40 Replies to “It’s Probably Nothing”

  5. Found this Wuhan webcam. I can’t vouch for its veracity. It automatically changes between cams. Pretty quiet for a city of 11 million. 6 weeks of quarantine complete…
    https://webcam.scs.com.ua/en/asia/china/wuhan/overview/

    Agree with the incomplete data and the inability to say what the CF is.
    There is more than 4-1/2 million Canadians age 70 and above for whom the Kung Flu might be yet another threat in addition to the regular Flu.
    The Johns Hopkins website numbers for new cases in China is flat. But the recovered cases are flat as well or stagnant might be a better term.

  6. We are in good hands. Trudeau has struck a Corona virus committee headed by Freeland who assures us they are ready for any possible pandemic.
    People are ahead of government, they’ve been stocking up canned goods and of course hand sanitizer and toilet paper, all seem to be on top of the list for stockpiling.
    Instead of borrowing a cup of sugar our neighbours might ask to borrow a roll of toilet paper should the virus happen to get past the committee.

  7. What is the case fatality rate elsewhere?

    According to today’s numbers from Johns Hopkins, outside of China, 15,337 cases in the rest of the world with 278 deaths gives a Case Fatality Rate of 1.8%, about the same, actually a hair less, as it has been since the onset.

    By definition: Case Fatality Rate = number of dead / number diagnosed, not the “number recovered” which is some made up nonsense, whether out of a lack of understanding or because it makes scarier, but bogus, numbers is unclear.

    Per the NIH, 80% recover with no treatment, the fatal cases so far are overwhelmingly among those the elderly or those with some other condition, and it is unknown how many cases with symptoms so mild they are never reported there are.

    For some perspective, during this flu season per the CDC there have been around 16,000 deaths reported and “pneumonia & influenza” have accounted for up to 7.5% of all deaths.

    Unlike the author of the link, epidemiology is part of my job description.

    1. The CDC? The guys who weren’t properly stocked up with hazmat suits during the Ebola outbreak when Barry was Pres?
      That CDC? If they told me the sky was blue, I’d have to look for myself.

      1. Was that the last Ebola outbreak we all died from, or the one before that we all died from ?

        1. “outbreak we all died from”

          Who is “we”. You and your tape worm?
          The CDC is incompetent. You’re either prepared or not. Being prepared is the CDC’s job. They’re bad at it.

    2. epidemiology is part of my job description
      Awesome. So can you explain it a bit better? I understand how someone who barely gets the sniffles will probably not get reported. But if the numbered recovered is bogus is the number that haven’t recovered bogus as well? I just assumed they were sods filling hospital beds that haven’t recovered or died.
      Also, are there or can there be two strains?

      1. Sure – it’s not the number recovered that is bogus, it is using it as the denominator in calculating case fatality rate that is bogus, or comparing isolated instances of case clusters.

        1) The full definition out of the textbook for case fatality rate is the ratio of people who die from a specific disease to all individuals diagnosed with that disease, or in short CFR=dead/diagnosed.

        Let’s say there is an outbreak of gastric epizootis, on day one, 10 people are diagnosed.

        At the end of a week, one has died, and one has fully recovered. That one has fully recovered is irrelevant, 10 people have still been diagnosed, and 8 still have it. So far the CFR is 1 dead/10 cases=10%, not 1 dead/1 recovered=100%. If, at the end of two weeks, everyone else has recovered the CFR is still 1 dead/10 diagnosed. Had someone else died, but everyone else recovered, then the CFR would be 2 dead/10 cases or 20%.

        2) Isolated instances. In Kate’s link the author has for Seattle 9 diagnosed, 9 dead for a CFR of 100% – is this accurate ?

        Yes and no. What can be said is of the cases reported in the author’s story, the Seattle CFR might be 100%, but that doesn’t explain why the same disease in South Korea has a CFR of 0.6%. Could it be two strains? Not impossible, but not likely that Seattle alone would have a worse strain than the rest of the world where the CFR in general is around 2-3% (and the rest of the US where the CFR is near zero), so something else must be going on. When one starts to dig into it, most of the cases were isolated to a single nursing home – IOW, a population most at risk. As of today all of Washington state is reporting 39 cases, and of 10 new cases reported yesterday, 7 are reported to be residents of the nursing home, and two others “associated” (assuming they work there or have a relative there) with it so this is clearly an outlier, a case cluster, and not indicative of the disease in general.

        Next, the data in Kate’s link are way off, from the reliable Hopkins data, South Korea has reported 6,088 cases and 35 deaths, not 88 cases. