I don't know if other shipmates have been through the anxieties of wondering if they have the virus. I have developed a very sore throat this weekend and general body aches, so I guess I will have to report for testing. All very alarming as I have been vigilant in isolating and all the health precautions we are required to practice. I don't mind admitting that I am scared.
My worry is about how many people had some kind of cough or fever earlier this year and wrongly assume they've had COVID-19 and are now immune.
I had a particularly brutal one than knocked me out for a week or more a few weeks before lockdown, but I don't think it was Covid-19.
There is no basis for any assumption at all. You might or might not have had it. We have to presume ALL symptoms which intersect with the COVID-19 symptoms are. Full stop.
I think the point he was making is that he doesn't assume he is now immune.
Worldometer is now showing just over 80 thousand deaths in the US , up by 13 thousand in the past week. That's tragic.
What looks even more ominous is that there have been close to 200 thousand new cases in the US diagnosed in the past week. Over three quarters of the new cases have arisen outside the epicentres of New York and New Jersey.
I note that ex President Obama has just described the response of the Trump Administration to the Coronavirus pandemic as 'an absolute chaotic disaster'. That looks a fair description.
And, almost on cue, Fauci, Redfield and Hahn are self isolating because of exposure to a WH official who tested positive. I wonder if Birx will have to do the same.
They are of course simply following their own advice. But there is now a photograph of Trump and the Chiefs of Staff meeting today in a situation room in the WH and NOT following the standard quarantining advice.
United Arab Emirates - 17,417 (12,937 / 4,295 / 185)
Israel - 16,454 (4,831 / 11,376 / 247) 2.1%
Austria - 15,833 (1,290 / 13,928 / 615) 4.2%
Japan - 15,663 (9,150 / 5,906 / 607)
Poland - 15,651 (9,429 / 5,437 / 785)
Romania - 15,131 (7,280 / 6,912 / 939)
Ukraine - 14,710 (11,425 / 2,909 / 376)
Bangladesh - 13,770 (11,142 / 2,414 / 214)
Indonesia - 13,645 (10,079 / 2,607 / 959)
South Korea - 10,874 (1,008 / 9,610 / 256) 2.6%
Philippines - 10,610 (8,064 / 1,842 / 704)
Colombia - 10,495 (7,481 / 2,569 / 445)
Denmark - 10,319 (1,700 / 8,093 / 526) 6.1%
Serbia - 10,032 (7,087 / 2,732 / 213)
The listings are in the format:
X. Country - [# of known cases] ([active] / [recovered] / [dead]) [%fatality rate]
Fatality rates are only listed for countries where the number of resolved cases (recovered + dead) exceeds the number of known active cases by a ratio of at least 2:1.
Italics indicate authoritarian countries whose official statistics are suspect. Other country's statistics are suspect if their testing regimes are substandard.
If American states were treated as individual countries twenty-four of them would be on that list. New York would be ranked at #2, between "everywhere in the U.S. except New York" (#1) and Spain (#3). New Jersey would be between Brazil and Turkey.
Serbia has joined the 10,000 case club since the last compilation.
I don't know if other shipmates have been through the anxieties of wondering if they have the virus. I have developed a very sore throat this weekend and general body aches, so I guess I will have to report for testing. All very alarming as I have been vigilant in isolating and all the health precautions we are required to practice. I don't mind admitting that I am scared.
My worry is about how many people had some kind of cough or fever earlier this year and wrongly assume they've had COVID-19 and are now immune.
I had a particularly brutal one than knocked me out for a week or more a few weeks before lockdown, but I don't think it was Covid-19.
There is no basis for any assumption at all. You might or might not have had it. We have to presume ALL symptoms which intersect with the COVID-19 symptoms are. Full stop.
I think the point he was making is that he doesn't assume he is now immune.
Quite. Had the self-isolation advice been issued then I would have done so. However, this was in the Time Before.
That's Dr. Deborah Birx, who is the administration's coronavirus task force response coordinator. I know there are various (possibly legit) questions about the CDC and the WHO. But this has me wondering if T has gotten to Dr. Birx...and she's seemed to me one of the saner people dealing with this at the White House level...
I am sure I'm not the only one who when hearing about the positive tests and utter foolishness in the White House who is reminded of Edgar Allan Poe's The Masque of the Red Death
That's Dr. Deborah Birx, who is the administration's coronavirus task force response coordinator. I know there are various (possibly legit) questions about the CDC and the WHO. But this has me wondering if T has gotten to Dr. Birx...and she's seemed to me one of the saner people dealing with this at the White House level...
Apparently the CDC data collection methods are a bit cranky, but so far as I can work out from the worldometer website, each state produces its own daily summary (updated during the day in some cases) and the worldometer and Johns Hopkins summaries are produced by collating the data from the States. CDC may have advised on how the State counting is to be done and presented, but that's another matter.
Forecasting is another matter again. Birx may have been criticising the increased forecast produced by the CDC that relaxation of restrictions in the States could lead to a spike to 3,000 deaths a day by 1 June. That is a projection via a model. Since all the States are doing different things, I'm not at all clear that there is a very good basis for a model just yet.
I'm pretty sure things are going to get worse but the 7 day average for daily mortality is currently close to 2,000 deaths. A 50% increase in that two or three weeks after the relaxations seems well within the bounds of possibility.
It does sound as though Birx may have been using some perfectly legitimate concerns to score a point with the President. In the Court of the Mad King, wise courtiers sometimes feel the need to play such dangerous games.
Quite a few journos asking if it's a coincidence that the US and UK top the table of deaths, and if this connects with right wing, small state, isolationist, exceptionalist governments, who were ill-equipped to handle a pandemic. I have no idea, sure, it's an interesting thesis, but you can probably construct a few others.
It's not uniquely so. Australia (after failing miserably with the fires) has done ok writ Covid, as has the Philippines and other right wing governments.
Whereas Spain was badly hit and has a left wing (coalition) government and Sweden's actions and outcome is complicated.
And then there's China, which is also complicated (not least because probably everyone, and at least the right wing*) is lying about what happened and is happening.
But I think the UK's and USA's government have done things that haven't helped (especially as what we're mostly worried about is what's just starting in both) and that were/are obviously flawed.
*The giveaway being that the story changes, inconsistently.
Quite a few journos asking if it's a coincidence that the US and UK top the table of deaths, and if this connects with right wing, small state, isolationist, exceptionalist governments, who were ill-equipped to handle a pandemic. I have no idea, sure, it's an interesting thesis, but you can probably construct a few others.
Here's a Twitter thread by someone who routinely analyzes alt-right (and other very far right) internet postings:
Everyone [ ed: on the far right internet ] agrees that ours was a hysterical, panicky and entirely excessive reaction, which is emblematic for the (post-)modern world and society (in contrast to them). Soft, headless politicians without leadership qualities stand for such a society.
And it is precisely here that we witness one of the most central elements of fascist ideology: the weak and all its synonyms. A decadent, soft, unmanly, hysterical, panicky, timid, effeminate society is the problem.
This is not new and also formed a central narrative of the emerging fascism during modernity's breakthrough: men aren't men anymore, but nervous, urban, overly intellectualized and (here it comes) sickly weaklings. The idea of sick as weak is important.
And it is exactly the same point of attack again: To panic because of this virus doesn't agree with masculine or national(ist) values. This is met with all kinds of moral assessments: it hurts the dignity, esteem, the spirit and so forth of the people („Volk“)
<snip>
Accordingly, in the intellectual treatment of it there are no innocent calls for the protection of grandparents (like we know from racist discourses) but only confirmation that the weak pulled the short straw. And should carry their burden with dignity.
In this there is no distinction between war and virus, because the principle of "bearing it" and dying without protest for the greater good are really principles of the fascist heroizing of war. War and the hero's death as value in itself.
<snip>
And what is demanded as a globally social strategy is to let things go their usual way, both in order not to ruin the economy and because the lockdown is a fearful and thus unmanly strategy, and the measure are the strong, not the weak.
What is demanded from people in the risk group is to not be weak, but strong, which means to die without protest. If they don't do it, they are weak and the weak drag everyone else down and therefore must be done away with.
There's a lot more and the whole thing is worth a read. The U.K. and U.S. governments obviously aren't fascist themselves (though I have my doubts about certain very specific members of the Trump administration*) but the alt-right exists to filter fascist ideas and insert them into what is considered the respectable right. I think we're seeing some of that here.
Quite a few journos asking if it's a coincidence that the US and UK top the table of deaths, and if this connects with right wing, small state, isolationist, exceptionalist governments, who were ill-equipped to handle a pandemic. I have no idea, sure, it's an interesting thesis, but you can probably construct a few others.
I think the common factor is that Johnson and Trump are primarily showmen, not politicians.
Quite a few journos asking if it's a coincidence that the US and UK top the table of deaths
All other things being the same, places with bigger populations will have more deaths. Also, places with higher population densities will have more cases simply because people are wedged in so much more closely.
Furthermore, places with significant levels of inward travel will begin their curve sooner than those that are comparatively isolated from the rest of the world. There are some big countries that are still way earlier in the curve than the UK and US, and that may well overtake us before all this is over.
Once this is all over (if this is ever all over) and all those factors can be adjusted for, then it will be a bit more possible to compare the impact of various political leadership styles and philosophies on the various outcomes.
Quite a few journos asking if it's a coincidence that the US and UK top the table of deaths, and if this connects with right wing, small state, isolationist, exceptionalist governments, who were ill-equipped to handle a pandemic. I have no idea, sure, it's an interesting thesis, but you can probably construct a few others.
It's not the only factor but it is relevant. There is a correlation between idiots in leadership and higher death rates. (Especially when you consider that both the UK and the USA saw what was happening in Italy).
Now, good science demands not jumping to conclusions and remembering the truism that correlation does not equal causation.
So the next question is simply is there a plausible mechanism connecting the proposed cause with the reported effect? for example, there's a strong correlation between carrying a lighter in your pocket and lung cancer but no plausible mechanism for the lighter carrying to cause the cancer...
Given that the US and UK governments have made decisions that are contrary to everything that we've known for decades about controlling an epidemic... and for transparently political reasons... yeah I'd say there was a causative link...
Croesos, many thanks for your stuff on the weak/sick equation in right wing thinking. It is quite widespread, there are comments that we are bed-wetters and scaredy cats, because we don't want to die!
And the heroic equation with death is long lived, I remember the Falangist slogan, down with intelligence, long live death. Interesting that some of them are scornful of Boris, not hard enough. As Hitler said, we must be as hard as Krupp's steel.
Quite a few journos asking if it's a coincidence that the US and UK top the table of deaths
All other things being the same, places with bigger populations will have more deaths. Also, places with higher population densities will have more cases simply because people are wedged in so much more closely.
Furthermore, places with significant levels of inward travel will begin their curve sooner than those that are comparatively isolated from the rest of the world. There are some big countries that are still way earlier in the curve than the UK and US, and that may well overtake us before all this is over.
Once this is all over (if this is ever all over) and all those factors can be adjusted for, then it will be a bit more possible to compare the impact of various political leadership styles and philosophies on the various outcomes.
The US and South Korea both reported their first Covid-19 patient on January 20. South Korea promptly started testing, contact tracing, and quarantining the sick. Today big chunks of South Korea have had no new cases in the last 14 days. 256 people there have died, about 5 per 1M of population. The US sat here with our collective thumb up our ass -- Chinese people weren't let in, but Americans who had visited China were admitted and not tested or quarantined and of course it didn't occur to the powers that be that folks coming from Europe could be virus carriers, we fucked up in constructing a test, and we shut down large parts of the country only after it was too late. Now some parts are now re-opening despite the fact that the number of new cases is still growing and we don't have adequate testing and contact tracing. Our deaths sit at 80,500+ and growing, 243 deaths per 1M of population.
I don't need to wait until it's all over to know that South Korean authorities are handling this a lot better than American ones. Or British authorities - you guys are sitting at 469 deaths per 1M population.
Quite a few journos asking if it's a coincidence that the US and UK top the table of deaths, and if this connects with right wing, small state, isolationist, exceptionalist governments, who were ill-equipped to handle a pandemic. I have no idea, sure, it's an interesting thesis, but you can probably construct a few others.
It's not the only factor but it is relevant. There is a correlation between idiots in leadership and higher death rates. (Especially when you consider that both the UK and the USA saw what was happening in Italy).
Now, good science demands not jumping to conclusions and remembering the truism that correlation does not equal causation.
So the next question is simply is there a plausible mechanism connecting the proposed cause with the reported effect? for example, there's a strong correlation between carrying a lighter in your pocket and lung cancer but no plausible mechanism for the lighter carrying to cause the cancer...
Given that the US and UK governments have made decisions that are contrary to everything that we've known for decades about controlling an epidemic... and for transparently political reasons... yeah I'd say there was a causative link...
AFZ
MD in Private Eye had a nice comment: The UK says it has followed the science every step of the way, so what the hell have Germany and South Korea been following?
That said ...
Earlier in the thread I was arguing that the source of the guidance seems genuinely to be the Chief Scientific Advisor and the Chief Medical Officer, so even if that guidance is utterly wrong from start to finish, Mr Johnson is not the source of that guidance and therefore its wrongness is not caused by his government's ideology. That was before it was revealed that Mr Cummings was participating in Sage meetings, which somewhat knocks a hole in my argument, but nevertheless, it does still seem that at least some of the bad decisions are coming from the medical establishment rather than gung-ho Cabinet ministers.
For example, in March, it was Dr Jenny Harries, Deputy Chief Medical Officer for England,
who was saying that the UK could ignore the WHO's advice on testing because the WHO is a world organisation - "The clue is in the name" - and testing was more important for countries with a less developed health service. Like Germany and South Korea, presumably ...
Forecasting is another matter again. Birx may have been criticising the increased forecast produced by the CDC that relaxation of restrictions in the States could lead to a spike to 3,000 deaths a day by 1 June. That is a projection via a model. Since all the States are doing different things, I'm not at all clear that there is a very good basis for a model just yet.
Not sure what you mean by "yet" here, given the reason you give. The states aren't all going to start doing the same thing any time before the parousia. However if each state is consistent you could have 50 models, each accurate for its target.
The UK did not follow science. It delayed. We locked up a week before the UK with exactly 8 infections in 1.1 million. Many of us felt the gov't delay of 3 days here was inexcusable. Small potatoes comparatively, but shows that political inferences kills.
United Arab Emirates - 18,198 (13,196 / 4,804 / 198)
Israel - 16,477 (4,795 / 11,430 / 252) 2.2%
Poland - 15,996 (9,498 / 5,698 / 800)
Austria - 15,871 (1,262 / 13,991 / 618) 4.2%
Japan - 15,777 (7,026 / 8,127 / 624)
Romania - 15,362 (7,350 / 7,051 / 961)
Ukraine - 15,232 (11,781 / 3,060 / 391)
Bangladesh - 14,657 (11,779 / 2,650 / 228)
Indonesia - 14,032 (10,361 / 2,698 / 973)
Colombia - 11,063 (7,895 / 2,705 / 463)
South Korea - 10,909 (1,021 / 9,632 / 256) 2.6%
Philippines - 10,794 (8,151 / 1,924 / 719)
Denmark - 10,429 (1,683 / 8,217 / 529) 6.0%
Dominican Republic - 10,347 (7,196 / 2,763 / 388)
Serbia - 10,114 (6,893 / 3,006 / 215)
South Africa - 10,015 (5,648 / 4,173 / 194)
The listings are in the format:
X. Country - [# of known cases] ([active] / [recovered] / [dead]) [%fatality rate]
Fatality rates are only listed for countries where the number of resolved cases (recovered + dead) exceeds the number of known active cases by a ratio of at least 2:1.
Italics indicate authoritarian countries whose official statistics are suspect. Other country's statistics are suspect if their testing regimes are substandard.
If American states were treated as individual countries twenty-six of them would be on that list. New York would be ranked at #2, between "everywhere in the U.S. except New York" (#1) and Spain (#3). New Jersey would be between Brazil and Turkey.
The Dominican Republic and South Africa have joined the 10,000 case club since the last compilation.
The NZ Prime Minister announced today that the country will move to Alert Level 2 at 11.59pm on Wednesday. This means that the Library will be open, as will retail shops, schools, Universities etc, will open again on Monday and domestic travel will not be subject to restrictions.
Meanwhile we should all keep an eye on Germany where the slight easing of restrictions has lead to an increase in infection rates, showing that we need to make sure the level of infection in the community is very low before we ease back on the restrictions in place. If we ease back too soon then not only do we add to the death toll, we end up taking longer before we can make a significant step out of lockdown.
Forecasting is another matter again. Birx may have been criticising the increased forecast produced by the CDC that relaxation of restrictions in the States could lead to a spike to 3,000 deaths a day by 1 June. That is a projection via a model. Since all the States are doing different things, I'm not at all clear that there is a very good basis for a model just yet.
Not sure what you mean by "yet" here, given the reason you give. The states aren't all going to start doing the same thing any time before the parousia. However if each state is consistent you could have 50 models, each accurate for its target.
I've done some checking since my post, because I wasn't quite sure what CDC did re forecasting.
It looks as though the CDC presents a range of forecasts based on various models, rather than "hanging its hat" on any particular one. That range does seem to cover both national and State forecasts. So I think both of my premises were wrong!
I was trying to understand why Birx should rubbish the CDC re any matter in the way she is reported to have done. Still don't!
Running multiple models (or, the same mathematical model with slight variations on input data) is the standard way of determining confidence limits (and, also identify what data is critical to know to the highest possible precision and accuracy). The nature of mathematical models is that the numbers run through with infinite precision, and hence a single model won't have confidence limits.
Question: Somewhere in the media, maybe a few days ago, someone who knows about statistical models said "All models are wrong, but they're helpful".
Opinions on that? I think the idea, AIUI, is that the models are attempts to figure out and play out different structures and possibilities, based on data.
Ah, Monte Carlo methods. 'Ave a guess. Go on, 'ave another one (I know it's useful - it just always struck me as funny).
Yep, that's it. It's not the only way (if there's a single input variable then you can simply run the model across the range of that variable within it's 95% confidence interval), but especially where variables are co-related Monte Carlo approaches are extremely efficient at ensuring you've covered the whole probability space.
GK, I think (with ex-engineer head on) that you're right. A model can be wrong for lots of reasons - the maths link between the inputs and the outputs can fail to minic reality, you can have the wrong inputs or just be missing an important one, random influences ('noise') can be present in real-life data which has its own set of challenges if you want to build it into your maths - it goes on and on. But what you want is a result better than a guess, which lets you mess around with your variables (control knobs) fairly quickly to see what their influence on the output is likely to be. Even if the numbers are out by a factor of 10, 'this makes it better, that makes it worse, and the other makes it really, really worse' can be very useful (note this is not just about better and worse, but rank ordering - which can still work even if your absolute values are way off). Being out by x2 in absolute terms is still, often, a very good result.
All this makes me smile ruefully about the hassle that Vallance (?) got over his 'we'll be lucky if <20k people die'. In modelling terms that quick summary still stands up very strongly. And for a modeller, he was saying 'think in low tens of thousands, rather than in hundreds, or hundred-thousands'. If I'd had to guess, could I have done better?
The "all models are wrong, some can be useful" is a common statement among statisticians and others who use models. It's also true that quite common models are all we have, and by the time we get the information to significantly improve the models it's too late - we'll have accurate models of coronavirus spread and effects in a couple of years, but we need to make decisions today. That's one reason you want lots of different groups to independently develop different models - you hope that working independently different modellers won't all make the same mistakes. To rely on a single model is foolishness, and should only happen when there's only one model available. And, of course, models are revised as more data becomes available, and so you should work with the models including the best, most recent, data.
Weather forecasts are probably the best known examples of modelled outputs. No one would rely on a forecast for tomorrow issued a week ago, we'll all go and see the forecast issued this morning because that includes all the data about how the weather systems have developed since that earlier forecast.
In relation to the coronavirus spread models will be being used for different reasons. You want a model to predict what health resources you need in a weeks time so you have time to get them into place. You want a model where you can put in different conditions and see what happens - how many more cases will you get if you have 10% more people using the London Underground? what will be the impact of 10% of the population driving to rural areas for a walk? At some point you might want a model to be able to answer the question of how many people would have died if nothing had been done or if measured advised had been enacted sooner, as part of a review of what could have been done better and learn lessons for the future.
The quote came from Dr Fauci, Golden Key. I like him. It was a reasonable comment on both the predictive limitation of models and their usefulness despite that. In that respect, it was very different to Dr Birx's reported rubbishing of the CDC. Which feeds straight into the dangerous and distorted Trump world view.
Modellers still struggle with the novelty of the virus, even though more is known about it now. It's essential to control its effective reproductive infection rate, keep it well below 1 (one person infects on average less than one person) so that the epidemic dies out. But if the rate does rise above 1 again, then the numbers of new infections will keep on increasing. And small changes in that rate produce quite big difference in new cases forecasts. The forecasts in models about this rate (and how it may be affected by relaxations of restrictions on personal contact) are crucial in determining the final figures. That's one of the reasons why the different models show a lot of variation in their predictions. They may also have different predictions about consequential sickness and mortality rates, though I should think these would be more marginal.
What they all show is that relaxing controls is risky. As the Germans appear to be finding out. The message to politicians is "go very carefully and be prepared to reverse course".
Meanwhile we should all keep an eye on Germany where the slight easing of restrictions has lead to an increase in infection rates, showing that we need to make sure the level of infection in the community is very low before we ease back on the restrictions in place. If we ease back too soon then not only do we add to the death toll, we end up taking longer before we can make a significant step out of lockdown.
I don’t think the easing was that slight. Hairdressers were open and very busy indeed. No social distance is possible between hairdresser and client.
I don't need to wait until it's all over to know that South Korean authorities are handling this a lot better than American ones. Or British authorities - you guys are sitting at 469 deaths per 1M population.
Too right. We started lockdown late, and we're still short of testing capability and PPE. I think we are going to tiptoe carefully and fearfully into cautious relaxation of social contact controls.
[I note that Russia is rapidly climbing the ladder of countries with most infections, but has a very low reported mortality rate (14 per million population) and actual death total (just over 2,000).]
Question: Somewhere in the media, maybe a few days ago, someone who knows about statistical models said "All models are wrong, but they're helpful".
Opinions on that? I think the idea, AIUI, is that the models are attempts to figure out and play out different structures and possibilities, based on data.
Thx.
This is an example of a smart person saying something really dumb.
What he means is that All models are not precise. Which is, of course true. But it is only in a truly pedantic sense that lack of precision equals "wrong." The problem being that most people who hear 'all models are wrong' will take that to mean the models are useless and thus the second part of the sentence will not be heard.
Let's use a simplistic example here:
Country A has a population of 50 million people and an average population density
Country B has a population of 50 million people and an average population density.
Camford University produces a model of a novel disease know as Tiraravirus - the model says that if certain measures are taken in a country much like countries A and B, then there will be 2000 deaths from Tiaravirus. It also says that if these measures aren't taken then there will be 40,000 deaths.
Country A thinks Camford University are quite smart and listen to them and introduce a range of measures. Tiaravirus causes 3462 deaths in the following year.
Country B thinks they know better and ignore the advice. Tiaravirus causes 29,000 deaths in country B.
Now tell me, was the model wrong?
It gets even more complicated when you consider Country C who has a population of 60 million and introduced some of the measured advised by Camford University. Their death toll was 12,000... "But of course we have more deaths than Country A, we have more people..."
It's not helpful to think about models as 'right' or 'wrong.' It's all about how precise they are. Two things matter in the real world rather than my simplistic example. The first is about assessing risk - not just in terms of probabilities or different outcomes but in terms of what is the consequence of such an outcome. For example, if you close your eyes for 10 seconds whilst driving at 70mph on a motorway, the odds are pretty good that no bad thing will happen. Conversely, if something bad does happen, it's likely to be a fatal accident. It is more tricky when choices are not consequence-free. We can all choose not to close our eyes for 10 seconds, that's easy. Closing down an economy does come with a big cost. However when you look at it seriously - even if the models are way out (they're not) then the excess cost in economic terms of closing down 'unnecessarily' is tiny compared to the excess cost in lives lost of not shutting down the economy. The second real-world factor is how the models are improving all the time with more and more data. In general, it's quite straightforward to know how the various factors interact - i.e. how infective a virus is and how many are infected right now and the population density - the relationship between these three example variables and the total number of cases you should expect is well understood. But with a new virus, the infectivity is unknown, with poor testing, the levels of infection in the community are unknown. Over time as we get more and more data, they get more precise. There's a helluva lot of data coming in at the moment.
The UK government has issued advice on making facemasks (not like they didn't have 5 months notice on the impending mass demand of masks or anything -- though will be interesting when there is a mass run on elastic).
The guidance states that they are to be worn in public transport and 'some shops'. Nice and unambiguous then, the police get to police 'unlawful' masks and no one can blame the government for lack of compliance.
Question: Somewhere in the media, maybe a few days ago, someone who knows about statistical models said "All models are wrong, but they're helpful".
Opinions on that? I think the idea, AIUI, is that the models are attempts to figure out and play out different structures and possibilities, based on data.
Thx.
This is an example of a smart person saying something really dumb.
Are you talking about Box, to whom the quote is originally attributed or Fauci? Because Box used the phrase in context and it was certainly not stupid. I'd have to hear/read Fauci's usage, but it is irresponsible IMO to use that phrase without context, especially in the context of where he is.
The more that the new plan is explained, the more confusing it gets. I've been watching travel restrictions, hoping for a holiday some time, and Raab seems to have said that you can drive as far as you want, in order to take exercise.
Local areas have reacted with alarm, as they don't want people pouring off to Cornwall, Lake District, etc. Anyway, I assume it means drive as far as you want, within one day. Oh well, Boris is now perorating, so I expect more confusion.
Also, is it correct that I can't visit a friend or relative, but I am expected to sit in an office, near a guy who is indifferent to social distancing, and gets passed every night with his mates? Rly?
I'm looking forward to having a nice round or two of golf soon. Even if I have to play on my own, it will be sooooo good to be able to do something fun for a few hours.
Excuse me for being thick, but isn’t golf a form of exercise that also is possible to do whilst social distancing ? As in, why can’t you already do that ?
It makes things clearer by not having some fuzzy line. If golf is allowed, why not croquet? If croquet, why not bowling? If bowling, why not tennis? If tennis, why not football? Somewhere there will be a line between safer and less safe forms of recreation, but it won't be clear ... clearer to just shut them all down. Which means, no pressure on club houses to be opened, no problems with unnecessary car trips ...
I heard Fauci say it in the context of a wider discussion re death and new case rates. From memory he was sceptical about the accuracy of predictions and insistent that the more the US focused on safe distancing, more testing, tracking and tracing the better the figures would be. His entire argument was about proactive counter measures. The usefulness of forecasts was that they pointed to how bad things would get if the recommended proactive measures weren't taken seriously.
Excuse me for being thick, but isn’t golf a form of exercise that also is possible to do whilst social distancing ? As in, why can’t you already do that ?
The problem with golf itself is the clubhouse. The flags. The carts. And any number of other things that people touch.
Comments
I think the point he was making is that he doesn't assume he is now immune.
What looks even more ominous is that there have been close to 200 thousand new cases in the US diagnosed in the past week. Over three quarters of the new cases have arisen outside the epicentres of New York and New Jersey.
I note that ex President Obama has just described the response of the Trump Administration to the Coronavirus pandemic as 'an absolute chaotic disaster'. That looks a fair description.
They are of course simply following their own advice. But there is now a photograph of Trump and the Chiefs of Staff meeting today in a situation room in the WH and NOT following the standard quarantining advice.
Absolute chaos? Pretty much.
The listings are in the format:
X. Country - [# of known cases] ([active] / [recovered] / [dead]) [%fatality rate]
Fatality rates are only listed for countries where the number of resolved cases (recovered + dead) exceeds the number of known active cases by a ratio of at least 2:1.
Italics indicate authoritarian countries whose official statistics are suspect. Other country's statistics are suspect if their testing regimes are substandard.
If American states were treated as individual countries twenty-four of them would be on that list. New York would be ranked at #2, between "everywhere in the U.S. except New York" (#1) and Spain (#3). New Jersey would be between Brazil and Turkey.
Serbia has joined the 10,000 case club since the last compilation.
Quite. Had the self-isolation advice been issued then I would have done so. However, this was in the Time Before.
Apparently the CDC data collection methods are a bit cranky, but so far as I can work out from the worldometer website, each state produces its own daily summary (updated during the day in some cases) and the worldometer and Johns Hopkins summaries are produced by collating the data from the States. CDC may have advised on how the State counting is to be done and presented, but that's another matter.
Forecasting is another matter again. Birx may have been criticising the increased forecast produced by the CDC that relaxation of restrictions in the States could lead to a spike to 3,000 deaths a day by 1 June. That is a projection via a model. Since all the States are doing different things, I'm not at all clear that there is a very good basis for a model just yet.
I'm pretty sure things are going to get worse but the 7 day average for daily mortality is currently close to 2,000 deaths. A 50% increase in that two or three weeks after the relaxations seems well within the bounds of possibility.
It does sound as though Birx may have been using some perfectly legitimate concerns to score a point with the President. In the Court of the Mad King, wise courtiers sometimes feel the need to play such dangerous games.
Whereas Spain was badly hit and has a left wing (coalition) government and Sweden's actions and outcome is complicated.
And then there's China, which is also complicated (not least because probably everyone, and at least the right wing*) is lying about what happened and is happening.
But I think the UK's and USA's government have done things that haven't helped (especially as what we're mostly worried about is what's just starting in both) and that were/are obviously flawed.
*The giveaway being that the story changes, inconsistently.
