Key-indicator analysis, the Chinese virus and the climate scam

By Christopher Monckton of Brenchley

Models! Dontcha just wish your taxes didn’t have to pay for them?

First there was the Imperial College model that predicted 500,000 deaths in the UK and 40 million worldwide from the Chinese virus in the absence of control measures, by the end of this year. Control measures were introduced in the worst-affected countries, so we shall never know how credible that prediction was.

Then, in the other direction, there was the model from the Institute for Health Metrics and Evaluation, which had originally predicted 200,000 deaths in the USA, of which 55,000 have occurred at the time of writing.

On April 4, my good friend Willis Eschenbach, who has an enviable facility with and interest in data, published some predictions from the IHME model for how many people would have died of the infection in the four months to August 4 this year.

Willis pointed out that “The IHME model is … not worth too much trust – it’s been wrong too many times … The model historically has predicted numbers that were too high.”

Just over three weeks have passed since Willis got the model to make its predictions. He wrote: “The latest incarnation of the model is predicting 81,766 COVID-19 deaths in the US by August 4, 2020. That’s down from 93,000 in the previous incarnation of the model.”

By April 4, there had been 10,384 deaths in the United States. To yesterday, just 23 days later later, there had been 56,797 such deaths, a five-and-a-half-fold increase, giving a mean daily compound growth rate of 7.7% in deaths.

If that growth rate were to persist for just five days, there would be more than 82,000 dead in the U.S. alone, a whole three months before the model’s due date of August 4.  Fortunately, the daily growth rate in deaths in the U.S. averaged over the past week is down to 4.1% and will be likely to fall further. But even if it falls fast enough to average little more than 0.35% over the 103 days from today to August 4, there will indeed be 81,766 U.S. deaths by then.

At present, though, the daily growth rate in active cases is not falling much, which means that in two or three weeks the daily growth rate in deaths will not be falling much either.

Willis also looked at Italy. On April 4, there had been 15,362 deaths in Italy. The model predicted that this would rise to 20,300 deaths by August 4. In fact, that total was surpassed on April 13, just nine days after Willis wrote, with 20,465 deaths. By yesterday there had been 26,977 deaths in Italy. Lesson: there is no single reproduction rate. It varies from time to time and from place to place. Models do not capture such differences easily.

In Spain, there had been 11,947 deaths by April 4. The model predicted 19,200 deaths by August 4. That total was surpassed less than two weeks later, on April 17, with 19,478 deaths. By yesterday there had been 23,521 deaths in Spain. Same lesson.

Willis also looked at the model’s predictions for California, the world’s fifth-largest economy. There had been 289 deaths in the state by April 4. The model predicted 1783 deaths by August 4. Remarkably, that total was reached yesterday, April 27.

Lesson: in the early stages of a pandemic models are not a lot of use because there are insufficient data to inform them. The compound daily growth rates in cumulative cases and in cumulative deaths give a better indication than the models do. These are the key indicators.

As a policy advisor at 10 Downing Street, often asked to provide analysis of technical questions on which the “experts” were either divided or flat-out wrong, I would look for the key indicators – never more than two or three – and make my recommendations based on them. One has to be ruthlessly dispassionate, and the use of key indicators is a great help with that, because it is much easier to see when someone is tampering with those than when a modeller is tweaking a few parameters in his model to achieve whatever result is most profitable to him.

Why is key-indicator analysis so important? The reason is simple. If governments had been aware that in the early stages of a pandemic the growth rate in cumulative cases and thus in deaths is near-strictly exponential, they would have realized a great deal sooner than they did that early control measures work a great deal better than late ones, saving lives, buying time and very greatly reducing the eventual economic cost.

We are now passing into an opposite problem. Now that the daily growth rates in active cases and in deaths are declining, and now that it is known that only over-60s with comorbidities are at appreciable risk, on the basis of those key indicators lockdowns can be cautiously dismantled, beginning at once.

But governments are still not learning from the key indicators, so some – such as the UK, which has been spectacularly behind the curve at every stage – still refuse to countenance relaxation of the lockdowns, or even to announce what their plan is.

Mr Trump has sketched out a plan: Mr Johnson has not. The British people, rightly, are feeling left out of the loop and are becoming impatient. Travel increased 5% last week compared with the previous week. It will increase again the next time we see the sun.

Certainly, as the Hokkaido example demonstrates, ending lockdowns prematurely or precipitately can lead to a renewed spike in infections, requiring a second and fiercer lockdown. But proper attention to the key indicators day by day, and far less mucking about with models, will lead governments to better and timelier decision-making.

One can apply the same key-indicators analysis to the climate question.

First, define the question: How much warming will a doubling of CO2 concentration eventually cause?

Next, find the key indicators. They are no more difficult to find than they are in a pandemic.

  1. How much warming has actually been measured to occur up to a given date? From 1850-2011, the year to which data were updated for IPCC’s latest Assessment Report, just 0.75 degrees’ warming had occurred (HadCRUT4).
  2. How many Watts per square meter of manmade radiative forcing drove the warming up to that date? Up to 2011 there had been about 2.5 Watts per square meter of anthropogenic forcing (IPCC 2013, Fig. SPM.5), from which the radiative imbalance of 0.6 Watts per square meter (Smith 2015) must be deducted, making 1.9.
  3. What is the best estimate of the forcing in response to doubled CO2? We can’t measure that, so we’re forced to rely on models. But it’s about 3.45 Watts per square meter (Andrews et al. 2011).

Just three key indicators. The warming to be expected from doubled CO2 is simply the product of the 0.75 degrees’ warming from 1850 to 2011 and the ratio of the 3.45 Watts per square meter CO2 forcing to the realized anthropogenic forcing of 1.9 Watts per square meter. And that’s about 1.4 degrees. The method is described in Lewis & Curry (2014).

One could argue that there has been quite a bit of warming since 2011, but one must also allow for more forcing since then as well. One could push up the equilibrium sensitivity to CO2 and make it around 1.5-1.6 K (Lewis & Curry 2018).

But the point is that with this simple analysis based on key indicators we are very likely to be somewhere inside the ballpark. But just look at the various profitable predictions of global warming made by the climate models:

The two scales –upper for doubled CO2, lower one for warming from 1850-2011 – are aligned to each other so that they both start at zero and so that 3.45 Watts per square meter of CO2 forcing is directly above the 2.5 Watts per square meter of radiative forcing to 2011.

Here’s how it works. We know how much warming would have been caused by 2011 if all of the 2.5 Watts per square meter of manmade forcing to that date had come through. It is the product of the 0.75 K warming to that date (the blue arrow) and the ratio of that 2.5 Watts per square meter total forcing to the realized forcing of 1.9 Watts per square meter: i.e., about 1 degree. Following the green arrow shows that 1 degree of warming to 2011 is equivalent to 1.4 degrees of warming in response to CO2 doubling.

But just look at the predictions made by the wretched models. In 1990 IPCC, ignoring the importance of the leading indicators, predicted 3 degrees’ equilibrium warming; the CMIP5 models predicted 3.35 degrees; and the CMIP6 models predict 4.1 degrees, with an interval of 3 to a remarkable 5.2 degrees. All of these predictions are manifestly excessive. They are two to four times too big.

One can also calculate how much warming would have been observed by 2011 if each of these three wild predictions had been correct, simply by following the dotted arrows. Only 0.75 degrees of warming had been observed by 2011, but if the models’ predictions of equilibrium warming in response doubled CO2 were correct the observed warming by now would have been somewhere between 1.7 and 2.25 degrees.

And it wasn’t. So we know the models are running hot.

We reached that conclusion simply by analysing the key indicators. Of course there are uncertainties in the climate data, just as there are with the pandemic. But on the basis of this simple calculation there is just not going to be anything like enough global warming caused by us over the 150 years or so that it will take to feel the eventual warming from doubled CO2 at the present rate of increase in concentration to make it worthwhile to do anything at all to make global warming go away. There is a pandemic emergency, but there is no climate emergency.

Instead, let the trees and plants thrive on the extra CO2. What a pretty paradox it is that those who call themselves “green” are so viscerally opposed to our returning to the atmosphere some insignificant and harmless fraction of the CO2 that once resided there, for it is visibly greening the Earth.

Or is it that the Greens – the traffic-light tendency – are simply too yellow to admit they’re really Reds?

Fig. 1. Mean compound daily growth rates in estimated active cases of COVID-19 for the world excluding China (red) and for several individual nations averaged over the successive seven-day periods ending on all dates from April 1 to April 27, 2020.

Fig. 2. Mean compound daily growth rates in cumulative COVID-19 deaths for the world excluding China (red) and for several individual nations averaged over the successive seven-day periods ending on all dates from April 8 to April 26, 2020.

149 thoughts on “Key-indicator analysis, the Chinese virus and the climate scam

    • Yes, MoB returns once more to the subject dear to our hearts!
      We ought not to worry about “returning to the atmosphere some insignificant and harmless fraction of the CO² that once resided there”. How true, but we should worry instead about the significant fraction of CO² that every day is sequestered away, locked up into calcium carbonate by sea creatures, destined to be imprisoned into limestone rocks for millions of years. CO² is a precious and rare resource in the atmosphere, and those who seek to reduce it even further are ignorant fools. Worse than that, they are dangerous nihilists. We can but hope that some good will come out of the real existential crisis caused by the coronavirus panic, and that the Michael Moore “green energy” exposure of mindless forest destruction will increasingly diminish government’s support for those fatuous green energy projects around the World.

      • By April 4, there had been 10,384 deaths in the United States. To yesterday, just 23 days later later, there had been 56,797 such deaths, a five-and-a-half-fold increase, giving a mean daily compound growth rate of 7.7% in deaths.

        If that growth rate were to persist for just five days, there would be more than 82,000 dead in the U.S. alone, a whole three months before the model’s due date of August 4.

        More inept pseudo science for the Baron of bunkum .

        In the last 23d US fatalities have gone from a steep rise of 12d to a steep decline for 12d. Of course this cannot be seen on his uninformative spaghetti graphs of the magic metric he thinks world leaders should be following.

        A quick look at unfiltered daily fatalities shows thin instantly.
        https://climategrog.files.wordpress.com/2020/04/2019-ncov-log-fatality-growth-us-it.png

        It is then obvious that the suggestion “If that growth rate were to persist for ….” is so banal and pointless he may as well be writing for the IPCC.

        At present, though, the daily growth rate in active cases is not falling much, which means that in two or three weeks the daily growth rate in deaths will not be falling much either.

        Fortunately, the daily growth rate in deaths in the U.S. averaged over the past week is down to 4.1% and will be likely to fall further.

        The daily growth rate as calculated by CofB is simply getting smaller because it is comparing to an ever growing historical cumulative total. That is why it is so uninformative. This figure will just slowly asymptote towards zero and averages out any changes that we may be hoping to see to inform about where we are going or what effect any policy changes make.

        Added to that he also applies a sloppy running average with turns a glitch in the data into a week long plateau ( see Taiwan and US in today’s death plot ).

        CofB insists on posting this bunkum day after days in the obstinate refusal to see that he has done the exact opposite of what you need to do if you want to detect short term changes to inform policy decisions: he has integrated instead of differentiated.

        By way of comparison here is a graph of the rate of change of daily cases in Italy.
        https://climategrog.files.wordpress.com/2020/04/2019-ncov-weekly-projection-diff-italy.png

        Here we can clearly see the effect of confinement rules and can now watch for any increase in the rate of change as rules are relaxed. Oddly there is not sign of that increase yet, just a perturbation of the usual week cycle.

        I can’t even be bothered to read the rest of his inept musings, I have other things to do today.

        Finally I’m sure we are all very appreciative that he has finally decided to take the advice I have been giving since his first post on this and is now using non lossy PNG format for this graphs which are now SO much clearer and the legend is at last legible. Thank you. Don’t mention it.

          • Adding: In the US Hospitals who claim the China Virus as a cause of death add 15% more compensation. Pneumonia Deaths are down 50% or better due to push to Covid-19 deaths.

