6 ms·

Some people believe the reason the R value was high in the first place was due to a higher false positive rate (aka miscalculation) https://lbry.tv/Mike-Yeadon

Some people believe the reason the R value was high in the first place was due to a higher false positive rate (aka miscalculation) https://lbry.tv/Mike-Yeadon-Unlocked:0 https://lbry.tv/Mike-Yeadon-Unlocked:0 For reference, this is the former head of research for Pfizer. The video (and him) have been banned off all the social media platforms due to “misinformation” (really a disagreement about the efficacy of the PCR protocol and how it has lead to a larger false positive rate).

rtkwe 6y ago
Even with false positives the real case number is probably larger just because of the combination of asymptomatic cases and the lack of randomized community screening.
- makomk 6y ago
  In the UK, one of the main things used to estimate the value of R is randomly sampling people from the population and testing them for Covid-19 regardless of symptoms.
  - DerDangDerDang 6y ago
    It's worth bearing in mind that initially (and until only a few months ago iirc) tests were only available to certified essential workers - first NHS staff, then civil servants, etc. I actually paid £100 for a private test in May. I've had an NHS drive-thru one more recently. I'm not sure of the absolute veracity of your 'regardless of symptoms' claim. As I understand it, the R number is calculated based on all the NHS tests done (and private, with some lag iirc). This even explicitly says "You cannot get a free NHS test unless you have symptoms, have been asked to by your local council, live in England and have been told to by your hospital, or are taking part in a government pilot project." https://www.gov.uk/get-coronavirus-test https://www.gov.uk/get-coronavirus-test
    - thomc 6y ago
      I believe they also run a programme of random tests regardless of symptoms. A friend of mine was selected for this and they periodically come to his house and take a sample.
      - DerDangDerDang 6y ago
        Ah ok. Any idea how extensive the programme is and what weight it's given in relation to overall testing? Obviously if this is the only / main input to the R number then my previous comment is crap and I retract it. Otherwise, I think I gave reasonable examples of how the sampling has been skewed, in good faith.
    - tigershark 6y ago
      Absolutely false. I got a test in May as part of a statistical study in UK. I was randomly selected as you would expect in this kind of studies.
      - secondcoming 6y ago
        What part is absolutely false? The NHS randomly picked you, you didn't ask the NHS
        jlokier 6y ago
        The false part is "tests were only available to certified essential workers". That's true for people seeking tests, and workplaces etc. But the statistical sampling was conducted separately by the Office of National Statistics (not the NHS) across the whole country in order to understand the pandemic, and it did have access to tests for this purpose.
        DerDangDerDang 6y ago
        While you’re right in absolute terms, I think you’re obscuring a valid point. The ONS having tests doesn’t change the fact that for the vast majority of the population, being an essential worker was the only way to get a test. The ONS tests are not the only input to the announced R number are they? Maybe I’m misunderstanding horribly, but it seems like you’re saying there’s absolutely no correlation whatsoever between availability of tests to the general public and the accuracy of the announced R number for the general public. If I’m misunderstanding I do genuinely want to understand!
  - ekianjo 6y ago
    Are all tests reliable? (rhetorical question)
- 3dprintscanner 6y ago
  Is having the virus without symptoms really a case? The Coronavirus act says so. However, there's only tenuous evidence of asymptomatic and presymptiomatic transmission of the virus.
  - rtkwe 6y ago
    Kids tested with no symptoms had the same viral load in their nasal cavities as symptomatic cases so there's little reason to believe they were less effective spreaders than a person showing symptoms. https://www.uchealth.org/today/the-truth-about-asymptomatic-spread-of-covid-19/ https://www.uchealth.org/today/the-truth-about-asymptomatic-...
- chrisseaton 6y ago
  > the lack of randomized community screening Lack of it? But isn’t that exactly how R is estimated?
  - rtkwe 6y ago
    It sounds like there's some limited sampling of asymptomatic people but it's not huge? Hard to tell this page doesn't really give details on how large the longitudinal and survey is conducted. https://www.gov.uk/guidance/the-r-number-in-the-uk#about-r-number-and-growth-rate https://www.gov.uk/guidance/the-r-number-in-the-uk#about-r-n...
    - DerDangDerDang 6y ago
      or how the longitudinal studies numbers are weighted against the overall numbers when coming up with the announced figure..
emmelaich 6y ago