Here's a Twitter thread by someone who routinely analyzes alt-right (and other very far right) internet postings:
There's a lot more and the whole thing is worth a read. The U.K. and U.S. governments obviously aren't fascist themselves (though I have my doubts about certain very specific members of the Trump administration*) but the alt-right exists to filter fascist ideas and insert them into what is considered the respectable right. I think we're seeing some of that here.
I think the common factor is that Johnson and Trump are primarily showmen, not politicians.
All other things being the same, places with bigger populations will have more deaths. Also, places with higher population densities will have more cases simply because people are wedged in so much more closely.
Furthermore, places with significant levels of inward travel will begin their curve sooner than those that are comparatively isolated from the rest of the world. There are some big countries that are still way earlier in the curve than the UK and US, and that may well overtake us before all this is over.
Once this is all over (if this is ever all over) and all those factors can be adjusted for, then it will be a bit more possible to compare the impact of various political leadership styles and philosophies on the various outcomes.
It's not the only factor but it is relevant. There is a correlation between idiots in leadership and higher death rates. (Especially when you consider that both the UK and the USA saw what was happening in Italy).
Now, good science demands not jumping to conclusions and remembering the truism that correlation does not equal causation.
So the next question is simply is there a plausible mechanism connecting the proposed cause with the reported effect?
for example, there's a strong correlation between carrying a lighter in your pocket and lung cancer but no plausible mechanism for the lighter carrying to cause the cancer...
Given that the US and UK governments have made decisions that are contrary to everything that we've known for decades about controlling an epidemic... and for transparently political reasons... yeah I'd say there was a causative link...
AFZ
And the heroic equation with death is long lived, I remember the Falangist slogan, down with intelligence, long live death. Interesting that some of them are scornful of Boris, not hard enough. As Hitler said, we must be as hard as Krupp's steel.
The US and South Korea both reported their first Covid-19 patient on January 20. South Korea promptly started testing, contact tracing, and quarantining the sick. Today big chunks of South Korea have had no new cases in the last 14 days. 256 people there have died, about 5 per 1M of population. The US sat here with our collective thumb up our ass -- Chinese people weren't let in, but Americans who had visited China were admitted and not tested or quarantined and of course it didn't occur to the powers that be that folks coming from Europe could be virus carriers, we fucked up in constructing a test, and we shut down large parts of the country only after it was too late. Now some parts are now re-opening despite the fact that the number of new cases is still growing and we don't have adequate testing and contact tracing. Our deaths sit at 80,500+ and growing, 243 deaths per 1M of population.
I don't need to wait until it's all over to know that South Korean authorities are handling this a lot better than American ones. Or British authorities - you guys are sitting at 469 deaths per 1M population.
MD in Private Eye had a nice comment: The UK says it has followed the science every step of the way, so what the hell have Germany and South Korea been following?
That said ...
Earlier in the thread I was arguing that the source of the guidance seems genuinely to be the Chief Scientific Advisor and the Chief Medical Officer, so even if that guidance is utterly wrong from start to finish, Mr Johnson is not the source of that guidance and therefore its wrongness is not caused by his government's ideology. That was before it was revealed that Mr Cummings was participating in Sage meetings, which somewhat knocks a hole in my argument, but nevertheless, it does still seem that at least some of the bad decisions are coming from the medical establishment rather than gung-ho Cabinet ministers.
For example, in March, it was Dr Jenny Harries, Deputy Chief Medical Officer for England,
who was saying that the UK could ignore the WHO's advice on testing because the WHO is a world organisation - "The clue is in the name" - and testing was more important for countries with a less developed health service. Like Germany and South Korea, presumably ...
Not sure what you mean by "yet" here, given the reason you give. The states aren't all going to start doing the same thing any time before the parousia. However if each state is consistent you could have 50 models, each accurate for its target.
The listings are in the format:
X. Country - [# of known cases] ([active] / [recovered] / [dead]) [%fatality rate]
Fatality rates are only listed for countries where the number of resolved cases (recovered + dead) exceeds the number of known active cases by a ratio of at least 2:1.
Italics indicate authoritarian countries whose official statistics are suspect. Other country's statistics are suspect if their testing regimes are substandard.
If American states were treated as individual countries twenty-six of them would be on that list. New York would be ranked at #2, between "everywhere in the U.S. except New York" (#1) and Spain (#3). New Jersey would be between Brazil and Turkey.
The Dominican Republic and South Africa have joined the 10,000 case club since the last compilation.
Fingers crossed it will go well.
I've done some checking since my post, because I wasn't quite sure what CDC did re forecasting.
Here is a link.
It looks as though the CDC presents a range of forecasts based on various models, rather than "hanging its hat" on any particular one. That range does seem to cover both national and State forecasts. So I think both of my premises were wrong!
I was trying to understand why Birx should rubbish the CDC re any matter in the way she is reported to have done. Still don't!
Opinions on that? I think the idea, AIUI, is that the models are attempts to figure out and play out different structures and possibilities, based on data.
Thx.
All this makes me smile ruefully about the hassle that Vallance (?) got over his 'we'll be lucky if <20k people die'. In modelling terms that quick summary still stands up very strongly. And for a modeller, he was saying 'think in low tens of thousands, rather than in hundreds, or hundred-thousands'. If I'd had to guess, could I have done better?