          • Yes, it’s rather monotonous. It’s a shame, as the collective Greg’s, (two or three at least) make otherwise good contributions.

            The steady strain and insights are appreciated in these trying times.

            Bravo Zulu CoB!

          • Don’t whine.

            It’s not a whine you can hear , it’s wince. At least we can read your graphs now. That’s a great improvement.

            But proper attention to the key indicators day by day, and far less mucking about with models, will lead governments to better and timelier decision-making.

            You were unable to tell us how we could detect the effect of confinement from your “key indicator” graphs. It follows directly that you will not be able to tell us in a “timely” manner when things are going too quickly in the other direction.

            I have provided a “key indicator” which clearly shows the break off from near exponential rise to a slow decline as a result of restrictions in Italy . If there is an upturn from the mild de-confinement they have done so far this will be apparent within a few days of it happening.

            https://climategrog.files.wordpress.com/2020/04/2019-ncov-weekly-filter-italy-1.png

            After filtering out the weekly cycle, we see that the rate of *change* in daily cases has moved a little nearer to the constant new cases line. Nothing to get upset about. Time to free up more than kiddy’s clothe shops and bookshops.

            Italy seems to have fairly consistent data and it once again playing crash test dummy for the western nations. We should be watching and learning.

        • CofB could save us a lot of time by taking as a reasonable fit the Gaussian Normal Distribution of beloved of statisticians. If the fit is credible we could arrive at, for each country, just three numbers (the cumulative value, the date of the median value and the standard deviation) rather a spilt bowl of technicolour spaghetti.

          For England the “total number of confirmed positive cases” (whatever that means) [1] as of 28th April 2020 yields figures of around:
          Asymptotic cumulative number: 120000
          Date of median : 7th April
          Standard deviation (σ): 11 days.
          Hence the cumulative total d days after the 7th April is given roughly by 60000(1+erf(d/(σ√2))). The daily new case figure is the time derivative of that, which recovers the Normal Distribution, peaking at around 4000 day around 7th April. Notice that near the median the cumulative total is growing linearly, not exponentially, because the daily new case figure has peaked out. (Journalists don’t show any comprehension of this.)

          In short, as of today (29th) we are 2σ past the peak and by VE Day we shall be 3σ. Th politicians, newspapers and purveyors of vaccines, masks and assorted snake-oil will have to work hard to keep this scare going against the forces of McD/KFC return-to-eat, not to mention Minnesotans For Global Warming[2].

          The value for σ is very useful as it is presumably directly related to the time taken for virus to “go through” most of the people it is ever going to infect. A comparison of this value between different countries might be interesting.
          In principle one could do the same for the other countries rather than drawing spaghetti with a rather obvious asymptotic behaviour. Do cultural differences in “personal space” contribute? Does mountain life prevent epidemics compared to the metropolitan urban life?

          All the “compound rate of rise”, variable “time to double” and waffle about “if that growth rate were to persist for just N days” obscures rather than elucidates the key factors: time of peak, value of median.

          As Steven Mosher points out, a Gompertz curve adds in one extra parameter (an asymmetry factor). It may be that a Gompertz curve will fit these data better as more comes in but I can’t be bothered to work out the Gompertz asymmetry factor for the England data let alone even get a feel for its uncertainty. In the meantime a more important and highly uncertain issue is whether the Ferguson Twin Peaks model has been adequately tweaked to fit the data so far available for this year’s outbreak. If population density and availability of mass transport is a significant feature of the model, then would it be practicable to modulate lockdown policy according to population density? This would appease victims of home arrest in Montana and Derbyshire at the expense of continued restrictions in New York and London, but might prompt a flight for the hills!
          [1] https://coronavirus.data.gov.uk/
          [2] https://www.youtube.com/watch?v=WMqc7PCJ-nc

  1. You should stick to climate issues.
    The lockdowns did not work. The virus spread wildly regardless.
    The health care systems in first world nations were perfectly capable of handling the contagion without anything more than stern warnings to wash your hands, wear masks if you can, socially distance reasonably, if you are sick, stay home, if you are vulnerable stay isolated. If you are seriously sick, seek medical care.
    But Lord Monckton backstopped the stupidity of of doing hard lockdowns with economic suicide as the form of virus control. Now he is complaining that governments are not opening up fast enough and it is costing money. Never happy. Governments have to be “adults” and act “responsibly” and I forgot what he said about me in the other thread, but it basically said that I was the one not acting responsibly when I claimed we should never have closed the economy by dictate and that we should reopen already.
    The problem with Lord Monckton arguing I was the one doing things that were irrational the truth is that this is the first time in history where carte blanche economic suicide has been tried as a method to prevent a contagion. The only other times in history where something so stupid was ever tried is when societies would sacrifice people, children, virgins and so forth to the “gods” in order to bring good fortunes. So, who were the adults in the room? The people who have studied and seen contagions come and go in times past and understand that the best path forward is to quarantine the sick, isolate the vulnerable, responsibly socially distance, be cleaner, and wear masks? Or the people who overreacted to the threat and caused far more harm than the benefits they could possibly have gained?
    2.2 million Americans could have died on the largest highest do nothing models that you are complaining about and should have known were suspect at best. The minimum cost to America for those 2.2 million lives had to be economic and total suicide. But the current numbers are, $3 trillion in direct spending on the backs of children who are for the most part invulnerable to the chinese kung flu, $5.6 trillion, most likely more, in lost economic output. Some of that might not have been averted, but the vast majority of it would have been. Let us just consider it $4 trillion in lost economic output. The Federal government will now lose $1.5 trillion dollars from that lost economic output. So, $8.5 trillion dollars divided by the massive 2.2 million old and sick and already near death the virus threatened… $3,850,000 was the absolute minimum cost per life that was threatened if you believed, (does anyone believe?), the initial models. As you avered above however, it was not really 2.2 million, but maybe 200,000. That comes out to burning only $42,500,000 per life threatened. That does not include those that were most likely to die and have died as a result of the virus even though we took these actions.
    The fact that many of these deaths likely were not due to but simply died with the virus means that that $42,500,000 is actually far greater per life threatened. We are probably actually talking about $100,000,000 to $300,000,000 per actually averted to a future date when the virus will still finally get them. As viruses tend to do. The only reason 290,000,000 Americans do not catch the flu each year is because once you have a strain of the virus, you can typically expect a couple years of immunity to it and others that are close enough.
    So, who were the adults? You and the government shut down people? Or the people who rationally figured that the best response was the same response we took for every other contagion through out history?
    China is the happiest today as it has ever been. It has convinced the world to shut down and lay in the fetal position while its hacks in academia and the media keep creating and spreading its propaganda to keep us in the fetal position for as long as possible. And you were instrumental in their efforts.

      • Not really. They were reliant on exports to gain capital to build their infrastructure. The infrastructure is built. They have huge empty cities waiting to be filled with workers. Why? They have vast reservoirs of raw materials waiting to be consumed. Why? They do not need us to survive. They just used us to build up. It is funny how easy it is to manipulate people. As if they cannot produce things for themselves. Like weapons of war.

        • Chinese (perhaps even Asian) thinking is fundamentally different from Western thinking. I can’t begin to list the differences. Let me just say this ‘You know nothing, Jon Snow’

          • Indeed, and China recently rebuilt the entire railroad infrastructure from China, through Russia, all the way to Lithuania at the Chinese Government’s expense.Upgrading thousands of miles of ostensibly Russian transport network. Why? So that (according to CCP officials) a reliable and fast alternative to ad hoc air transport for Chinese Goods will be able to reach Europe in around 6 days or less. The first trainload of 200 tonnes of cargo left China on 6th April, from the new terminal facility, arriving in the Baltic States on 12th April. The cargo was mostly medical supplies such as disposable masks, gowns, and gloves etc., much needed in Europe at this time. Up to 2 trains are planned to depart each day, and with international agreement of Russia, Lithuania, Poland, Denmark, and others; China Post are set to undercut many German based air transport networks such as DHL etc. The air transport restrictions imposed largely by European nations upon China, prompted these actions by the CCP and China Post. So now German business has lost control of a substantial part of the lucrative transport of Chinese manufactured goods. That’s another nail in the coffin of ubiquitous Brussels EU control too, because those China Post agreements, are particularly with individual reciprocal Postal businesses, and not arranged on a Europe wide basis by the “EU Commission”. We shall no doubt see more and more Russian businesses competing in Europe with their own manufactured products also. I can’t help thinking that Putin & Xi have pulled off a fantastic commercial coup, just at the time when the entire EU as a supranational control body is on the point of disintegration. Why, it’s almost as if the mysterious coronavirus outbreak was part of that plan? Oh, suspicious me!

          • Jack
            I don’t really care what you call the government system. I decide what is good or bad about it by the results. The railway situation was probably part of a 5 year plan maybe 10 years ago. They can do this sort of stuff without environmentalist interference.
            As to the Covid situation, it was just a monumental stuff-up. The Chinese are good at some things and really horrendous at others. The problem is the system. Its all top-down and if you don’t follow the chain of command you can get really f*cked up.
            Xi would be mightily upset because no-one in China would call him a liar or an incompetent. It’s just not the way a country with Confucian roots thinks. He doesn’t really understand Western thinking.
            He’d be just like a young girl being called a pr!ck-teaser. No-one has ever spoken that way to her before.

        • Beyond what has already been said the standing of China in the world is massively diminished and you are going to need hundreds of “Belt and Road initiatives” for other countries to forget.
          They have probably lost any chance to bring Taiwan back into China and president Xi is openly called a liar by the world … I am sure they are really happy with those outcomes.

          • You misunderstand the Chinese.

            They really don’t give a flying f*** what westerners think of them, inferior insects that we are. They may (or may not) have been playing us like a violin all this time but they are — or at least they believe they are — leading the orchestra and we are dancing to their tune.

            Think about it.

            “ China recently rebuilt the entire railroad infrastructure from China, through Russia, all the way to Lithuania at the Chinese Government’s expense.Upgrading thousands of miles of ostensibly Russian transport network. Why? So that (according to CCP officials) a reliable and fast alternative to ad hoc air transport for Chinese Goods will be able to reach Europe in around 6 days or less.”

            And what else can railways transport? Soldiers, perhaps? Tanks? Artillery? Just thinking.

          • Using railways to transport armed forces, doesn’t work too well, if you’re up against an opponent who has GPS guided munitions.
            Once you reach that river, you find there’s no bridge anymore.
            So, who’s planning on shipping a few armies around the place?

    • I read your first sentence and then gave up.

      I’m not sure how many other people feel the same way that I do, but I would suggest that your your writing effort is largely wasted. You do seem eager to criticize others. Should you be open to some constructive criticism, then please read the following and practice it to improve your writing to make it more readable.

      https://writingcenter.unc.edu/tips-and-tools/paragraphs/

        • Paragraphs would help, but only for composition attributes. D- for attitude. C+ for content…actually agree with a few points but wasn’t able to quite read it all as it all ran together without any paragraph breaks. It’s not like there is a lack of space here for inserting paragraphs. Note to self…

    • Astonerii writes:

      “The lockdowns did not work. The virus spread wildly regardless.”

      Without going into Astonerii’s other discussions deeper in the post, let us try and compare a large flightless bird with a small flightless bird.

      New Zealand: Home of hobbits, rugby, and suppression of freedoms. When the world realised that WHO couldn’t be trusted they went for the full ‘Level 4’ lock down.

      Australia: Home of bogans, dropbears and an entire eco system that wants to actively kill you. Australia took a different approach. International and then domestic travel were locked down and then various degrees of Social Distancing (side note – This WILL be word of the year next time the dictionaries start publishing. Prove me wrong) on a state by state bias.

      Victoria, usually argued to be the most Marxist of all Australian states, went pretty hard on its lockdowns, happily using the police to bully people driving alone in their cars or playing golf solo. NT, the more sparsely populated region on Australia, did so little that my contacts in Alice tell me they are still playing club tennis. Where I live I am still working from work and apart from the fact I haven’t seen my parents in about two months, can’t play sport, and can’t go out on a Friday night it is pretty much same old same old. People still casually walk the streets, the skate park I drive past on way home from work is still filled with youth types, and many ‘non essential’ shops are still open for causal browsing.

