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Previously on "Coronavirus: Follow virus advice or 'tougher measures' likely, says PM"

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  • darmstadt
    replied
    Originally posted by SueEllen View Post
    I'm surprised always at the number of women who do this especially with primary aged children....
    Theoretically men, and probably women, should wash their hands after entering the toilets. You've just opened a door which has been touched by a multitude of people and then you're going to touch sensitive private parts....

    Leave a comment:


  • SueEllen
    replied
    Originally posted by scooterscot View Post
    Always amazed at the number of blokes that walk out of the public loo without washing their hands. Filthy buggers.

    Was at services along the M4 a few months back, practically had the sinks to myself.
    I'm surprised always at the number of women who do this especially with primary aged children....

    Leave a comment:


  • darmstadt
    replied
    In Leeds:

    For the last 4 years Johnson, Gove and Raab have been telling the British people that;

    1. They shouldn't listen to experts
    2. They should not follow the example of other countries
    3. They are special

    So why are they surprised when the British people;

    1. Ignore experts
    2. Don't follow the example of other countries
    3. Think they are special

    Leave a comment:


  • hairymouse
    replied
    Originally posted by d000hg View Post
    I am surprised the police cannot disperse crowds.

    One imagines all the people went out expecting it to be quiet. The thing is you CAN have a heck of a lot of people outside maintaining 2m distance (over 1000 can fit in a football pitch!) but you inevitably get pinch points as they enter and exit.
    A looped walk could be very busy if you could stop people bunching in the car-parks.

    Best is just find your nearest footpath, not some national beauty spot.
    I live in Richmond and was actually in Bushy Park on Saturday, which was then featured on the national news as a bad example. As you said, the exits were pinch points and that's where they chose to film. Even then, people were keeping a pretty good distance, but when filmed from a distance it looks like everyone is bunched up. Once inside, there was a decent amount of space. I don't know about the parking lots or kiosks as we didn't go anywhere near.

    Also as you said, the next day we choose a route that runs alongside the sewage treatment plant and there were considerably fewer people.

    Leave a comment:


  • sasguru
    replied
    Originally posted by jamesbrown View Post
    Looks interesting, thanks.
    On that paper I think the low R number in Korea is biased (low) because of their very sophisticated tracking and warning techniques.

    Leave a comment:


  • sasguru
    replied
    But actually an overall IFR or CFR is less important than an age stratified one. Basically under 50, death rates are similar to normal flu. Above 50 they're most certainly not.

    Leave a comment:


  • jamesbrown
    replied
    Originally posted by sasguru View Post
    Also the S. Korea example is informative, but they had very sophisticated techniques to stop spread, this has CFRS:

    https://www.ijidonline.com/article/S...150-8/fulltext
    Looks interesting, thanks.

    Leave a comment:


  • jamesbrown
    replied
    Originally posted by sasguru View Post
    Not my area either and for obvious reasons of speed not many peer reviewed papers out yet. Obviously everything is an informed guess but I think 0.5%-1% is very reasonable.

    Some indications (albeit from an obviously biased sample: rich 50-somethings healthy enough to go on a cruise, but we have the denom for this unusually, so its a kind of controlled experiment):

    Cruise ship outbreak helps pin down how deadly the new coronavirus is | Science News.

    But the 1% is quoted by Whitty and I think the Imperial College team have his ear.
    Right. The discrepancy between CFR and IFR should reduce as the testing becomes more expansive, but 0.2% does seem low. Either way, it's the impact of comorbidities (conditional rate) that stand out to me, albeit even harder to estimate, and I don't know if they're particularly different for other SARS-like CVs.

    Leave a comment:


  • d000hg
    replied
    I am surprised the police cannot disperse crowds.

    One imagines all the people went out expecting it to be quiet. The thing is you CAN have a heck of a lot of people outside maintaining 2m distance (over 1000 can fit in a football pitch!) but you inevitably get pinch points as they enter and exit.
    A looped walk could be very busy if you could stop people bunching in the car-parks.

    Best is just find your nearest footpath, not some national beauty spot.

    Leave a comment:


  • sasguru
    replied
    Originally posted by jamesbrown View Post
    My understanding is that the IFR is, by definition, harder to calculate than the CFR precisely because it requires these assumptions about "true" infections.