Estimation is surprisingly hard! Johns Hopkins Newsletter deletes article re excess Covid-19 deaths -- https://twitter.com/JHUNewsLetter/status/1332100155986882562 https://twitter.com/JHUNewsLetter/status/1332100155986882562
- tialaramex 6y ago
  The crazy thing for that article is, it basically says there aren't any excess deaths, which is one of those conclusions where you ought to stop and think "Wait, surely that's a high level statistic I could cross-check?" and sure enough yes there are excess deaths statistics calculated, that's a normal thing countries do - and of course the US stats shot up due to COVID-19. It's written by an economist, which maybe explains why they didn't check. You won't get far in economics if you insist on checking whether your work matches reality. Ask Arthur Laffer.
  - hkt 6y ago
    That's a terrible thing to say about economists - don't you know those people successfully predicted eight out of the last three recessions? (wrap in a joke tag)
  - Izkata 6y ago
    The graph on the second page is really low quality (I can't read the X-axis, the highlighted section is a different size, and the highlighted section has 2 additional series that don't show up in the key), so it's really hard to say for sure, but it's totally possible for both to be true: If most of the deaths so far were a "culling effect" of people likely to die later in the year, then the net by the end of the year could be "no difference". Given the average age of deaths by COVID-19 being above average life expectancy, this totally seems possible to me - lots of excess deaths early in the year, but the opposite later in the year, resulting in net "deaths as usual" over the whole year.
    - disgruntledphd2 6y ago
      > Given the average age of deaths by COVID-19 being above average life expectancy, this totally seems possible to me - lots of excess deaths early in the year, but the opposite later in the year, resulting in net "deaths as usual" over the whole year. Life expectancy at birth, and life expectancy given a particular age are very different. Most of those Covid deaths were above life expectancy are using life expectancy at birth figures, which is very misleading (as if you make it 82 you're almost certainly a fitter than average 82 year old).
spion 6y ago
The reason why they are banned is because what he is saying sounds plausible but is very, very likely wrong. First of all, the number of tests isn't growing at the same rate as the number of cases, hospitalizations and deaths: https://imgur.com/2cVrGz7 https://imgur.com/2cVrGz7 You can notice the very low positive rate in mid August (150 000 tests and only 500 cases - even if all false positives, thats 0.3% FP rate) But okay, lets assume that they did something to ramp up the false positive rate, If we look at the daily rate of growth (% increase) for cases, hospitalizations and deaths: https://imgur.com/bEix1Fo https://imgur.com/bEix1Fo We can see that there is a perfect exponential 7% rate of growth starting in September and slowly decaying after. But more than that, the rate of growth in hospitalizations and deaths also follows the same pattern almost perfectly but with a 5 day and 16 day delay, respectively! If you were accidentally getting false positives, you would either not expect hospitalizations and deaths to grow at the same rate as false positives do. Even if they did, you would expect them to grow at exactly the same time without any delays. If there is no causal relationship they should all grow at the same rate, at the same time as any other random subgroup of people To get the delay to happen, you would have to somehow perfectly fine tune the false positives for hospitalizations and deaths as well. In which case you're better off just making numbers up. But more importantly, there is a much simpler explanation, which we get if we super-impose google mobility trends % increase in amount spent staying at home, and we shift cases by 6 days (avg time to symptoms), hospitalizations by 11 and deaths by 22 days: https://imgur.com/UKklUIP https://imgur.com/UKklUIP We can see that the rate of growth is almost perfectly inversely correlated with the % increase in staying at home (with perhaps some light seasonal / immunity / other measures effects included). Additionally we have non-PCR data like the Zoe symptom tracker app largely corraborating more or less the same rate of growth as detected by PCR tests: https://covid.joinzoe.com/data#levels-over-time https://covid.joinzoe.com/data#levels-over-time
- spion 6y ago