      Claim being made? New Zealand when harsher lockdown than Australia by a significant margin.

      However, let us look at some of the stats, like say cases per capita and deaths per capita.

      New Zealand exceeds Australia in both.

      More restrictions. Worse result.

      Yes, we are comparing large flightless birds to small flightless birds, but statistically New Zealand has failed to Australia.

      Bemusingly New Zealand also now claims to have ‘eliminated’ the virus, despite the fact their raw ‘new cases’ for recent days is more than Australia. Guess ‘eliminated’ means different thing if you are a government employee.

      • Craig,
        As far as I can see ‘raw new cases’ are lower in NZ than in Australia. Over the last week in NZ
        there were 26 new cases whereas in Australia over the same period there were 93 new cases.
        On the positive side both countries are well on the way to getting rid of COVID19 which is evidence that lockdowns work. The one in NZ was legally more stringent while in Australia more businesses could open but in fact most had shut down because people were staying at home so the net effect was similar in both countries.

        • Ardern will say and do anything with an election coming up this year to make people feel “safe” and that the Govn’t did something to “save lives”.

        • Raw cases are not a useful metric. As Craig pointed out, on a per million population basis, NZ is worse off than Australia. Cases per million: Australia, 264, NZ, 306. Deaths per million, Australia, 3, NZ 4. Per worldometer.com as of this posting.

        • On the positive side both countries are well on the way to getting rid of COVID19 which is evidence that lockdowns work.

          Unless both countries choose to remain practically cut off from the rest of the world then they’d better get used to perpetual lockdowns and/or constant invasive government surveillance.

          COVID-19 isn’t going away and it isn’t going to leave them alone. Most likely they have simply postponed the start their pandemics.

        • Population Kiwiland 5 million
          Population Land of Oz 25 million
          26 new cases in Kiwi 5.2/million popln
          93 new cases in Oz 3.7/million popln

          So was more stringent lockdown in NZ warranted ?
          The luvvies praise Saint Jacinda while ignoring the fact that other approaches worked just as well or better

      • Aus and NZ due to being islands with no land borders have traditionally good and strict quarantine. Additionally, I think chinese new year coinciding with Australia Day long weekend and both just before school starting meant that 100,000 to 200,000 chinese students and families were still in China prior to lockdown saved us from a broad initial spread. The spread into Australia mostly came from cruise ships and the USA and not direct from China.
        Whether the initial spread was broad ( say chinese students going to universities throughout the country) or focused ( say tourists/cruise destinations or industrial/ business hubs ) , may be a contributor to the different rates of infection in various countries.
        There may have been chinese tourists in aspen pre lockdown but not many in fly over states.

      • “Australia: Home of bogans, dropbears and an entire eco system that wants to actively kill you.”

        First, that is true and funny. Well done.
        Second, Thank you! That has always been my impression of Australia. It amazes me so many people have managed to survive when there is so much in Aus. that seems to not want people to live.

        I have long thought Australia is not for the faint of heart and Aussies are, indeed, a brave and hardy people.

        • “KcTaz April 29, 2020 at 10:28 am

          I have long thought Australia is not for the faint of heart and Aussies are, indeed, a brave and hardy people.”

          Now full of snowflakes and latte drinkers who think cutting back Australian CO2 will save the planet.

    • Completely agree. This virus cannot be stopped and could never have been stopped. The most irritating thing is that we knew from the Diamond Princess dataset and from early Italian hospital data what the mortality of infections was. And the older your population the higher the average mortality. Very sensitive to age distributions. So UK its about 0.6%, USA about 0.5%, Italy about 0.8%, India about 0.2%.

      And from that information we could have made some very educated views on how infectious and widespread this was. Very early on. And that would have informed about the best strategy. Locking down does nothing except delay the spread. It CANNOT be stopped. The best would have been to do what Sweden has done.

      • Definitely NOT Sweden’s approach.
        Czechia has the same population, started about the same time and on the 29th of March Sweden were 19th and Czechia 20th on the worldometers site.
        Sweden are now 22nd with 1943 cases/M and 233 Deaths/M.
        Czechia are now 42nd with 701 cases/M and 21 Deaths/M.

        Princess Diamond does not represent any kind of national conditions with the Passengers locked up with both infectious passengers and staff and the infectious staff were serving the passengers.

        • March Sweden were 19th and Czechia 20th on the worldometers site.
          Sweden are now 22nd with 1943 cases/M and 233 Deaths/M.
          Czechia are now 42nd with 701 cases/M and 21 Deaths/M.

          Watch what happens when Czechia lifts its expensive lockdown in late May. There is no way Czechia can avoid the deaths it has postponed.

          Princess Diamond does not represent any kind of national conditions with the Passengers locked up with both infectious passengers and staff and the infectious staff were serving the passengers.

          All that plus a higher proportion of old and vulnerable than normal – yet the infection rate and death rate were nothing spectacular.

  2. Yes, it’s a signal to noise problem. It’s easy to get mislead by the bafflegab coming from both sides. There’s also the problem of innumerate people who can’t see the forest for the trees. They will ignore simple truths to defend their opinions with complicated crap.

    The wise are able to find something simple and tamper proof and hang their hat on that. My favorite figure for the current pandemic is excess deaths. If deaths are up 100% over the expected rate, it doesn’t matter much if people count them as related to the coronavirus or not. The total death rate is a lot harder to fudge or botch than any other figure related to the pandemic.

    Having said the above, a lot of people accuse China of outright lying. On the other hand, the Chinese members of the family call the Western media lazy for ignoring figures that are openly published in the Chinese media.

    • When sick and vulnerable people are stressed there are several negative events that can kill them. Are they covid-19 deaths?
      When people are unemployed and have no prospects for a future many of them do stupid things and those things deliberately kill them or bring them to death. Are they covid-19 deaths?
      Every year they estimate the number of deaths due to the flu. It varies year to year from 25,000 to 80,000. They do not count everyone who is infected with flu viruses like they do with covid-19. Instead the almost never actually do blood tests for the flu. Someone dies of a heart attack, they do not run a blood test to see if they have influenza A, B, C or D. They assign them a death certificate of heart failure. But what if. Just what if they tested every single person who dies in the United States of America for the flu when they die? Out of the other 2.5 million people who die every year, I would estimate that 15% of them die with a flu virus in their system. So, a year with 80,000 flu deaths would also have an additional 375,000 flu related deaths.
      I also think that this virus is very close to that 15% level. But I also think the virus counts are high, as New York City simply deemed almost 4,000 deaths as covid-19 related regardless of no evidence. So, we are basically at about 60,000 deaths right now. That comes out to about 9,000 actual covid-19 caused deaths and 51,000 died with covid-19 virus deaths. Which is much more likely than actually having every last person with the disease that died being caused by the disease. 80-90% of people with the virus show no symptoms. Yet 100% of deaths with the virus are caused by the virus? Not likely.

      • They might be deaths from Sky Diving thru boredom or perhaps they all watch TV for endless hours until they pass away. None of that matters the numbers are up deal with the fact CB gave.

        So perhaps the best argument your ilk could possibly run is that the lockdowns caused the increase, so now all you need to do is put a coherent argument together. Instead you play definition games like Nick Stokes does and it’s just as annoying because no-one is fooled.

        • The ONS weekly data for England and Wales suggests to the layman that one or two fewer teenagers per week are dieing in 2020, possibly because they are not outside doing stupid things in 2020 as in other years.

          It also suggests that under 45s are virtually unaffected. Despite a few sad and headline making exceptions.

          • At least that is an argument but it only deals with who isn’t in the numbers. The data posed by CB was the increased numbers because as he said that is a lot harder to fudge.

      • I agree. The effects of the lockdowns are going to be proved to be worse than a disease which targets the old, sick and fat. Economic disasters are the best way of producing depression and worse. The effects of these will evolve over the next 3-5 years, not the next few months. The politicians who ordered strict lockdowns are already backing and filling to avoid blame for the effects of the lockdowns. Expect a great deal of emphasis on ‘a disaster averted’ and ‘everything is OK because of what we did’. A lot of the negative comments to your post are from people who are self-justifying their own fearful reaction.

        NZ and Oz are irrelevant on a global scale. If people can be kept fearful enough, the lady with horse’s teeth will get reelected; if not, she is toast, because closing borders is economic suicide. Is she going to have all air and sea crews locked into their planes and ships? Alternatively, she can preside over a peaceful and green country of peasants who produce everything they ever need by themselves, and whose only view of the outside world is on the internet (until the machines fail, and then isolation will be complete. – a beautiful hobbit world without any plastic polution).

        I saw with my own eyes one of the last smallpox epidemics; children dead from measles; families that had seen multiple babies die of congenital syphilis, hospitals with perfect record of losing the mother, the baby or both, real dependence on the next harvest. And I think it would have been a blessing if my mother had died in one of the multiple episodes of pneumonia before her mind was totally gone.

    • If deaths are up 100% over the expected rate, it doesn’t matter much if people count them as related to the coronavirus or not.

      I agree but, to add to that, I’d wait until the end of the year before reaching a firm conclusion. This should tell us whether the pandemic simply accelerated the deaths of already very sick people or was responsible for deaths that wouldn’t have happened that year.

    • “… My favorite figure for the current pandemic is excess deaths. If deaths are up 100% over the expected rate, it doesn’t matter much if people count them as related to the coronavirus or not. The total death rate is a lot harder to fudge or botch than any other figure related to the pandemic. …”

      Have a look at 12:36 mark Bob.

        • I watched almost the whole thing (up to when he started showing pictures of the viewers). What I get from it is evidence of the large number of asymptomatic cases. There is much evidence of this but, for some reason, people find a way to discount it. example

          It could be that the infection rate from this coronavirus is hugely underestimated. That means the death rate for those infected is actually rather low. Of course, the actual excess deaths are rather high. That is explainable if the actual infection rate is huge.

          As the video points out, asymptomatic people are infectious whether or not they go on later to develop symptoms. That means, for many countries, the lockdown was imposed long after the horse had left the stable.

  3. Will agree that deaths are creeping up and may pay pass whatever the IHME model is predicting today may eventually be surpassed, but…. I doubt the tally to be a clean, accurate set.

    In the US, and I did look as to whether there’s a financial incentive for a death to be counted as involving the WuFlu. One thing I found was that hospitals will be reimbursed by the feds at Medicaid rates for treatment. Not enough to live on, but it’s a fool that doesn’t stop to pick up a bit of change lying on the ground.

    Long as they’ve something to sanitize it with.

    • Even if we play your game and they padded it by some incredible amount lets say 20% the US will still get close to that or possibly even pass it. To put 20% in perspective that is around 12,000 as a padded raw tally. It also leaves out there is an reverse argument the number is actually under-counted currently.

      The whole lock down is a different argument which boils down to how much is a life worth both in money and freedoms and why it occurred. However I would think that the whole numbers are padded argument left the paddock and bolted a while ago. I think many started the argument because it looked easy but as the numbers come up it just looks what it is a stupid argument.

      • There’s always a reverse argument and when the post-mortem studies are done on what exactly the true count from the WuFlu was, there’ll be vigorous push-back at the findings. Too much face at stake, what with the economic and health consequences of the shut-down response.

        Don’t count deaths, nor did I make the decision to reimburse US hospitals for a WuFlu death, but I can point to a financial incentive for the latter to influence the former. Is it insignificant, or greater than what you consider an “incredible” amount?

        Don’t know and doubt you do either, but you’re always free to post a link supporting your feelings on the issue.

        • It’s an esoteric argument that someone sometime in the future will make some finding … they call it history.

  4. “Just three key indicators. The warming to be expected from doubled CO2 is simply the product of the 0.75 degrees’ warming from 1850 to 2011 and the ratio of the 3.45 Watts per square meter CO2 forcing to the realized anthropogenic forcing of 1.9 Watts per square meter. And that’s about 1.4 degrees. The method is described in Lewis & Curry (2014).

