6 ms·

"Some people with swine flu travelled on a plane from New York to China, and many fellow passengers got infected. Some researchers looked at whether passengers

by mattm 5y ago

"Some people with swine flu travelled on a plane from New York to China, and many fellow passengers got infected. Some researchers looked at whether passengers who wore masks throughout the flight stayed healthier. The answer was very much yes. They were able to track down 9 people who got sick on the flight and 32 who didn’t. 0% of the sick passengers wore masks, compared to 47% of the healthy passengers. Another way to look at that is that 0% of mask-wearers got sick, but 35% of non-wearers did." https://slatestarcodex.com/2020/03/23/face-masks-much-more-than-you-wanted-to-know/ https://slatestarcodex.com/2020/03/23/face-masks-much-more-t... At the beginning of the pandemic I was skeptical about the effectiveness of masks and this article is what convinced me that there is some benefit.

solarengineer 5y ago
What is astounding to a lot of us in South East Asia is the reluctance of the West in learning from our lessons. How many deaths and personal trauma experiences do people in general need to go through in order to learn from others?
- ddingus 5y ago
  There is a strong culture of individuality, and that is coupled with an extreme reluctance to just do what we're told, and what I mean by that is more about trust than Authority. Trust is low here, which is problematic for a scenario like this. Many of us did learn those lessons. For me personally when this all began, checking out what the world is doing seemed the natural thing to do. The US is also very insular, in that a smaller percentage of people travel abroad than is typical for many Western Nations. And a small percentage of people seek news produced outside the nation too. Both of those stats are better elsewhere in the West, so make of that what you will.
  - kelnos 5y ago
    I think it goes further than individuality, though. There's a pervasive selfishness that seems to run through our (American) culture. Many who do believe that COVID is a threat to others (say, to older people, or to immuno-compromised people) but do not believe that they themselves are in much danger will decide not to wear a mask because they don't think it matters to them if they do or not. This is the thing that makes me saddest. It just seems like people in the US are unwilling to endure even a minor inconvenience if it will help someone else but not do anything for themselves.
    - collyw 5y ago
      It seems pretty selfish to force small businesses to close and not allow people to earn a living, for a disease that has a pretty high survival rate and is only really a problem for old or very unhealthy people. And it goes against all pandemic guidelines from before 2020, which was to shield the vulnerable and let everyone get on with life more or less.
    - ddingus 5y ago
      I agree strongly! The idea of some effort, cost, minor sacrifice or inconvenience for a common, public good is not strong here. Couple that being basically as insular on a personal level as we generally are nationally, and we find more of us than we may expect are empathy challenged too.
- crocodiletears 5y ago
  In the US, it's more to do with the way the CDC's messaging throughout the pandemic than any rejection of the evidence concerning a mask's efficacy. People refusing to wear masks rarely question whether or not it works, and more to do with a low estimation of the disease's threat, as well as contempt for both the technocrats who chose to mislead the public about masks early on, and leaders who they believe are overstepping their authority by mandating them. Our leadership has been doing everything possible to burn through its perceived legitimacy, and this is the result. Childish, spiteful, somewhat understandable behavior.
  - AshWolfy 5y ago
    As someone who worked the public for the entire pandemic, id say it was about 50-50 between people who thought covid wasnt a threat and people who thought masks werent effective
    - apgwoz 5y ago
      who _has_ or who _did_? I take one of these as “the pandemic is over” which seems far from the case, generally...
  - j4yav 5y ago
    Wasn’t it more a result of tribalism? Even before the masks were really a topic it became quite important politically for the pandemic to be real or not, depending on which group you hoped benefitted politically or not. From the outside it looked like everything more or less flowed from that starting point, and then everyone picked their positions and favorite realities from there.
    - piva00 5y ago
      No. And I say that due to my experience here in Sweden, with the same message spread around about masks. I understand why the government did it in the beginning of the pandemic, to save PPE from shortages, to avoid people using masks and getting a false sense of security, etc. Still, it created a lot of distrust when the message changed a few months ago, it wasn't a tribalist issue and I can completely understand how people ended up with this distrust. They are still wrong and I completely agree with this comment [1]. [1] https://news.ycombinator.com/item?id=27231688 https://news.ycombinator.com/item?id=27231688
- Gibbon1 5y ago
  Friends were talking about that a year ago. Health authorities in the west were completely ignoring their counterparts in Asia early on. Dismissed the threat until the pandemic blew up in Northern Italy and New York. A lot of people in HN were arguing that the 0.7% fatality rate reported by Chinese authorities in Feb/20 was because Chinese medical care is bad. Casual racism is kinda pernicious.
  - astrange 5y ago
    If you watched reddit all the comments to all news from China (including doctors dying, doctors not dying, hospitals being built or filling up, doctors clapping on TikTok because they'd released their last patients) was complaining about it and calling it fake news from the CCP. They were happy about the same thing from the US though.
    - collyw 5y ago