    Where have you seen better or less arbitrary assumptions as the basis for modeling? Genuine question, because this is not my area, but I take an interest from a statistical modeling POV.
    Not my area either and for obvious reasons of speed not many peer reviewed papers out yet. Obviously everything is an informed guess but I think 0.5%-1% is very reasonable.

    Some indications (albeit from an obviously biased sample: rich 50-somethings healthy enough to go on a cruise, but we have the denom for this unusually, so its a kind of controlled experiment):

    Cruise ship outbreak helps pin down how deadly the new coronavirus is | Science News.

    But the 1% is quoted by Whitty and I think the Imperial College team have his ear.

    Also the S. Korea example is informative, but they had very sophisticated techniques to stop spread, this has CFRS:

    https://www.ijidonline.com/article/S...150-8/fulltext

    And most obviously, this which Ive posted elsewhere:

    https://www.imperial.ac.uk/media/imp...16-03-2020.pdf
    Last edited by sasguru; 23 March 2020, 12:25.

    Leave a comment:


  • jamesbrown
    replied
    Originally posted by sasguru View Post
    Hmmm their methodology seems complete arbitrary. IFR of 0.2% based on :

    "Therefore, to estimate the IFR, we used the estimate from Germany’s current data 22nd March (93 deaths 23129) cases); CFR 0.40% (95% CI, 0.33% to 0.49%) and halved this for the IFR of 0.20% (95% CI, 0.17% to 0.25%) based on the assumption that half the cases go undetected by testing and none of this group dies"

    Let alone the arbitrariness of simply halving, there are severe problems of bias using just German death data - for one its health system probably has the most capacity of any system in the world (largest per capita no of ventilators and ICU beds)
    My understanding is that the IFR is, by definition, harder to calculate than the CFR precisely because it requires these assumptions about "true" infections.

    Where have you seen better or less arbitrary assumptions as the basis for modeling? Genuine question, because this is not my area, but I take an interest from a statistical modeling POV.

    Leave a comment:


  • sasguru
    replied
    Originally posted by jamesbrown View Post
    Good article here on fatality rates and conditionalities (and uncertainties and unknowns):

    https://www.cebm.net/global-covid-19...atality-rates/
    Hmmm their methodology seems complete arbitrary. IFR of 0.2% based on :

    "Therefore, to estimate the IFR, we used the estimate from Germany’s current data 22nd March (93 deaths 23129) cases); CFR 0.40% (95% CI, 0.33% to 0.49%) and halved this for the IFR of 0.20% (95% CI, 0.17% to 0.25%) based on the assumption that half the cases go undetected by testing and none of this group dies"

    Let alone the arbitrariness of simply halving CFR, there are severe problems of bias using just German death data (which has one of the lowest CFRs to date) - for one its health system probably has the most capacity of any system in the world (largest per capita no of ventilators and ICU beds)
    Last edited by sasguru; 23 March 2020, 12:08.

    Leave a comment:


  • jamesbrown
    replied
    Originally posted by sasguru View Post
    The 1% is a figure that most epidemiologists have arrived at as a reasonable figure, when all the dust has settled.
    The WHO figure of 3.4% is too high.
    In part based on analysis of Diamond Princess where the denom was known.
    I've read several academic papers on this, I suggest you do the same.
    Good article here on fatality rates and conditionalities (and uncertainties and unknowns):

    https://www.cebm.net/global-covid-19...atality-rates/

    Leave a comment:


  • sasguru
    replied
    Originally posted by Whorty View Post



    Seems you're a bit slow on the uptake in many ways .... even Shauny beat you to this conclusion, years ago
    Yes I suppose your Remainer tendencies which blinded me were just random noise

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  • sasguru
    replied
    Originally posted by Whorty View Post
    Show us your workings and assumptions then, rather than just posting soundbites and getting all hissy-fitty. Is this what you're like at work when you come up with some analysis and people want to know how you got there?
    The 1% is a figure that most epidemiologists have arrived at as a reasonable figure, when all the dust has settled.
    The WHO figure of 3.4% is too high.
    In part based on analysis of Diamond Princess where the denom was known.
    I've read several academic papers on this, I suggest you do the same.

    Leave a comment:

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