    One could argue that there has been quite a bit of warming since 2011, but one must also allow for more forcing since then as well. One could push up the equilibrium sensitivity to CO2 and make it around 1.5-1.6 K (Lewis & Curry 2018)”

    The relevance of all that math about climate sensitivity depends on the idea that the proposed climate action will change the rate of warming although there is no evidence to support that assumption. The real issue here is climate action not climate change.

    Three links below

    https://tambonthongchai.com/2018/12/14/climateaction/

    https://tambonthongchai.com/2018/12/19/co2responsiveness/

    https://tambonthongchai.com/2020/03/23/anti-fossil-fuel-activism-disguised-as-climate-science/

  5. Lesson to be learned – from the first part of this article – Statistics can NEVER be used to predict. They can only be used to understand what DID happen, not what will happen. Any model that uses statistics as its justification for prediction will NEVER be accurate. Models for disease spread or climate change, makes no difference. Doomed to fail.

    • “Any model that uses statistics as its justification for prediction will NEVER be accurate.”

      wrong.

      wrong

      Statistical prediction is not judged by accuracy it is judge by skill or the error of prediction.
      This is intimately tied to the USE. For example, a political poll can suggest you
      are weak in District X, and of course yu use that to spend money in district X.
      Or, Image recognition. Pure statistics. Every day I go into work the camera guesses
      correctly that it’s me. Now, sometimes the model is wrong. Like the fraud detection model
      that Visa uses. When I land in Korea and use my card for the first time, I get a notice.
      “Was this your charge steve?” The model used statistics to predict the probability of fraud.
      They contact me. they were wrong, but the model was useful.
      because its false alarm rate is low.
      Or that statistical model in the fighter jet. It is tracking a target. Based on a Model of
      vehicle kinematics it predicts where the next signal will arrive from.

      https://en.wikipedia.org/wiki/Kalman_filter

      Stats and physics. A model. that makes predictions that are GOOD ENGOUGH.
      good enough to kill the bad guy. he won’t survive to complain that you used a model and stats.

      Ever buy fire insurance?

        • life insurance?
          earthquake insurance?
          extended warranty?

          The argument is simple.
          Statistics work to predict the future
          ‘work’ means they are useful.
          use is contingent upon the circumstances and your goals.

          Note that you did not respond to the argument, you found fault with one example.
          Now ask yourself WHY it is required

          • No fire insurance. No life insurance. No earthquake, flood, or cyclone insurance. So far, so good. Seems as though I have predicted the future well enough so far. Useful enough?

          • The statistics used by insurance companies can be validated within a few months time. This gives the companies confidence to keep using them.
            Unlike predictions made for things that won’t happen for 50 to 100 years.

            Beyond that such statistics are inherently backwards looking. As long as the future is the same as the past, they work. But the instant something new is introduced such statistics fail, big time.

            That’s why automotive insurance companies are refunding premiums right now.

          • ‘The statistics used by insurance companies can be validated within a few months time.’

            Thank you, for shooting down that latest false equivalency.

      • “Stats and physics. A model. that makes predictions that are GOOD ENGOUGH.” (sic)

        Ever buy spell checker insurance?

    • statistics can NEVER be used to predict. They can only be used to understand what DID happen, not what will happen.

      I suggest you never drive in a road vehicle, travel by train or take and aircraft then: Engineering is done using failure statistics, and if they don’t predict correctly, cars will fall apart, aircraft crash…

      And indeed the whole physical world is only a statistical probability emerging out of quantum mechanics, It could all vanish in a puff of green smoke. Its just rather unlikely.

      No, the lesson Christopher teaches, is how complex models with many unknowns, but whose shape is generally known, can be useful if you can monitor the output that concerns you. In terms of his virus analysis that works, but I am less sanguine about climate change. There is no real evidence that we even have the right shape of the model.
      For all we know the modest 20th century rise in temperature had nothing whatever to do with carbon sensitivity, it being mere coincidence that at that time CO2 was rising – but so were many other things – air transport urban development deforestation…

      When did you stop beating your wife? Before we attempt to answer leading questions like ‘what is the climate sensitivity with respect to carbon dioxide?’ it behoves us to ask whether or not carbon dioxide plays any significant role in global climate AT ALL..

      Correlation is coincidence, not necessarily causation, and the correlation between global temperatures and CO2 is very, very ,very poor over even the last 100 years let alone the last few millennia. It is patently obvious to paleogeoligists that huge climate shifts have taken place independently of carbon dioxide concentrations, which if they are correlated at all, lag the climate changes.

      • I’m still waiting to see what SUVs were popular during the Medieval Warm Period. Apparently the Romans had them too, during Hadrian’s time. Two HP bio-mass fueled chariots? /sarc

  6. Death rate of people <60y is probably 0.0008 (based on 1% CFR and 8% of total COVID-19 deaths in UK).

    For herd immunity:

    50.5 million <60y x0.7 x0.0008 = 28,280 deaths

    Not talking about hospitalization numbers.

    • Ron, from what I saw here on discussion, you have most realistic and correct information and opinions about Covid-19.
      For longer time I’m thinking about one thing. Wearing face mask helps for sure with spreading virus. But side effect of face masks could be that it is increasing of asymptomatic number of infections by one or two orders.
      I saw tests where it was measured how much viruses will come through face mask. Result was around 1000 times less.
      So in real life if all people are wearing face masks, they will all come into contact with virus, but all under minimal dose for infection and without ability to spread virus.
      So under such circumstances even hospitalized cases are lighter and there is less death cases overall because infection dose is generally smaller.

      • Thanks for the compliment but I just try to look unbiased on the numbers and guess for a best-case and worst-case scenario. South Korea is a good place to look at because their strategy of containment would not work if there would be a lot of undetected cases. I read somewhere it has to be >10%.

        The example of Singapore told us that this might be adequate.

        To answer your question: nobody knows. The measured viral load of symptomatic and asymptomatic patients did not differ in the few studies that were done on this topic and that would argue against the hypothesis that the initial viral exposure determines the severity of the symptoms and other factors are at play.

        The number of particles necessary to infect a patient and trigger the disease is also unknown. I can only guess that if one needs a specific load – as even with HIV otherwise the innate immune system fights of the virus before it can spread in the body – decreasing the particles one is exposed to would not result in more asymptomatic cases but indeed in less transmissions.
        This low dose exposure would not be sufficient to trigger the generation of antibodies but I don’t know if it would give somebody an advantage in case of an exposure with a higher load. I’m not an immunologist.

      • Asymptomatic is a very tricky issue you need to be careful about did you check for symptoms or did you “ask” if the person has symptoms. The problem with asking has shown up in both Wuhan and in US homeless studies. Having covid19 is not just a condition it has a stigma and can have work/finance consequences and some will either deliberately or covertly “lie”. It can be a bit like asking someone if they have a sexually transmitted disease and expecting everyone to answer truthfully.

    • Hospital admissions is the critical number. Once you’ve reached your maximum, then the fun really starts.
      We’re seeing patients being trundled in ambulances, around New York, trying to find a hospital with a spare bed that can take them.

      • That’s right I just was too lazy to check for the numbers. 🙂

        Patients <65y make up 56.6%(!) of hospitalized patients even if you take only <50y it's still 25.5%. Too much if you let the virus go wild.

      • Adam,
        I have a hard time believing that ambulances are still trying to find beds for patients. The USS Comfort only had, I believe, 71 patients and it left NYC as it wasn’t needed. The Javitch Center hospital is closed. Healthcare professionals have been laid off for lack of patients because elective procedures are not being performed and even what would be called essential procedures aren’t, either. Whatever data you are using appears to be very out of date.

  7. There seems to be an effort to attribute any death to #19. I’ve read that it’s to the $ advantage of the health provider to claim #19 deaths over any others. If that’s true we have faulty data. I agree that we need to look at + or – total deaths to get a true picture if we can’t trust reporting/data. I’m betting it’s the same as any flu season (not comparing flu deaths, but overall deaths).

  8. Models – Climate Change and COVID

    I began my career when the introduction of computer models through science and technology seems to have take off in many direction. I was fortunate enough to meet and briefly interact within a technical setting with one of the most pragmatic geniuses I’ve ever met.

    Post- Teton Dam collapse I was fortunate to be in a rapidly changing field involving the earth and science. Designing and building infrastructure out of earth materials was dynamically growing with the use of IBM computers. While a the computer was a god send for those having perform all of the calculations with a calculator, or iteratively seek a solution that required scaling and directing forces to a solution.

    In my field Ralph B. Peck was a close the source of major advances in the field of soil mechanics and their application to solving real-world problems. Like answering how will the earth dam perform over the next 75 years of it’s design life? So he worked in the world where sometimes a hand-calculated solution to a problem would first be made on the back of an envelope, and quite often the solution was just fine. in a recent article in GEOSTRATA, answer to the questions hewas posed from an interview period covering 2002 to 2004 were presented.

    When queired whether “engineering judgement” was compatible with computers, he responded:

    “Computers can solve a lot of drudgery- They can solve problems quickly that we could barely solve in the past. But I still don’t think one should put a problem immediately on a computer without first making some kind of rough estimate as to what ‘s likely to happen or what the answer should be. If you can’t do that, I don;t really think you have any business trying to do it on a computer. If you don’t have a sense of what the answer ought to be, you’re at the mercy of this machines that can make big mistakes faster than any other way.”

    I believe we are suffering through a failure of competence with both climate change and COVID-19. The true geniuses will have to fight their way forward through the barrage of politicized science yet.

    We will make it!

    t phas

    • Excellent.

      I have some experience wit modeling, and I have seen that computer models do not have access to unknown unknowns. They are very good at doing math and running algorithms. But expecting a computer model to tell us what the climate is going to be in 10 or 50 or 100 years is precisely like randomly choosing a rock out of your garden, squeezing it with powerful tools, and expecting blood to come out of it. I think you can see how foolish that would be, and is.

    • ““Computers can solve a lot of drudgery- They can solve problems quickly that we could barely solve in the past. But I still don’t think one should put a problem immediately on a computer without first making some kind of rough estimate as to what ‘s likely to happen or what the answer should be. If you can’t do that, I don;t really think you have any business trying to do it on a computer. If you don’t have a sense of what the answer ought to be, you’re at the mercy of this machines that can make big mistakes faster than any other way.”

      Simple question.

      Its Feb 17th. The US has 68 cases and zero deaths.

      You are the head of operations for a NYC hospital.
      The CEO asks you.

      How should we prepare for this epidemic if it comes to New York. We have 0 cases

      using only information you what do you tell him?

      1. Hw many tests should yu have?
      2. How much PPE?
      3. How many patients should you expect and will yu have enough beds?
      4. How many ventilators.

      march 1st rolls around you get the very first case in New York,

      How do your projections change?

      1 case. March 1st.

      You can use pen and paper. Show your work

      Now, the head of operations is not a scientist but the boss expects him to use some math.
      Maybe pen and paper, maybe a spreadsheet, maybe a model, maybe a simulation.

      Should we prepare for 20000 hospitalizations? more or less? why.

      Show your work.

      Note I did not so for an estimate of body bags. Ice will suffice

      • Any statistician will tell you that one case isn’t enough to do any sort of statistical analysis. Perhaps a better question is whether you should order the entire city to shut down and destroy an economy the same size as a medium-sized country? Now let’s not talk about New York, which has had a severe case, but 99% of America, which as had almost no deaths. Should you shut down 99% of America because of an outlier?

        • As long as you are sure that the reasons why that outlier appeared do not translate to anywhere else in your country you can do business as usual of course.

          But if you look around many different countries that are not at all like New York City and find similar outcomes like Bergamo or Alsace Lorraine you should maybe think twice.

  9. “Lesson: in the early stages of a pandemic models are not a lot of use because there are insufficient data to inform them. The compound daily growth rates in cumulative cases and in cumulative deaths give a better indication than the models do. These are the key indicators.”

    the purpose of the model is to Predict from limited data the BURDEN on hospitals.

    To do that you have to start SOMEWHERE.