  But more generally, there is a fundamental problem with social media: it unfortunately acts a generator of large amounts of "perfect bullshit". First, it gets thousands of people to generate various conspiracy theories and plausable looking ideas. Many of these will be interesting and have some real merit, but most of them wont. (By itself, this doesn't do much - we're people, we generate ideas and theories, many of them wrong - nothing special about this process). Then, give people the retweet button, and have them act as a filter for the most convincing looking bullshit. This is where things go terribly wrong. Retweets are a powerful amplifier. What gets retweeted? Is it the most throughly researched content? Highly unlikely, most people aren't experts in the subject (heck, I don't even dare go into the mechanics of the theory, only the math and stats) but they will still retweet if they find it interesting, plausible and aligned with what they strongly believe or wish was true. Side note: having some authority (Nobel prize, etc) also helps a lot with this process. Still, remember that social networks won't differentiate whether 1 scientist is actually having this idea or many, and worse, it won't necessarily inform you if many scientists are actually demonstrating how the idea is wrong (unless they make it equally interesting for a retweet) Finally, trick people by giving them dopamine system rewards (notifications for retweets and likes). They inevitably end up surrounded by a group of supporters that praise and retweet what they say. This whole process makes it so much harder for people (even scientists) to go back on what they said if it turns out they were wrong. So what do you end up with? You end up with a system that delivers the most perfect bullshit to the largest number of people. The scientists that tweet the same old boring conservative stuff (words like "likely" often appear) are largely voiceless. I don't think any single person is necessarily at fault in this system. But I do think that the system is a total disaster, and we have to invent something better than this. These simplistic social network designs are failing humanity.
Marazan 6y ago
He's totally, utterly wrong. Wrong on a spectacular level. We empircally know he is wrong because when schools went back there was a MASSSSSSIVE spike it requested tests (as school children got their start of season colds and worried parents got them tested in the first 2 weeks of school returning). But there was not a MASSSSSIVE spike in Covid cases. If Covid numbers were being driven by false positives then there HAD to be a massive spike in cases as testing numbers spiked. There was not. So false positives cannot be the reason.
DanBC 6y ago
Plenty of immunologists (esp those still working) disagree with a lotof what Yeadon says. Here's a pretty good explainer: https://twitter.com/andrew_croxford/status/1330882994471653376 https://twitter.com/andrew_croxford/status/13308829944716533... And another: https://twitter.com/andrew_croxford/status/1331722078777729024 https://twitter.com/andrew_croxford/status/13317220787777290...
robtaylor 6y ago
Yeadon has published, and has kept published, a known lie https://twitter.com/MichaelYeadon3/status/1318450567631544320 https://twitter.com/MichaelYeadon3/status/131845056763154432... Why would someone who deals in facts do such a thing? Surely the correct position would be to correct and remove. Personally anyone who refers to his material is tarnished. On a general point, there are many people now growing in fame (and monetising that) due to the pandemic. Are their interests aligned with a pandemic ending, what do they pivot to?
- bjourne 6y ago
  That is a very long twitter thread. What in it is a known lie?
  - robtaylor 6y ago
    The first two posts, perhaps more? Considering the OP is calling into question why this person was booted from some social media, posting lies about public hospitals and their staff during a pandemic seems a fair reason. Shame the posts on Twitter remain and a shame Twitter themselves have not taken action.
    - bjourne 6y ago
      Two first posts: "A source just gave me the following information. A hospital in Wales, Nevill Hall in Abergavenny, has 250 beds. 200 beds are empty. The surgeons are bored & pass much time on the nearby golf course. I think this might be one answer to why UK doctors are not investigating to find out why hospitals have no patients in them! Apparently all covid cases are currently being sent to this hospital. This story tallies with the original evidence which drew me into this ghastly mess we’ve made of our country. I’ve not mentioned this..." What in it is a known lie?
      - robtaylor 6y ago
        You appear a clever chap, so you can verify that the statements are false. You can also locate where the author also states they are false, but does not delete them. It might be a sixth form debating point, but you have also have previously posted "The problem is that it has become acceptable to treat ideas as dangerous. For example, if I want to deny the Holocaust, that is my right." That is where I bow out, with a link to show how such 'ideas' and 'rights' have real world impact during this pandemic https://twitter.com/dashaburns/status/1332798207911399424?s=12 https://twitter.com/dashaburns/status/1332798207911399424?s=... Have a great day / life etc.