      Do you remember the posts about people dropping dead in the streets, people skin turning black, or massive cement mixers "disinfecting" streets? There was plenty of fake news going around.
      - astrange 5y ago
        The people spraying disinfectant everywhere was a bit silly but also not any different from what we were doing. At the time people out here were keeping their mail outside for 3 days and sanitizing their groceries.
- johbjo 5y ago
  > What is astounding to a lot of us in South East Asia is the reluctance of the West in learning from our lessons. Agreed. We should have relocated Britain and NYC to the equator long time ago.
deleted 5y ago
[deleted]
irq11 5y ago
That is not “very much yes”, that is “an anecdote suggests yes”. The statistical illiteracy here is astounding from professional scientists. ”0% of ths sick passengers wore masks, compared to 47% of the healthy passengers. Another way to look at that is that 0% of the mask wearers got sick, but 35% of non-wearers did” And another way to look at it is that 65% of non-wearers didn’t get sick. The group of sick people is also quite small, meaning that the error bars on the effect size are large. Sloppy, sloppy thinking.
- mike_hearn 5y ago
  Error bars would be nice. They're MIA in large swathes of COVID related research. I've read a lot of COVID papers in the past year and this paper is typical of the field. Things you should expect to see when reading epidemiology literature: 1. Statistical uncertainty is normally ignored. They can and will tell politicians to adopt major policy changes on the back of a single dataset with 20 people in it. In the rare cases when they bother to include error bars at all they are usually so wide as to be useless. In many other fields researchers debate P-hacking and what threshold of certainty should count as a significant finding. Many people observe that the standard of P=0.05 in e.g. psychology is too high because it means 1 in 20 studies will result significant-but-untrue findings by chance alone. Compared to those debates epidemiology is in the stone age: any claim that can be read into any data is considered significant. 2. Rampant confusion between models and reality. The top rated comment on this thread observes that the paper doesn't seem to test its model predictions against reality yet makes factual claims about the world. No surprises there; public health papers do that all the time. No-one except out-of-field skeptics actually judge epidemiological models by their predictive power. Epidemiologists admit this problem exists, but public health has become so corrupt that they argue being able to correctly predict things is not a fair way to judge a public health model[1]. Obviously they insist governments should still implement whatever policies the models say are required. It's hard to get more unscientific than culturally rejecting the idea that science is about predicting the natural world, but multiple published papers in this field have argued exactly that. A common trick is "validating" a model against other models [2]. 3. Inability to do maths. Setting up a model with reasonable assumptions is one thing but do they actually solve the equations correctly? The Ferguson model from Imperial College, which we're widely assured is one of the world's top teams of epidemiologists, was written in C and filled with race conditions/out of bounds reads that caused their model to totally change its predictions due to timing differences in thread scheduling, different CPUs/compilers etc. These differences were large, e.g. a difference of 80,000 deaths predicted by May for the UK [3]. Nobody in the academic hierarchy saw any problem with this and worse, some researchers argued that such errors didn't matter because they just ran it a bunch of times and averaged the results. This is confusing the act of predicting the behaviour of the world with the act of measuring it, see point (2). 4. Major logic errors. Assuming correlation implies causation is totally normal. Other fields use sophisticated approaches to try and control for confounding variables, epidemiology doesn't. Circular logic is a lot more common than normal, for some reason. None of these problems stop papers being published by supposedly reputable institutions in supposedly reputable journals. After reading or scan-reading about 50 epidemiology papers, including some older papers from 10 years ago, I concluded that not a single thing from this field can be trusted. The problems aren't specific to COVID, they're cultural and have been around a long time. Life is too short to examine literally every paper making every claim but if you take a sample and nearly all of them contain basic errors or what is clearly actual fraud, then it seems fair to conclude the field has no real standards. [1] "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 ... Philips et al state that since a decision-analytic model is an aid to decision making at a particular point in time, there is no empirical test of predictive validity. From a similar premise, Sculpher et al argue that prediction is not an appropriate test of validity for such model" https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001435/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001435/ [2] https://github.com/ptti/ptti/blob/master/README.md https://github.com/ptti/ptti/blob/master/README.md [3] https://github.com/mrc-ide/covid-sim/issues/116 https://github.com/mrc-ide/covid-sim/issues/116 https://github.com/mrc-ide/covid-sim/issues/30 https://github.com/mrc-ide/covid-sim/issues/30 https://github.com/mrc-ide/covid-sim/commit/581ca0d8a12cddbd106a580beb9f5e56dbf3e94f https://github.com/mrc-ide/covid-sim/commit/581ca0d8a12cddbd... https://github.com/mrc-ide/covid-sim/commit/3d4e9a4ee633764ce927aecfbbcaa7091f3c1b98 https://github.com/mrc-ide/covid-sim/commit/3d4e9a4ee633764c...
avereveard 5y ago
Doesn't seem it corrects by seat position

by mattm 5y ago

solarengineer 5y ago

What is astounding to a lot of us in South East Asia is the reluctance of the West in learning from our lessons. How many deaths and personal trauma experiences do people in general need to go through in order to learn from others?