    So they started with deaths. Deaths from Wuhan,
    From this curve they then predicted deaths in other areas. you have to start somewhere.
    From deaths they derive ICU and ventiliator burden, and hospital burden.

    Later they tried to adjust deaths based on assumptions about lockdown effectiveness

    The point is if you are trying to plan for an emergency you need SOME KIND OF ESTIMATE.

    Waiting until the last minute won’t work. Kinda learned that with testing.

    So you have to plan. And plan with a safety margin. Just like in Airplane design.

    So. if you run a hospital you need to plan. There is no physics to tell you how the future will
    be. You need to estimate. That means a model. math. informed by data, but basically assumptions
    turned into math. Like your retirement plan. You estimate how much it takes to live. You make
    assumptions about inflation, about return on investment, and you make a decision. It will
    likely be wrong, either high or low. but you plan nevertheless.

    What’s needed is “better models” which best comes from an open iterative transparent process
    Mere criticism from the sidelines doesnt get you anywhere because every model is wrong.
    Some are useful and they become more useful when people make constructive improvements

    As for models

    here is one

    https://wattsupwiththat.com/2020/03/13/the-math-of-epidemics/

    “You can see why the Gompertz Curve is used to describe epidemics—it’s a very good fit to real-world epidemiological data. And because any given Gompertz Curve ends up at some maximum value that it doesn’t exceed, it also allows us to estimate the part of the curve that hasn’t happened yet. So far, there have been some 7,362 cases in South Korea. The Gompertz Curve estimates that the final total will be on the order of some 8,100 cases or so.

    Now, that’s not a hard number, of course. All kinds of things can happen to bend the curve either up or down. But it’s better than just making a blind guess.”

    current cases: 10,700

    “Although the uncertainty in this one is greater, it looks at present like the final total of deaths in South Korea will be on the order of one hundred, give or take.

    Conclusions

    On my planet at least, this is very good news. Deaths in China look like they will be on the order of 3,500 lives lost. Cases in South Korea are near to peaking. And although it’s early to do this kind of analysis on the number of deaths in South Korea, to date there have only been 60 deaths, and the best fit Gompertz Curve peaks out at a hundred deaths.”

    Current deaths: 244.

    Now, the point here is not to slag on Willis.

    he used a model. It was wrong.

    The next step would be to make that model better…

    or you can turn your focus to there modelers and forget how hard it is

    • So you have to plan. And plan with a safety margin. Just like in Airplane design.

      Nope. It just doesn’t seem like “Airplane design” at all. Not even close, really.

      So. if you run a hospital you need to plan. There is no physics to tell you how the future will be. You need to estimate. That means a model. math. informed by data, but basically assumptions
      turned into math.

      Yep, that’s more like it. Not like airplane design, but rather something pretty much akin to, “God exists.” Now we’re going to turn that faith into math and make it useful for humanity during a worldwide pandemic, the critical parameters about which we have little to no knowledge for input variables into our model. How do you even start coding that model based on faith? We did that and that plan didn’t really work out well did it?

      https://tinyurl.com/yaxyvrj5

      or you can turn your focus to there modelers and forget how hard it is

      What if we turn our focus to evaluating how successful (read: “accurate”) our models predicting the, e.g., hospital burden turned out to be?

      Then, perhaps going forward we can code a model that models how useful modeling models the pandemic of economic destruction modeling has caused to the most disadvantaged of the citizenry in the US and around the world because of faulty modeling (perhaps anyway, we can’t even really scientifically evaluate THAT proposition, because by definition doomsayer hypotheses CAN’T be nullified)? And this even before we model how successful the models modeled all the various result sets (hospital beds, deaths, infections, etc.) from which the policy maker’s decision criteria was formed in the first place?

      What say you? Should we use the various historical model results from past models to model the usefulness of any future models? What would you say the historic data from the old models in your current model suggest would be the proper course of action with regard to future modeling?

      What probability of future usefulness of new models would be had from the data of the old? How will you determine what went wrong with the old ones? How will you fix the new ones if you don’t know what went wrong with the old ones? How will you know that what affected the old ones (e.g., Trump sending Comfort to NY, etc.) will be available as a valid input variable at the next pandemic?

      • “Nope. It just doesn’t seem like “Airplane design” at all. Not even close, really.”

        What you dont think there are safety margins in aircraft design?

        Well lets take a problem from Aircraft design that I worked on and see how you would answer it.

        The issue is Crew system design.

        The problem is designing an ejection system that, works throughout the envelope of the aircraft
        Doesnt cost too much, doesnt weigh too much, doesnt cause TOO MUCH injury to the pilot
        ( like if you blow it out too fast you get flailing injuries) works across the spectrum
        of pilot body types and sizes.

        Go ahead, tell me how you would do that?

        ########################

        “Now we’re going to turn that faith into math and make it useful for humanity during a worldwide pandemic, the critical parameters about which we have little to no knowledge for input variables into our model. How do you even start coding that model based on faith? We did that and that plan didn’t really work out well did it?”

        You can’t rise to the challenge can you? Look SOMEONE has to build the plan for the hospital
        Let’s pretend thats YOU.
        feb 17th the USA has 68 cases, ZERO deaths.
        You are the CEO of a NYC hospital? How should you prepare?

        the models are not coded on faith. They are coded on the nature of disease spread.
        BUT there are unknowns, basically R0.. which you only have limited data on.

        From Korea and China you had some data. What do YOU do?

        It is easy to say they got it wrong. here is the challenge to YOU.

        Given: USA 0 deaths and 68 cases on Feb 17th
        Predict how many hospital beds and body bags you will need in new york by April 30th.
        Show your work!

        ##############
        What if we turn our focus to evaluating how successful (read: “accurate”) our models predicting the, e.g., hospital burden turned out to be?”

        For IHME I would say it was damn useful for New York.
        They predicted more beds than needed and more vents than needed.

        Consider this. In an aircraft you have a model called the BINGO FUEL model.
        It runs constantly. You enter your flight plan Point A, to Point B, returning to Point A.
        You add the weight for your bombs, the model looks at drag tables, looks at winds,
        and makes several assumptions.. wind will stay the same, will the course be followed and
        bombs will be dropped n time, and after making these assumptions it also has a safety factor
        added. What you dont want is an ACCURATE answer, you want a model that predicts
        0 fuel when there is actually 10% remaining. you want to be conservative in all
        your judgements because a plane with fuel, like a hospital without beds, is a BAD BAD
        Thing.

        So success in predicting beds is NOT measured by accuracy, it measured by
        Did you over run the beds, or did you have spare beds?
        That’s the first order metric.
        The second order metric is how much excess did you have? and what did that excess
        cost you?

        it is the same kind of problem I would face in production planning. I want to
        build 100K machines, each has 300 chips. how many do I buy?
        100K * 300?
        Nope.
        Why? well because history tells me I have to plan for an UNKNOWN yield
        unknown yield of chips, unknow yield after final assembly.
        I have to plan with safety factors. Should I plan for 10% yield loss? 5%? should
        I just assume that the this new chip will be like old ones and use 98%?
        what about that time, yield was only 85%
        If I use 85% what will I do with the excess? is it sellable? where? to whom? how much?

        ###########################

        What say you? Should we use the various historical model results from past models to model the usefulness of any future models?

        probably not. The issue is you basically have two types of models.
        A) agent based models ( discrete time step event models) or mechanistic models
        B) Differential models (continuous equations ) non mechanistic

        And to make the problem harder you don’t have a lot of historical data to improve them.
        Unlike, say, weather models. You have what you have. and decisions will be made.
        Decisions to do nothing or do something. And absent a time machine that means modelling.
        Its the same with war. You basically have t go to war with a battle plan.
        These plans are checked and “validated” with models.
        Again 2 types.
        1. Discrete type event models.
        2. differential equations
        (https://en.wikipedia.org/wiki/Lanchester%27s_laws)

        And again not a lot of data to go on.

        But the general wanted a plan

        https://onlinelibrary.wiley.com/doi/abs/10.1002/1520-6750(199506)42:4%3C691::AID-NAV3220420411%3E3.0.CO;2-X

        Model used here was this
        https://apps.dtic.mil/dtic/tr/fulltext/u2/a083189.pdf
        old and basic.

        Every war is unique, every fight against a pandemic is unique. This isn’t rocket science,
        its harder than that. There you have laws that dont change.

        Now, no one whines when war modellers got it wrong. How do I know? well I did combat modelling in the 80’s. we got a ton of shit wrong. There was no choice but to give our best
        assessment, which we knew would be wrong and which we knew would offer no lessons for the future.

      • L-I-B “Mosher”! I’m flattered you took the time! I really do mean that too.

        What you dont think there are safety margins in aircraft design?

        Not what I’m (as in, “you’re”) saying. I assume there are safety margins, but if there are they can’t at all be evaluated in the same manner as a viral pandemic. It was your argument. You said they weren’t the same thing right after you decided to compare them as though they were:

        So. if you run a hospital you need to plan. There is no physics to tell you how the future will be. You need to estimate.

        Nevertheless I’ll grant you that you’ve got me by the man parts when it comes to designing “Crew” systems. I haven’t a clue.

        You can’t rise to the challenge can you? Look SOMEONE has to build the plan for the hospital Let’s pretend thats YOU. feb 17th the USA has 68 cases, ZERO deaths. You are the CEO of a NYC hospital? How should you prepare?

        Ok let’s pretend. After all, we’re modeling. Well, on Feb 29 the leading experts on the subject matter were suggesting there’s no reason to take any unusual mitigating measures. So I suppose were I the CEO of some NYC hospital system I would’ve been ~panicking along with them, what say you?

        https://tinyurl.com/yb5xopyu

        Further, I’m not sure what you’re getting at here because on Feb 17 IHME is predicting, “All beds needed* 0 (0-0).”

        https://tinyurl.com/w4jhzx4

        Finally, why should we only consider NYC hospitals? Shouldn’t your model be valid for any hospital located anywhere in the United States? Was it? Was it valid when the experts advising Trump used it to advise him to shut down the entire nation, and not just New York?

        the models are not coded on faith. They are coded on the nature of disease spread.
        BUT there are unknowns, basically R0

        Ok not coded on faith, rather the nature of disease spread, “BUT there are unknowns.” So, 1) these particular unknowns are unknowns about which we must actually know something, otherwise they’d be “unknowns” we don’t know by faith? And 2) surely the models aren’t JUST “coded on the nature of disease spread” right? I mean, a model coded on the nature of the spread of the common cold wouldn’t do in this scenario would it? A C-19 R0 is completely different from the common cold or flu given its asymptomatic nature isn’t it?

        From Korea and China you had some data. What do YOU do? It is easy to say they got it wrong. here is the challenge to YOU. Given: USA 0 deaths and 68 cases on Feb 17th Predict how many hospital beds and body bags you will need in new york by April 30th. Show your work!

        Yes it’s easy to say, “they got it wrong.” That’s the problem. It’s too easy to say from the number of times they got it wrong that they did get it wrong.

        Let’s use your assumptions with your own model. Go here: https://tinyurl.com/w4jhzx4

        Then use the slider to select Feb 17 and tell me what you get. I get: “All beds needed* 0 (0-0).”

        For IHME I would say it was damn useful for New York. They predicted more beds than needed and more vents than needed.

        I didn’t ask you to evaluate on the basis of that which is useful. I asked you to evaluate on accuracy.

        So that’s your definition of useful in order to shut down a nation’s economy? That more beds and vents were predicted than needed? How many beds and vents? Hundreds, thousands, millions or does it matter?

        Why aren’t you considering the rest of the nation in your claim of usefulness? Shouldn’t your model accurately predict the number of beds and vents required regardless of regional locale?

        What if we don’t have a New York next time? Why should New York (or wherever) determine the course of action for an entire nation?

        Consider this. In an aircraft you have a model called the BINGO FUEL model.

        Why would I consider that? I’m not doing bombing runs, I’m doing a virus pandemic. Are the parameters the same?

        So success in predicting beds is NOT measured by accuracy, it measured by
        Did you over run the beds, or did you have spare beds?