rtkwe 6y ago

Even with false positives the real case number is probably larger just because of the combination of asymptomatic cases and the lack of randomized community screening.

makomk 6y ago
In the UK, one of the main things used to estimate the value of R is randomly sampling people from the population and testing them for Covid-19 regardless of symptoms.
- DerDangDerDang 6y ago
  It's worth bearing in mind that initially (and until only a few months ago iirc) tests were only available to certified essential workers - first NHS staff, then civil servants, etc. I actually paid £100 for a private test in May. I've had an NHS drive-thru one more recently. I'm not sure of the absolute veracity of your 'regardless of symptoms' claim. As I understand it, the R number is calculated based on all the NHS tests done (and private, with some lag iirc). This even explicitly says "You cannot get a free NHS test unless you have symptoms, have been asked to by your local council, live in England and have been told to by your hospital, or are taking part in a government pilot project." https://www.gov.uk/get-coronavirus-test https://www.gov.uk/get-coronavirus-test
  - thomc 6y ago
    I believe they also run a programme of random tests regardless of symptoms. A friend of mine was selected for this and they periodically come to his house and take a sample.
    - DerDangDerDang 6y ago
      Ah ok. Any idea how extensive the programme is and what weight it's given in relation to overall testing? Obviously if this is the only / main input to the R number then my previous comment is crap and I retract it. Otherwise, I think I gave reasonable examples of how the sampling has been skewed, in good faith.
  - tigershark 6y ago
    Absolutely false. I got a test in May as part of a statistical study in UK. I was randomly selected as you would expect in this kind of studies.
    - secondcoming 6y ago
      What part is absolutely false? The NHS randomly picked you, you didn't ask the NHS
      - jlokier 6y ago
        The false part is "tests were only available to certified essential workers". That's true for people seeking tests, and workplaces etc. But the statistical sampling was conducted separately by the Office of National Statistics (not the NHS) across the whole country in order to understand the pandemic, and it did have access to tests for this purpose.
        DerDangDerDang 6y ago
        While you’re right in absolute terms, I think you’re obscuring a valid point. The ONS having tests doesn’t change the fact that for the vast majority of the population, being an essential worker was the only way to get a test. The ONS tests are not the only input to the announced R number are they? Maybe I’m misunderstanding horribly, but it seems like you’re saying there’s absolutely no correlation whatsoever between availability of tests to the general public and the accuracy of the announced R number for the general public. If I’m misunderstanding I do genuinely want to understand!
- ekianjo 6y ago
  Are all tests reliable? (rhetorical question)
3dprintscanner 6y ago
Is having the virus without symptoms really a case? The Coronavirus act says so. However, there's only tenuous evidence of asymptomatic and presymptiomatic transmission of the virus.
- rtkwe 6y ago
  Kids tested with no symptoms had the same viral load in their nasal cavities as symptomatic cases so there's little reason to believe they were less effective spreaders than a person showing symptoms. https://www.uchealth.org/today/the-truth-about-asymptomatic-spread-of-covid-19/ https://www.uchealth.org/today/the-truth-about-asymptomatic-...
chrisseaton 6y ago
> the lack of randomized community screening Lack of it? But isn’t that exactly how R is estimated?
- rtkwe 6y ago
  It sounds like there's some limited sampling of asymptomatic people but it's not huge? Hard to tell this page doesn't really give details on how large the longitudinal and survey is conducted. https://www.gov.uk/guidance/the-r-number-in-the-uk#about-r-number-and-growth-rate https://www.gov.uk/guidance/the-r-number-in-the-uk#about-r-n...
  - DerDangDerDang 6y ago
    or how the longitudinal studies numbers are weighted against the overall numbers when coming up with the announced figure..