ddingus 5y ago
There is a strong culture of individuality, and that is coupled with an extreme reluctance to just do what we're told, and what I mean by that is more about trust than Authority. Trust is low here, which is problematic for a scenario like this. Many of us did learn those lessons. For me personally when this all began, checking out what the world is doing seemed the natural thing to do. The US is also very insular, in that a smaller percentage of people travel abroad than is typical for many Western Nations. And a small percentage of people seek news produced outside the nation too. Both of those stats are better elsewhere in the West, so make of that what you will.
- kelnos 5y ago
  I think it goes further than individuality, though. There's a pervasive selfishness that seems to run through our (American) culture. Many who do believe that COVID is a threat to others (say, to older people, or to immuno-compromised people) but do not believe that they themselves are in much danger will decide not to wear a mask because they don't think it matters to them if they do or not. This is the thing that makes me saddest. It just seems like people in the US are unwilling to endure even a minor inconvenience if it will help someone else but not do anything for themselves.
  - collyw 5y ago
    It seems pretty selfish to force small businesses to close and not allow people to earn a living, for a disease that has a pretty high survival rate and is only really a problem for old or very unhealthy people. And it goes against all pandemic guidelines from before 2020, which was to shield the vulnerable and let everyone get on with life more or less.
  - ddingus 5y ago
    I agree strongly! The idea of some effort, cost, minor sacrifice or inconvenience for a common, public good is not strong here. Couple that being basically as insular on a personal level as we generally are nationally, and we find more of us than we may expect are empathy challenged too.
crocodiletears 5y ago
In the US, it's more to do with the way the CDC's messaging throughout the pandemic than any rejection of the evidence concerning a mask's efficacy. People refusing to wear masks rarely question whether or not it works, and more to do with a low estimation of the disease's threat, as well as contempt for both the technocrats who chose to mislead the public about masks early on, and leaders who they believe are overstepping their authority by mandating them. Our leadership has been doing everything possible to burn through its perceived legitimacy, and this is the result. Childish, spiteful, somewhat understandable behavior.
- AshWolfy 5y ago
  As someone who worked the public for the entire pandemic, id say it was about 50-50 between people who thought covid wasnt a threat and people who thought masks werent effective
  - apgwoz 5y ago
    who _has_ or who _did_? I take one of these as “the pandemic is over” which seems far from the case, generally...
- j4yav 5y ago
  Wasn’t it more a result of tribalism? Even before the masks were really a topic it became quite important politically for the pandemic to be real or not, depending on which group you hoped benefitted politically or not. From the outside it looked like everything more or less flowed from that starting point, and then everyone picked their positions and favorite realities from there.
  - piva00 5y ago
    No. And I say that due to my experience here in Sweden, with the same message spread around about masks. I understand why the government did it in the beginning of the pandemic, to save PPE from shortages, to avoid people using masks and getting a false sense of security, etc. Still, it created a lot of distrust when the message changed a few months ago, it wasn't a tribalist issue and I can completely understand how people ended up with this distrust. They are still wrong and I completely agree with this comment [1]. [1] https://news.ycombinator.com/item?id=27231688 https://news.ycombinator.com/item?id=27231688
Gibbon1 5y ago
Friends were talking about that a year ago. Health authorities in the west were completely ignoring their counterparts in Asia early on. Dismissed the threat until the pandemic blew up in Northern Italy and New York. A lot of people in HN were arguing that the 0.7% fatality rate reported by Chinese authorities in Feb/20 was because Chinese medical care is bad. Casual racism is kinda pernicious.
- astrange 5y ago
  If you watched reddit all the comments to all news from China (including doctors dying, doctors not dying, hospitals being built or filling up, doctors clapping on TikTok because they'd released their last patients) was complaining about it and calling it fake news from the CCP. They were happy about the same thing from the US though.
  - collyw 5y ago
    Do you remember the posts about people dropping dead in the streets, people skin turning black, or massive cement mixers "disinfecting" streets? There was plenty of fake news going around.
    - astrange 5y ago
      The people spraying disinfectant everywhere was a bit silly but also not any different from what we were doing. At the time people out here were keeping their mail outside for 3 days and sanitizing their groceries.
johbjo 5y ago
> What is astounding to a lot of us in South East Asia is the reluctance of the West in learning from our lessons. Agreed. We should have relocated Britain and NYC to the equator long time ago.