        Why do I need you then? Any moron can over-predict product need. And you still haven’t answered the critical question:

        If accuracy isn’t the goal, then what is? If you’ve consistently been inaccurate in your prediction of the number of required beds in this pandemic, why should I believe that the next time you won’t under-predict rather than over-predict it? What’s your guarantee and how do you guarantee it?

        Now, no one whines when war modellers got it wrong. How do I know? well I did combat modelling in the 80’s. we got a ton of shit wrong. There was no choice but to give our best
        assessment, which we knew would be wrong and which we knew would offer no lessons for the future.

        Is that your argument? That you knew there was no choice other than the pandemic modeling would be wrong and offer no lessons for the future, nevertheless we should use it anyway?

    • Coronavirus, Deaths, Fears, Models, Data, Numbers, Sources, and endless arguments about the intricate details of the same. I think it’s all a bit of a distraction that’s engaged the World’s greatest minds, as well as the gawking rabbles. Notwithstanding the personal tragedies of individual fatalities, and the avaricious agendas of opportunists such as Bill Gates and his band of like minded Malthusians, and the hosts of rent seeking “scientists” and medical “researchers”, pharmaceutical businesses et al; there is I suspect a very large planned political agenda behind the panicked response, if not the “accidental” and fortuitous for some, mysterious appearance of such a seemingly virulent microbe at this time, when western democracies seemed set for an economic revival, having survived the recent financial crash of the past decade. Fear, Uncertainty, Doubt (FUD); it’s a well known tried and tested military tactic. Hmm 🤔

  10. “The models” means “the guesses.”

    Maybe all this will help some people figure that out.

    And maybe not. The statistics are being tortured until they will confess to anything.

  11. Generally speaking, scientific models require measurable factors that can be expressed mathematically. The discussion about climate models uses W/m^2, degrees C, and CO2 concentration. Those are measurable (more or less) and expressed as numbers.

    Lockdown and Social Distancing are being used as factors in various models, yet neither is defined nor can be measured. Some lockdowns are draconian, others are lockdown-lite. Social distance sounds like a measurement, but it is not.

    In NY nursing homes with vulnerable elders were forced to accept infected Covid patients shedding the virus. Some 25-30% of NY Covid deaths were in those nursing homes. That’s the opposite of a lockdown: more like a lockup with disease carriers.

    A lockdown in a state or nation is considered to be consistent within the boundaries or borders, yet that is manifestly untrue in every case. Claims that lockdowns “work” or don’t are not verifiable.

    Today I observed shoppers lined up to enter a Big Box store where inside social distancing of a putative 6 feet was poorly enforced. It wasn’t enforced at all in the waiting line. How many feet is a social distance? Can that even be measured?

    Yet these unmeasurable, poorly defined, frequently violated, subjective obscurities are cited as known, scientific factors in epidemiological models and as guidelines and/or strictures to be included in socio-economic policies.

    How can we “rely on the science” when it isn’t scientific?

    PS — the Big Box was sold out of meat and Pepsid, although they had toilet paper. Consumers are panic buying and running hog wild, but without the pork. And where’s the beef?

  12. The only argument of the lockdown advocates was to “flatten the curve” in order to avoid to overhelm the healthcare system.

    We know since months thanks to the South Koreans and Chines scientific publications- before any lockdown has occurred in Europe – that only the ederly (and some clearly identified vulnerable under 65) are at risk and that not one fatality occurred on 0 -9 years old children (all those data are is still true so far).

    Thus, the only actual necessary (and urgent) action which would have protected the vulnerable was the containment of nursing homes (and chronic disease facilities) :
    – not a general lockdown of the healthy.

    This could have allowed most of the countries to get herd immunity as soon as possible without destroying their economy and without putting at risk anyone (as we will see, rather lowering the risks).

    Getting herd immunity among the healthy does not cause healthcare system overhelm :
    – The death toll under 65 is small, comparable to the death toll of a common flu so there is NO possibility for this epidemy to overhelm the healthcare system more than a seasonal flu if the appropriate actions (as seen before, essentially nursing homes, elderly and vulnerable containment) are taken and correctly applied.

    Almost each year, the healthcare system is locally overhelmed when the seasonnal flu hits nursing homes. Almost each year in Italy and this happens also in other developped countries, as in the US in 2017-2018. In this case, patients need to be transfered elsewhere and/or ephemeral hospital are created.
    Does that justify a lockdown of the healthy and the destruction of the economy ?

    Furthermore, one lockdown effect (among many other actual disasters it’s causing) is probably to increase the death toll of the vulnerable :
    – Indeed, as seen before, the best way to protect the vulnerable and the elderly is to confine them until the others – healthy people – get herd immunity and this herd immunity must be achieved as soon as possible because the containment of the more vulnerable can’t be effective against a viral infection propagation for a very long time (someone makes almost certainly an error sometime and the more you have to confine the most vulnerable, the more this human error probability increases with daily routine and weariness).

    In conclusion, this “flattening the curve with a lockdown” policy is counterproductive, contradicted by data, based on no published scientific article and is actually causing a social, economical and “icing on the cake”, a health disaster (how many suicides, how many children and women have been beaten ? How many mental illnesses, school dropouts among young people ? How many millions of serious disease treatments have been delayed due to the lockdown ?).

    Do we have to fear a “second wave” ?
    The only hope is that the lockdown has been almost completely useless to decrease the infection propagation so that there will be no “second wave” :
    – We will see whether this assumption is wrong or not but the analysis of the UK and German daily deaths peak, assuming that the mean delay from infection to death is 28 – 29 days (this seems to be correct at least for UK and Germany), seems to show that most of the lockdowns where completely useless, since they have been applied a week or two after the infection propagation started decreasing. This seems to be true for most of the European countries, with – perhaps – the exception of Norway. Time will tell.

    Conclusion :
    Maybe next time politicians will listen to actual scientists, not apocalypse sellers and other charlatans.
    May I highly doubt it ?

    • Thanks for the discussion but my point is that “lockdown” is an amorphous term that cannot be measured, and therefore cannot be credited or discredited scientifically.

      Another non-scientific term is “flatten the curve”. What curve? What does flatten mean? Can anyone provide a mathematical definition? Please specify in units of measurement.

      I mean, we’re all waiting for the “curve” to “flatten”. That’s when the “lockdown”, however that may be defined, can be allegedly or partially ended. But how will we know? What are the parameters exactly? It’s kind of important, but fuzzy/squishy as heck.

      The politicians all say they are relying on science, but their pronouncements are as far from science as can be. It’s fake science, pseudo-science, dumbed down for dummies of which I aren’t one. Even the so-called scientists are using these unscientific terms. Nobody is wearing any clothes.

      • The curve, is the distribution of number of cases. Bell curve, Gompian (Spelling?) Boltzman, whatever your’re using.
        You predict how many infections you’ll get in an area. You parametrise for the number who’ll need hospital admission (Seems about 20% of cases), ditto for those needing ICU admissions (Seems to be about 5% of cases).
        You add in duration of stay.
        How many hospital beds to you have available at any one time? How many available ITU beds.
        There are your ceiling numbers.
        Once those beds are occupied, you’ll be turning patients away.
        “Sorry, no room at the inn”
        Now, unlike in fairy tales, where the mother gives birth in a stable & everybody lives happily ever after, this means that people are going to be dying, if not dying on the hospital steps, they’ll be dying miserably at home, bouncing about in the back of an ambulance as they go from hospital to hospital, to try & find a spare bed. Maybe even spreading the infection to their carers.
        Those carers & their relatives, friends & associates, have votes.
        So, to flatten these curves means to match number of patients, to available care at any point in time. This may mean building extra capacity to care for them, the Nightingale Units in the UK, for instance. Emptying hospital beds asap, if not before, as has happened in the UK, as of 9th March.
        Exceed the capacity of the system to care for these seriously ill people & they’ll die in droves.
        Your chances as a politician, of getting re-elected, just went down the plughole.
        By the sounds of it, you are a dummy, if you can’t comprehend this.

        • The curve, is the distribution of number of cases. Bell curve, Gompian (Spelling?) Boltzman, whatever your’re using.

          This is what I mean about vague unscientific math babble terminology. Our economy is in tatters and we’re Waiting for Gompers? I feel like we’re in a Beckett play.

          There is a graph one could make of total cumulative cases or deaths over time. That graph would be a curve. It would be S-shaped, starting at zero, rising gradually, then steeply, then gradually again but never dipping. Deaths accumulate. The curve does not go down because nobody un-dies.

          There is another graph one could make of the rate or speed of cases or deaths over time, i.e. cases or deaths per day. That graph would also be a curve but it would be bell-shaped. Mathematically the rate curve is the first derivative, or slope, of the cumulative curve. The rate curve goes faster then slower over time. It looks like a camel’s hump.

          Neither of those curves is ever flat. Flat is not something curves do. But I’m tilting at windmills. None of you journalist types have ever passed a math class. I’m spitting into the wind. Figuratively. Don’t arrest me.

    • This is one of the best posts I have read summarising the flawed thinking behind the lockdowns. It ought to be read by all policy makers.

      Certainly, it ought to be only the elderly and those with underlying health problems who are protected by social isolation policies. The young and healthy should be allowed to continue their normal lives with minimal restrictions to protect those vulnerable groups. So, it is shocking to read Mike Dubrasich’s comment that, in NY, “nursing homes with vulnerable elders were forced to accept infected Covid patients shedding the virus”. Unfortunately, a GP in Cheshire has reported that the same thing is happening in the UK too ! In today’s Times newspaper, the front page headline is “Care homes deaths set to overtake hospitals”. That’s hardly surprising if the practice of sending elderly patients who are still infectious back to their care homes is widespread.

      In your post, you have listed some of the health related collateral damage caused by the lockdown. In the UK, with a state funded health service, there has been widespread postponement or delay of diagnosis and treatment for cancers, heart disease, etc in order to redirect staff and facilities to Covid-19. How many life-years will be lost by these patients ? You have also mentioned domestic violence, suicides and mental health issues. One thing which is easily overlooked is that there is a well established correlation between poverty and life expectancy. Unfortunately, many small business owners and people who have been furloughed will find that their livelihood will not return when the coronavirus crisis is over and their standard of living will plunge. This may well result in a serious loss of life-years for those people, albeit this loss may not be manifested for some decades and may not be directly traceable back to the coronavirus lockdown.

      Your point regarding the “second wave” is also well made. Politicians seem to think that by suppressing the transmission of the disease through social distancing they can make it go away. But the virulence of the virus has not changed. If the transmission rate in a population without immunity is 2.6 or whatever the figure is, then a second wave is inevitable when the lockdown is relieved. Only herd immunity can force the transmission rate permanently below 1. Unless there is a vaccine on the short term horizon then lockdown simply buys a flatter curve at the cost of a longer tail and an extended crisis.

      When we weigh the pros and cons against each other:
      – on the one hand we have the lives immediately saved by keeping the current transmission rate low through the lockdown measures. There is also the prospect of holding the situation until a vaccine or treatments are available,
      – on the other hand there is the possibility that the lockdowns are not actually saving lives but simply deferring deaths to a second or subsequent wave, and there is the health related collateral damage caused to patients with other serious conditions and (currently) no conditions.
      It is by no means obvious where the balance of “good” lies. What is clear is that the lockdowns are a huge gamble where the stake is certain catastrophic economic damage and the winnings are debatable.

      • You have been making bad assumptions about both the “Lockdown” and the Non COVID-19 deaths in the UK.
        First of all the lockdown is to protect the health system being overloaded, the question of when the lockdown can be released is when there is a large reduction in new cases.
        But that does not mean that you can abandon social spacing.
        Think about this for a minute, with the UK in supposed lockdown how are we still getting over 3000 new cases every day?
        The other point you raised about Non COVID-19 deaths has absolutly nothing to do with any kind of lockdown.
        It is totally to do with the government and NHS mishandling of how to run hospitals when an epidemic is present.
        It is called Quarantine, ie you Do Not mix COVID-19 patients in hospitals with ordinary general medical patients, risking their lives and eventually stopping or cutrailing normal operations.
        The only real deadly desease quarantine areas we have are actually inside general hospitals instead of out in the country “isolation” hospitals that we used to have.