emmelaich 6y ago

Estimation is surprisingly hard! Johns Hopkins Newsletter deletes article re excess Covid-19 deaths -- https://twitter.com/JHUNewsLetter/status/1332100155986882562 https://twitter.com/JHUNewsLetter/status/1332100155986882562

tialaramex 6y ago
The crazy thing for that article is, it basically says there aren't any excess deaths, which is one of those conclusions where you ought to stop and think "Wait, surely that's a high level statistic I could cross-check?" and sure enough yes there are excess deaths statistics calculated, that's a normal thing countries do - and of course the US stats shot up due to COVID-19. It's written by an economist, which maybe explains why they didn't check. You won't get far in economics if you insist on checking whether your work matches reality. Ask Arthur Laffer.
- hkt 6y ago
  That's a terrible thing to say about economists - don't you know those people successfully predicted eight out of the last three recessions? (wrap in a joke tag)
- Izkata 6y ago
  The graph on the second page is really low quality (I can't read the X-axis, the highlighted section is a different size, and the highlighted section has 2 additional series that don't show up in the key), so it's really hard to say for sure, but it's totally possible for both to be true: If most of the deaths so far were a "culling effect" of people likely to die later in the year, then the net by the end of the year could be "no difference". Given the average age of deaths by COVID-19 being above average life expectancy, this totally seems possible to me - lots of excess deaths early in the year, but the opposite later in the year, resulting in net "deaths as usual" over the whole year.
  - disgruntledphd2 6y ago
    > Given the average age of deaths by COVID-19 being above average life expectancy, this totally seems possible to me - lots of excess deaths early in the year, but the opposite later in the year, resulting in net "deaths as usual" over the whole year. Life expectancy at birth, and life expectancy given a particular age are very different. Most of those Covid deaths were above life expectancy are using life expectancy at birth figures, which is very misleading (as if you make it 82 you're almost certainly a fitter than average 82 year old).

spion 6y ago

The reason why they are banned is because what he is saying sounds plausible but is very, very likely wrong. First of all, the number of tests isn't growing at the same rate as the number of cases, hospitalizations and deaths: https://imgur.com/2cVrGz7 https://imgur.com/2cVrGz7 You can notice the very low positive rate in mid August (150 000 tests and only 500 cases - even if all false positives, thats 0.3% FP rate) But okay, lets assume that they did something to ramp up the false positive rate, If we look at the daily rate of growth (% increase) for cases, hospitalizations and deaths: https://imgur.com/bEix1Fo https://imgur.com/bEix1Fo We can see that there is a perfect exponential 7% rate of growth starting in September and slowly decaying after. But more than that, the rate of growth in hospitalizations and deaths also follows the same pattern almost perfectly but with a 5 day and 16 day delay, respectively! If you were accidentally getting false positives, you would either not expect hospitalizations and deaths to grow at the same rate as false positives do. Even if they did, you would expect them to grow at exactly the same time without any delays. If there is no causal relationship they should all grow at the same rate, at the same time as any other random subgroup of people To get the delay to happen, you would have to somehow perfectly fine tune the false positives for hospitalizations and deaths as well. In which case you're better off just making numbers up. But more importantly, there is a much simpler explanation, which we get if we super-impose google mobility trends % increase in amount spent staying at home, and we shift cases by 6 days (avg time to symptoms), hospitalizations by 11 and deaths by 22 days: https://imgur.com/UKklUIP https://imgur.com/UKklUIP We can see that the rate of growth is almost perfectly inversely correlated with the % increase in staying at home (with perhaps some light seasonal / immunity / other measures effects included). Additionally we have non-PCR data like the Zoe symptom tracker app largely corraborating more or less the same rate of growth as detected by PCR tests: https://covid.joinzoe.com/data#levels-over-time https://covid.joinzoe.com/data#levels-over-time