Weather forecasts are probably the best known examples of modelled outputs. No one would rely on a forecast for tomorrow issued a week ago, we'll all go and see the forecast issued this morning because that includes all the data about how the weather systems have developed since that earlier forecast.
In relation to the coronavirus spread models will be being used for different reasons. You want a model to predict what health resources you need in a weeks time so you have time to get them into place. You want a model where you can put in different conditions and see what happens - how many more cases will you get if you have 10% more people using the London Underground? what will be the impact of 10% of the population driving to rural areas for a walk? At some point you might want a model to be able to answer the question of how many people would have died if nothing had been done or if measured advised had been enacted sooner, as part of a review of what could have been done better and learn lessons for the future.
Modellers still struggle with the novelty of the virus, even though more is known about it now. It's essential to control its effective reproductive infection rate, keep it well below 1 (one person infects on average less than one person) so that the epidemic dies out. But if the rate does rise above 1 again, then the numbers of new infections will keep on increasing. And small changes in that rate produce quite big difference in new cases forecasts. The forecasts in models about this rate (and how it may be affected by relaxations of restrictions on personal contact) are crucial in determining the final figures. That's one of the reasons why the different models show a lot of variation in their predictions. They may also have different predictions about consequential sickness and mortality rates, though I should think these would be more marginal.
What they all show is that relaxing controls is risky. As the Germans appear to be finding out. The message to politicians is "go very carefully and be prepared to reverse course".
I don’t think the easing was that slight. Hairdressers were open and very busy indeed. No social distance is possible between hairdresser and client.
Too right. We started lockdown late, and we're still short of testing capability and PPE. I think we are going to tiptoe carefully and fearfully into cautious relaxation of social contact controls.
[I note that Russia is rapidly climbing the ladder of countries with most infections, but has a very low reported mortality rate (14 per million population) and actual death total (just over 2,000).]
Mind you, I bet many Russians have an inbuilt immunity to the adverse effects of vodka, so it might work...
This is an example of a smart person saying something really dumb.
What he means is that All models are not precise. Which is, of course true. But it is only in a truly pedantic sense that lack of precision equals "wrong." The problem being that most people who hear 'all models are wrong' will take that to mean the models are useless and thus the second part of the sentence will not be heard.
Let's use a simplistic example here:
Country A has a population of 50 million people and an average population density
Country B has a population of 50 million people and an average population density.
Camford University produces a model of a novel disease know as Tiraravirus - the model says that if certain measures are taken in a country much like countries A and B, then there will be 2000 deaths from Tiaravirus. It also says that if these measures aren't taken then there will be 40,000 deaths.
Country A thinks Camford University are quite smart and listen to them and introduce a range of measures. Tiaravirus causes 3462 deaths in the following year.
Country B thinks they know better and ignore the advice. Tiaravirus causes 29,000 deaths in country B.
Now tell me, was the model wrong?
It gets even more complicated when you consider Country C who has a population of 60 million and introduced some of the measured advised by Camford University. Their death toll was 12,000... "But of course we have more deaths than Country A, we have more people..."
It's not helpful to think about models as 'right' or 'wrong.' It's all about how precise they are. Two things matter in the real world rather than my simplistic example. The first is about assessing risk - not just in terms of probabilities or different outcomes but in terms of what is the consequence of such an outcome. For example, if you close your eyes for 10 seconds whilst driving at 70mph on a motorway, the odds are pretty good that no bad thing will happen. Conversely, if something bad does happen, it's likely to be a fatal accident. It is more tricky when choices are not consequence-free. We can all choose not to close our eyes for 10 seconds, that's easy. Closing down an economy does come with a big cost. However when you look at it seriously - even if the models are way out (they're not) then the excess cost in economic terms of closing down 'unnecessarily' is tiny compared to the excess cost in lives lost of not shutting down the economy. The second real-world factor is how the models are improving all the time with more and more data. In general, it's quite straightforward to know how the various factors interact - i.e. how infective a virus is and how many are infected right now and the population density - the relationship between these three example variables and the total number of cases you should expect is well understood. But with a new virus, the infectivity is unknown, with poor testing, the levels of infection in the community are unknown. Over time as we get more and more data, they get more precise. There's a helluva lot of data coming in at the moment.
AFZ
The guidance states that they are to be worn in public transport and 'some shops'. Nice and unambiguous then, the police get to police 'unlawful' masks and no one can blame the government for lack of compliance.
Local areas have reacted with alarm, as they don't want people pouring off to Cornwall, Lake District, etc. Anyway, I assume it means drive as far as you want, within one day. Oh well, Boris is now perorating, so I expect more confusion.
I heard Fauci say it in the context of a wider discussion re death and new case rates. From memory he was sceptical about the accuracy of predictions and insistent that the more the US focused on safe distancing, more testing, tracking and tracing the better the figures would be. His entire argument was about proactive counter measures. The usefulness of forecasts was that they pointed to how bad things would get if the recommended proactive measures weren't taken seriously.
I had no problems with what he said overall.