosol spread * Denying asymptomatic and presymptomatic spread. Giving health/testing advice mainly based on symptoms * Not using and blocking rapid tests * Not scaling testing capacity with cases Japan had a more coherent approach on some of these with their three C’s approach: avoid closed spaces, crowded rooms, and close contact. The West generally just emphasized the latter. (The west did have capacity limits, but only to space people out within rooms, not for aerosols)

redis_mlc 6y ago

> I've spent a lot of time reading the science over the last year and a half or so. Pro tip: there wasn't any science to read. Pro tip 2: when a pandemic's origin contains a lab that studies and publishes that virus, it's from the lab.

throwawaysea 6y ago

I think the word “science” itself has lost meaning. Many people I know have yard signs that say “science is real” but in practice these same people can be easily manipulated by bad studies that are cycled through news media and social media. They also often listen to science only when it agrees with their views. I think like what came before, popular science is turning into an act of blind faith. We certainly see this with blind belief in “scientific authorities” who can get things very wrong (like the WHO). We also see it with fact checkers - as an example, I remember reading a (factually correct) article on Facebook yesterday about COVID lockdowns, which mentioned the infection fatality rate. This post had a fact check content warning, from a fact checker who incorrectly quoted the case fatality rate for COVID-19 as evidence that the article was misinformation. I’m not sure what the fix is. It feels like there is too much information out there for the public to handle and process properly. Or maybe we need a new word that is not “science”, that captures more of the critical thought that is needed, and moves us away from blind faith.

gher-shyu3i 6y ago
Scientism is basically a religion nowadays. This has lead to the rise of certain figures, such as Neil deGrasse Tyson, who start talking way beyond their fields - and rarely questioned, and then start judging others and imposing their own morality.