spion 6y ago
But more generally, there is a fundamental problem with social media: it unfortunately acts a generator of large amounts of "perfect bullshit". First, it gets thousands of people to generate various conspiracy theories and plausable looking ideas. Many of these will be interesting and have some real merit, but most of them wont. (By itself, this doesn't do much - we're people, we generate ideas and theories, many of them wrong - nothing special about this process). Then, give people the retweet button, and have them act as a filter for the most convincing looking bullshit. This is where things go terribly wrong. Retweets are a powerful amplifier. What gets retweeted? Is it the most throughly researched content? Highly unlikely, most people aren't experts in the subject (heck, I don't even dare go into the mechanics of the theory, only the math and stats) but they will still retweet if they find it interesting, plausible and aligned with what they strongly believe or wish was true. Side note: having some authority (Nobel prize, etc) also helps a lot with this process. Still, remember that social networks won't differentiate whether 1 scientist is actually having this idea or many, and worse, it won't necessarily inform you if many scientists are actually demonstrating how the idea is wrong (unless they make it equally interesting for a retweet) Finally, trick people by giving them dopamine system rewards (notifications for retweets and likes). They inevitably end up surrounded by a group of supporters that praise and retweet what they say. This whole process makes it so much harder for people (even scientists) to go back on what they said if it turns out they were wrong. So what do you end up with? You end up with a system that delivers the most perfect bullshit to the largest number of people. The scientists that tweet the same old boring conservative stuff (words like "likely" often appear) are largely voiceless. I don't think any single person is necessarily at fault in this system. But I do think that the system is a total disaster, and we have to invent something better than this. These simplistic social network designs are failing humanity.

Marazan 6y ago

He's totally, utterly wrong. Wrong on a spectacular level. We empircally know he is wrong because when schools went back there was a MASSSSSSIVE spike it requested tests (as school children got their start of season colds and worried parents got them tested in the first 2 weeks of school returning). But there was not a MASSSSSIVE spike in Covid cases. If Covid numbers were being driven by false positives then there HAD to be a massive spike in cases as testing numbers spiked. There was not. So false positives cannot be the reason.

DanBC 6y ago

Plenty of immunologists (esp those still working) disagree with a lotof what Yeadon says. Here's a pretty good explainer: https://twitter.com/andrew_croxford/status/1330882994471653376 https://twitter.com/andrew_croxford/status/13308829944716533... And another: https://twitter.com/andrew_croxford/status/1331722078777729024 https://twitter.com/andrew_croxford/status/13317220787777290...

robtaylor 6y ago

Yeadon has published, and has kept published, a known lie https://twitter.com/MichaelYeadon3/status/1318450567631544320 https://twitter.com/MichaelYeadon3/status/131845056763154432... Why would someone who deals in facts do such a thing? Surely the correct position would be to correct and remove. Personally anyone who refers to his material is tarnished. On a general point, there are many people now growing in fame (and monetising that) due to the pandemic. Are their interests aligned with a pandemic ending, what do they pivot to?

bjourne 6y ago
That is a very long twitter thread. What in it is a known lie?
- robtaylor 6y ago
  The first two posts, perhaps more? Considering the OP is calling into question why this person was booted from some social media, posting lies about public hospitals and their staff during a pandemic seems a fair reason. Shame the posts on Twitter remain and a shame Twitter themselves have not taken action.
  - bjourne 6y ago
    Two first posts: "A source just gave me the following information. A hospital in Wales, Nevill Hall in Abergavenny, has 250 beds. 200 beds are empty. The surgeons are bored & pass much time on the nearby golf course. I think this might be one answer to why UK doctors are not investigating to find out why hospitals have no patients in them! Apparently all covid cases are currently being sent to this hospital. This story tallies with the original evidence which drew me into this ghastly mess we’ve made of our country. I’ve not mentioned this..." What in it is a known lie?
    - robtaylor 6y ago
      You appear a clever chap, so you can verify that the statements are false. You can also locate where the author also states they are false, but does not delete them. It might be a sixth form debating point, but you have also have previously posted "The problem is that it has become acceptable to treat ideas as dangerous. For example, if I want to deny the Holocaust, that is my right." That is where I bow out, with a link to show how such 'ideas' and 'rights' have real world impact during this pandemic https://twitter.com/dashaburns/status/1332798207911399424?s=12 https://twitter.com/dashaburns/status/1332798207911399424?s=... Have a great day / life etc.