deleted 5y ago

[deleted]

irq11 5y ago

That is not “very much yes”, that is “an anecdote suggests yes”. The statistical illiteracy here is astounding from professional scientists. ”0% of ths sick passengers wore masks, compared to 47% of the healthy passengers. Another way to look at that is that 0% of the mask wearers got sick, but 35% of non-wearers did” And another way to look at it is that 65% of non-wearers didn’t get sick. The group of sick people is also quite small, meaning that the error bars on the effect size are large. Sloppy, sloppy thinking.

mike_hearn 5y ago
Error bars would be nice. They're MIA in large swathes of COVID related research. I've read a lot of COVID papers in the past year and this paper is typical of the field. Things you should expect to see when reading epidemiology literature: 1. Statistical uncertainty is normally ignored. They can and will tell politicians to adopt major policy changes on the back of a single dataset with 20 people in it. In the rare cases when they bother to include error bars at all they are usually so wide as to be useless. In many other fields researchers debate P-hacking and what threshold of certainty should count as a significant finding. Many people observe that the standard of P=0.05 in e.g. psychology is too high because it means 1 in 20 studies will result significant-but-untrue findings by chance alone. Compared to those debates epidemiology is in the stone age: any claim that can be read into any data is considered significant. 2. Rampant confusion between models and reality. The top rated comment on this thread observes that the paper doesn't seem to test its model predictions against reality yet makes factual claims about the world. No surprises there; public health papers do that all the time. No-one except out-of-field skeptics actually judge epidemiological models by their predictive power. Epidemiologists admit this problem exists, but public health has become so corrupt that they argue being able to correctly predict things is not a fair way to judge a public health model[1]. Obviously they insist governments should still implement whatever policies the models say are required. It's hard to get more unscientific than culturally rejecting the idea that science is about predicting the natural world, but multiple published papers in this field have argued exactly that. A common trick is "validating" a model against other models [2]. 3. Inability to do maths. Setting up a model with reasonable assumptions is one thing but do they actually solve the equations correctly? The Ferguson model from Imperial College, which we're widely assured is one of the world's top teams of epidemiologists, was written in C and filled with race conditions/out of bounds reads that caused their model to totally change its predictions due to timing differences in thread scheduling, different CPUs/compilers etc. These differences were large, e.g. a difference of 80,000 deaths predicted by May for the UK [3]. Nobody in the academic hierarchy saw any problem with this and worse, some researchers argued that such errors didn't matter because they just ran it a bunch of times and averaged the results. This is confusing the act of predicting the behaviour of the world with the act of measuring it, see point (2). 4. Major logic errors. Assuming correlation implies causation is totally normal. Other fields use sophisticated approaches to try and control for confounding variables, epidemiology doesn't. Circular logic is a lot more common than normal, for some reason. None of these problems stop papers being published by supposedly reputable institutions in supposedly reputable journals. After reading or scan-reading about 50 epidemiology papers, including some older papers from 10 years ago, I concluded that not a single thing from this field can be trusted. The problems aren't specific to COVID, they're cultural and have been around a long time. Life is too short to examine literally every paper making every claim but if you take a sample and nearly all of them contain basic errors or what is clearly actual fraud, then it seems fair to conclude the field has no real standards. [1] "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 ... Philips et al state that since a decision-analytic model is an aid to decision making at a particular point in time, there is no empirical test of predictive validity. From a similar premise, Sculpher et al argue that prediction is not an appropriate test of validity for such model" https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001435/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001435/ [2] https://github.com/ptti/ptti/blob/master/README.md https://github.com/ptti/ptti/blob/master/README.md [3] https://github.com/mrc-ide/covid-sim/issues/116 https://github.com/mrc-ide/covid-sim/issues/116 https://github.com/mrc-ide/covid-sim/issues/30 https://github.com/mrc-ide/covid-sim/issues/30 https://github.com/mrc-ide/covid-sim/commit/581ca0d8a12cddbd106a580beb9f5e56dbf3e94f https://github.com/mrc-ide/covid-sim/commit/581ca0d8a12cddbd... https://github.com/mrc-ide/covid-sim/commit/3d4e9a4ee633764ce927aecfbbcaa7091f3c1b98 https://github.com/mrc-ide/covid-sim/commit/3d4e9a4ee633764c...

avereveard 5y ago

Doesn't seem it corrects by seat position