        • “First of all the lockdown is to protect the health system being overloaded, the question of when the lockdown can be released is when there is a large reduction in new cases. But that does not mean that you can abandon social spacing.”

          Reply : I am not advocating no lockdown. I am in favour of a targeted lockdown which separates the vulnerable groups (elderly and those with underlying medical conditions) from the rest and allows the rest to continue their lives unimpeded. It is almost exclusively those in these vulnerable groups for whom infection requires hospitalisation. The rest of the population can be exposed to the virus with mild or no symptoms, thus creating herd immunity which provides the ultimate protection for the vulnerable groups.

          The overwhelming majority of the elderly do not work and so their confinement would have little impact on the economy. Those in the working population who have underlying medical conditions should be allowed to self-isolate without prejudice from their employers.

          What do you think will happen when there is a large reduction in new cases and so the lockdown is released ? The population will not have acquired herd immunity.

          “Think about this for a minute, with the UK in supposed lockdown how are we still getting over 3000 new cases every day?”

          Reply : This could mean that it is too soon to release the lockdown. Or it could mean that the lockdown does not work to prevent the spread of the disease. The lockdown has now been in place for over 5 weeks. This is longer than the period to incubate the disease, suffer from the symptoms, fully recover and no longer be infectious. So why are we still getting a substantial number of daily new cases ?

          “The other point you raised about Non COVID-19 deaths has absolutly nothing to do with any kind of lockdown.”

          Reply : If you read the online newspaper comments sections, you will see plenty of commenters saying that their cancer referrals and therapies have been repeatedly postponed. It is difficult to believe that this won’t have any effect on outcomes.

          Also, the fear of contracting covid-19 in a hospital must be widespread because NHS officials have felt it necessary to urge the public not to hold back from requesting help if they develop suspicious symptoms. Perceptions affect behaviours.

          As regards an increase in domestic violence, suicides, mental health problems and loss of life expectancy from poverty, these are all a direct result of the lockdown: confinement with an abusive partner, worry over loss of livelihood and the material effects of having no money. Health outcomes are not exclusively about what happens in hospitals.

    • The notion that infecting the <65y old would not overwhelm the health care system is not justified by the numbers. Hospitalization rate and ICU occupation is still too high in younger ages though the death rate is relatively low but patients <65y make up 56.6%(!) of hospitalized patients if you take <50y it's still 25.5%.

      Though even the relatively low death rate translate into big numbers if you want to go down the path of herd immunity:

      You need 70% for herd immunity.

      From New York State numbers the ages 20-50y make up 5.5% of deaths.

      CFR from Iceland, Taiwan and South Korea is at least 1% and that is also the newest upper projection for Europe as more data comes in. Prof. Woo-Joo Kim even estimates 2-4% but let’s just hope he is wrong (though he was right about most things so far…).

      So the death rate for this specific group would be 0.00055%.

      From 308 million Americans ~40% are 20-50y.

      308 x 0.4 x 0.7 x 0.00055 makes 47,432 deaths.

      I don’t think so many people <50y die from the flu annually and definitively not that much have to get hospitalized.

      "that only the ederly (and some clearly identified vulnerable under 65) are at risk and that not one fatality occurred on 0 -9 years old children (all those data are is still true so far)."

      There are already some deaths from Spain, France, China and Italy in this age groups and they recognize an extraordinary accumulation of a very severe condition in children resembling the Kawasaki-like disease where SARS-CoV-2 could be the underlying course.

    • They’re also treating the pandemic, as being uniform across entire countries.
      If we look at the UK, there’s a big band of infections stretching from Hampshire, through London & into Kent. Other hot spots in Cardiff & surrounds, Birmingham, Lancashire & Glasgow. Other areas are more or less, untouched. South-West England, Central Wales, The Borders, Scottish Highlands& islands & Northern Ireland.
      I’m guessing that the USA will be the same.
      So, rather than setting national rules for this, local ones need setting.
      Shutting up the major cities is a good idea, trying to test & trace in them, will be virtually impossible. Small towns & below, much, much easier.
      So, local lockdowns in areas with uncontrolled infection, test, track & trace with isolation & quarantine in areas with less infection.

  13. “Lesson: there is no single reproduction rate”.

    A similar sort of thing occurs in the field I work in, remote mineral exploration drilling, (it’s not about health, but it might interest some oil researchers and others at this site), and I was once asked about an ‘aglorithm’ or spreadsheet that I use to predict drill hole deviation for an upcoming major drilling program, making it easier to plan such holes from a head office, rather than getting one’s ‘hands dirty’ locally. I replied that we didn’t use any spreadheet or algorithm on site, because such holes rarely behave the same, they are all different.

    What we noticed on site though, is that holes drilled very close to each other (say within 30m or so, and at the same particular gold prospect), and also drilled in the same direction, often deviate in the same direction and inclination. So for hitting a small, say only 5m wide, gold target, 250m below the surface, we often rely on past nearby holes to make adjustments to the planned holes, so we don’t miss the small high grade gold target. (We intercepted the highest gold intercept in Australia in 2019, although one in Canada just beat us out worldwide). The reason this method works locally, is that the rocks closeby to each other often have the same structural configurations; the same dips and strikes, the same foliation, the same contact relationships, the same hardness and weathering, and so on. But go to another prospect 1 kilometre away, and all these characteristics are different, resulting in completely different hole deviations. Aim if left and it will go right, and vice versa. Most often you can’t transfer one set of hole deviations to another area.

    So these is no single spreadsheet or ‘algorithm’ for a major regional drilling program, unless you are within 30 or so of other holes drilled in the same dip and direction. Localised factors play a significant role in hole deviation, which can’t be predicted without prior localised drill data.

  14. My dear Monckton:

    I fear you are fast becoming a disgrace to your father’s powers of propaganda.

    Let us pray for your speedy recovery.

  15. In case anyone miss it… You Tube took down the vidoe of the the California ER doctors discussing evidence and arguing for an immeidate end to the lockdowns.

    That interview did not conform to what the SheePeople are suppose to hear about what is going on.

  16. The problem here is that, as in much of “climate” science, we really don’t know whether the models are good or not. This is because the “data” being plugged into them is highly suspect, in both cases.

    The problems with climate “data” going into the models have been beaten to death here. For CoViD-19, there are very similar problems with the “data.”

    How many deaths are FROM CoViD-19, and how many deaths are simply WITH CoViD-19?

    Of the former, how many deaths are FROM infection by the novel coronavirus, and how many are the result of mistreatment of the infection? Note, this is not an indictment of medical professionals, at least not First World practitioners. They are, by and large, treating patients by Accepted Medical Standards. “Accepted” does not necessarily mean “correct” – which is why the standards are always a moving target. There are indications that the “accepted” treatment for severe respiratory inflammation, full scale ventilation, is NOT correct in all too many cases. Patients that would not be in the death tally if less invasive procedures had been used.

    Of both, how many cases (dead or hospitalized) are ACTUAL CoViD-19, and how many are PRESUMED CoViD-19? As in much of climate “science,” there are political factors that can push the numbers either way – and economic factors that are pushing the numbers only upward.

    In any case, the real “indicator” should be, for any scenario, how many total years of reasonably decent life are being lost to the population? For a very small portion of the population, a few years, or months, or weeks of life, with illnesses that are already diminishing the decency of that life, are being preserved by the shutdowns. For a very large portion of the population, I would say at least 90%, decades of what could otherwise be a decent future life are being turned into chimeras.

  17. Our governor clown of Ca. just announced that we are weeks not months away from ending lockdown. He uses the kingly “we” as he announces maybe the results of what his models predict. Such certitude from an expert. I guess the “we” know how our immune systems have not been compromised by the lockdown. At least Newport Beach opened the beaches in defiance of the “we”.

  18. Christopher:

    You’re splitting hairs over the IME model. At least it was approximately right, within a few 10s of %, rather than panic-inducing wildly wrong by multiple orders of magnitude. Problem is that Ferguson has form about being wildly wrong, creating widespread panic amongst the innumerate Classicists that govern us and precipitating solutions that cause more harm than good. The F&MD was an absolute tragedy for the countryside and wholly unnecessary as subsequent enquiries found.

    That being said, a simple analysis based on observation, as opposed to deriving nonsense from intricate (and unstable) models of complex systems, is probably a better approach to making predictions about climate. As a career engineer and also a pilot, if I’d had £10 for every decision I’d made not to fly based on a72hr or 96hr weather forecast, I’d be a multimillionaire. Common expression in our household then the forecast turns out to be wrong again “if they can’t get it right over 5 days, how do they expect us to believe forecasts for the year 2,100″….

    Occasionally you write nonsense, sometimes it is okay. Whatever, keep up the good work.
    ATB & KBO

    • Ferguson’s organisation is heavily funded by Gates and other Malthusians, and he who pays the piper calls the tune. Imperial will never censure Ferguson, because he us a sellout and just doing as instructed by his puppeteer masters. Why the UK Government under Al Johnston permits such chicanery is a mystery though. It can’t continue. MoB was, I fear, distracted temporarily by these events, and no doubt concerned for those in the “Sceptred Isle”; tried to apply his considerable mathematical expertise to the problem, in the best way he knew how. We hope however that these events thus exposed as a largely political ploy to the general public at large, will make them rather more sceptical about the pernicious ” climate agenda” too.

  19. Maybe a weather ( or climate) analogy is hurricanes heading towards Florida.
    We see a hurricane coming.
    We rate it’s potential danger.
    We plot it’s course.
    We warn the public, enforce evacuation and take action.
    If the hurricane changes direction or reduces in intensity the alerts and actions should change.
    There should be no loss of face or bickering about lost revenue.
    Just say opps we got that one wrong, we’ll try and be more accurate next time.

    The lockdown was needed, but the government got the scale of the virus wrong .
    Now, let’s move on and open the lockdown

    • With the number of states in lock down you would hope so …. be just a little bit pointless if they weren’t 🙂

    • richard
      Seasonal flu(es) peaked in the US about February, after starting in the Fall. It appears that COVID-19 started about February. If COVID-19 is subject to the same influences as the common seasonal viruses — increased humidity and temperatures, increased vit’-D, greater physical fitness from outdoor activities — it shouldn’t be a surprise that the cases are falling. California has had 90 degree days recently, and it was over 70 in the Mid-West recently.

      Interestingly, Sweden (with no actual lockdowns), has lower death rates than Ireland and Canada, and only slightly higher than the US. I’m of the opinion that social distancing is helpful; however, the lockdowns are of questionable additional value, at tremendous cost to the economy and mental health.

    • No it is not, look at the shape of the “curve” in countries with lockdown, instead of sharp peaks we have a peak followed by a long plateu.

    • Trust good old GC, he never did mince his words, and never ceased to be amazed as to why people paid him large sums of money to stand there and simply by telling the bald truth, and stating the bleedin’ obvious, make the people laugh. It must have been “the way” he told ’em? RIP George Carlin, but if he could come back from the dead, just for a few hours, it would be to chisel “Here lies a man who didn’t die of CoViD19”.
      Many’s a true word that’s spoke in jest !

  20. “… at least eight of the next-generation models, produced by leading centers in the United States, the United Kingdom, Canada, and France, that “equilibrium climate sensitivity” has come in at 5°C or warmer …” (Science AAAS).
    That prediction is indicated on Christopher Monckton’s second diagram above.
    I’m a layman but I do know how to plot a graph and applying that prediction to his first diagram (HadCRUT4) and assuming a constant rate of CO2 increase (~2.4 ppm/annum) it is apparent even to me that it is a preposterous proposition, even 3C above pre-industrial is nonsense.
    This ‘builders’ square’ from Skeptical Science’s Daniel Bailey in 2010 is the general idea except that now twenty years on the ’21st Century Warming – Still to Come’ line would be even steeper:
    http://3.bp.blogspot.com/_CXhZq5GDGH4/TGoWgvTsEjI/AAAAAAAAAMQ/S_KyPNOJp5Q/s1600/Hockey+stock+-+21st+century.jpg

  21. The key indicators for the Charney warming used here are based on the assumption that all the observed warming has been caused by CO2 increases. That assumption is wrong. Most of it was caused by ‘natural causes’. The real Charney warming will turn out to be between 0.5K and 0.7K, less than half of the 1.4 given here. Some caution here. The way things are going it is questionable whether the ‘doubling of CO2 concentration’ from 280 or 300 to 560 or 600 ppm will ever materialise, so we may never know the real answer.

    • It may not even be that much. The water cycle is a powerful thermostat capable of keeping the planet at a stable temperature unless something interferes with its operation. Or to put it simply, IF Svensmark is right about cloud intensity modulation, that is a lever many times more powerful than trace CO2.
      IIRC continental drift has been invoked as a way of modulating global circulations and heat transports to create ‘desert earth and ‘snowball earth’ as well as effective local variations in solar input due to orbital and polar axis changes.

  22. The unanswered question that comes out of this Covid 19 world response, is, what do we do when the next novel virus comes along?
    If the world was panicked into economic suicide due to Covid 19. what will it do when Covid 21 hits us?
    The known costs of this over reaction to maintaining the fragile lives of the near death age group, along with the near death patients already carrying other life threatening illness is unprecedented.
    It gets worse.
    When you consider the cost and efforts being deployed, will only be a short period of delay in the inevitable outcome of those already knocking on deaths door, which is always… “come on in, we have been expecting you”.
    When did we become afraid of the only certain fact of life, i.e. we all die?
    The life changing effects, for those who are traumatised by lock down debt, or social decay, or hyper anxiety leading to ongoing mental issues, will be unknown but no less real. For many it will be lifelong and for some it will lead to suicide.
    Many of the businesses that were only ever there because of tradition, or family commitments will not reopen. the pubs, the clubs, the social circles, how many will be permanently lost?

    All this additional legacy national debt for what?

    The victims of this virus, novel or not, are virtually all at the end of their long life. A quick look at the stats tells us, the majority of those who die are over the average life expectancy, so what is the real problem?
    I suspect the issue is not that people are dying. It is more to do with the difficulty the medics are having dealing with a virus that does not respond to traditional care or treatment. They can’t deploy traditional support treatments and thus, they are at a loss as to what to do to provide beneficial support to the patients presenting.
    This virus is a killer that is true, but only if you are among the at risk group. For the vast majority of people it is just another virus, it won’t be the last, so I ask again.
    What do we do when the next novel virus hits, because it will?

    • What if it exclusively pre pubery teens, or teens in puberty.
      How would you then feel about lockdown?
      The whole problem for the world is that China did not “lockdown”, they did not prevent anybody coming in or going out of their country.
      And the rest of the world did not lockdown China either, they just let them travel all over, instead of immediately returning them to China and properly quarantining every body in the aircraft ship or whatever.
      Those things should have been co-ordinated by the WHO and they did exactly the opposite.
      But then they failed those suffering with Ebola as well.

    • We plan for it.
      We plan to identify it quickly.
      We plan to stop travellers from the source of the infection, carrying it far & wide.
      We plan to test for it, to trace contacts with infected people.
      We plan how to isolate & quarantine those with infection.
      We plan how to rapidly increase hospital capacity, to take the ill infected patients, out of the general healthcare system.
      We plan how to either increase stocks of PPE, or to rapidly increase manufacturing capacity of PPE.
      We plan for it.

  23. There is an important point here. Engineering models are extremely accurate, because they were improved until they told the exact truth (partly because the underlying science was completely understood). These models which Christopher is discussing have no scientific basis, simply a statistical one. If we understood the exact transmission mechanism, the infectivity by virus load, the exact outcome for various underlying existing conditions and many other things we could have a very good model. The problem is the same as the climate one, we virtually know nothing about all the connected incidences, and so we start to rely on statistics taken from faulty and incomplete data. His calculations based on his 3 parameter method are quite accurate so far, probably as good as any of the computer statistical models. This should tell us many important things about the climate. First we need much more research into the sources and sinks of CO2. Never mind the predictions, we need the real science. Second we need far less hype. This may get funding but basically is making false claims with no basis. Third, we need to understand the simple point that unless we wreck our society and kill a huge number of people we cannot stop using fossil fuels, we cannot return to a subsistence farming kind of stone age, there is far too much population on Earth. Now we know the parameters we cannot change, we need to make sensible decisions as to actions, which probably are none except stop worrying.

    • But the hapless uninformed vast majority, who never read these columns, or indeed the articles themselves (for there’s often more to be gleaned for the thirsty minded in the comments), they think themselves immortal when young, have plenty time in middle age, and when elderly are past caring what others nay think. Then comes the point when as elders they are freed from the shackles and bondage of political correctness and conformity. They’ve seen it all before, and not so easily ruled by convention. This is why it is important to have the wisdom if the aged, and why the youth do need them to stay with us as long as possible, for written records can be amended, faked, censored. Its less easy with a living being. The problem still remains to discern who is lying, and who states the truth. By their deeds shall ye know them!

  24. I would like to take a historical perspective based on a book [Ref. 1] published in 1989 and edited by the late Fred Singer in which Andrew Lacis, writing from a modelling point of view, wrote at page 83, “The results of these climate simulations show that … the climate system operates with strong positive feedbacks which magnify climate forcing perturbations by a factor of the f = 3-4 yielding a global warming of 3-5[deg]C for doubled CO2 …”

    Lord Monkton has shown above that today (i.e. about thirty years later) the models are still predicting warming some 2 to 4 times what the empirical evidence suggests. It is thus clear that the modellers and their allies have learnt nothing in the intervening years. One wonders why they have failed to improve their predictions given all the public funding they have received over the years.

    This is a very sorry post-normal science business.

    Reference
    1. S. Fred Singer (editor), “Global Climate Change – human and natural influences”, ICUS/Paragon House, New York, 1989, especially Chapter 4, ‘CLIMATE from a MODELING POINT of VIEW’ by A. Lacis.

    Regards,
    John Cullen.

  25. When I glanced at the chart with the model predictions of warming, my brain first interpreted CMP5 and CMP6 as ‘CHMP5 and CHMP6’ as in Chimpanzee 5 and 6. Chimpanzees throwing darts at a board with warming predictions are probably as accurate as the model predictions of global warming.

    • No it is just the number of chimpazee’s recruited to write them. You need an infinite number to produce one of Shakespeare’s plays, so 5-6 is probably about the right for the model predictions made.

  26. “One can apply the same key-indicators analysis to the climate question.” – only if one assumes a priori that CO2 causes warming for which there is definitely no evidence.

    Analysis of atmospheric CO2 concentration relative to UAH satellite lower troposphere temperature does not show a statistically significant probability for a non-zero correlation. However analysis of the annual rate of change of CO2 concentration (necessary because the temperature data is adjusted to remove seasonal variation) with the temperature provides a correlation with an infinitesimal probability that it is zero.

    The relationship is so definite that the Fourier Transform amplitude of both time series, CO2 rate of change and temperature, are practically identical. Furthermore the peaks in the amplitude spectra relate to the periods of movement of the Moon and the planets with respect to the Sun and the Earth. The most prominent amplitude relates to the period of occurrence of the El Ninó Southern Oscillation. At the other end of the scale, the spectra define the 27.2 day draconic period and the 29.5 day synodic period of the Moon, a temperature change event of which we are not consciously aware.

    Clearly the temperature drives the rate of change of CO2 concentration as it is not possible for a rate of change, dCO2, to define a level, temperature.

    The fallacy is to assume that linear trends indicate causation. A linear trend can be fitted to any time series. That does not mean that everything is related causally to everything else, being positively related if the linear trends are either both positive or both negative or negatively related if the slopes are in opposite directions.

    In spite of this being apparent in data freely available on the Internet, the World soldiers on using the false assumption that CO2 causes warming. Why, just because the UN IPCC says so?

  27. CMoB, one question:

    What changed in the analysis between Apr 24 and Apr 26 whereby the case growth rate now has some negative values? Thus the Apr 23 value for Australia changed from about +0.5% to -12.5%. Is this a result of the starting date shifting from Mar 28 to Apr 1?

  28. There are some odious people pushing this lock down. In the US , a video of two doctors using stats to illustrate that the lock is not necessary has been pulled by youtube.

    • Why do you keep insisting that lockdowns with social spacing have no affect on the numbers?

      • judging by no lock down countries they don’t make any difference.

        But what will happen is lock downs will be in for a heavy recurrence later in the year.

  29. 1. How much warming has actually been measured to occur up to a given date? From 1850-2011, the year to which data were updated for IPCC’s latest Assessment Report, just 0.75 degrees’ warming had occurred (HadCRUT4).

    If we’re looking for ‘key indicators’, then calculating the warming from an 1850 start date presents a difficulty. The cumulative influence of man-made greenhouse gas emissions would have been a lot smaller in the earlier years, when they were still relatively low. Indeed, there is no trend at all to be found in the global HadCRUT data over the first ~80 years of its coverage (1850-1930 trend is 0.00 C/dec; 0.00 C total warming).

    Perhaps starting the calculation from the beginning of the 20th century may provide a more useful key indicator. To 2011 this gives a warming rate of +0.07 C per decade; +0.83C total warming. If, rather than stopping at the last IPCC report date in 2011, we take it out to the latest HadCRUT4 update (Feb 2020), then the rate from the beginning of the 20th century rises to +0.08 C/dec; +0.98 C warming overall.

  30. There are of course problems with the reported number of deaths. As others have pointed out, the deaths figure is “reported deaths” not “actual deaths”. There are time lags in the reports, inaccuracies and revisions. Not to mention reclassifications: “died from” morphed to “died with” to “possibly died from”. Add in the incentive of free government cash for each ChiCom flu death at your institution. Don’t forget the desperate need to have the death totals match the model’s sloppy predictions to save face.

  31. One point to make that’s been raised before by others: The death rates in the US are bunkum. Medical professionals are basically being instructed to designate deaths as COVID-19 whether the doctor thinks the virus had anything to do with the death or not. If there is a chance that the person was infected when they died, it’s being documented as a COVID-19 death.

    I was a little skeptical about these reports when I first started hearing them, but I have a good friend who’s a doctor and verified it. If anything, she says, the reports are a bit understated about how much pressure is being applied to them to classify deaths as COVID-19 deaths.

    I’m curious as to where this pressure is originating. My guess would be some liberal “deep state” operative in the Department of Health or CDC that’s trying to keep the fear alive long enough to crash the economy even worse than it already is and possibly in an effort to increase absentee voting in November, which is notoriously prone to voter fraud…but that’s just a theory.

  32. If you’ve got a beach, go there! There’s not a live virus around, you get your vitamin D and you get to thumb your nose at your oppressors.

  33. Models aren’t worth the paper they are printed on. I say that recalling the old admonition that says, “Garbage in, garbage out’! Models, like political polls, lie! Those who believe them are gullible fools. IMHO Just sayin…

    • Dear Robert, absolutely correct. Models are kind of pointless when you don’t have decent data going in. The most important number you need to know is the % mortality rate of those infected, and you get that by lots of testing. From the reports I’ve seen where this has been done – South Korea for instance who know a thing or two about viruses and their spread – the mortality rate of Corona Virus is at least 1% and possibly as high as 3%. So if everyone in your county catches the virus you can work out how many will die.
      Obviously not everyone will catch the virus and at some point herd immunity will kick in, but it does give you a reasonable estimate of what you are dealing with.
      Also worth noting, this isn’t going to be a short term problem. Until there is an effective vaccine or herd immunity kicks in many more people will catch it, some of whom will die.
      No point in looking at the numbers now because we are under a lock down which is not sustainable. In the next few weeks / months the world must get back to work or go bankrupt which in itself would probably kill more than the virus.
      So to summarize , Corona Virus is here, it isn’t going away, and until we have a vaccine or herd immunity kicks in we are going to lose many hundreds of thousands of people across the planet. How many? No one knows, especially computer models…..

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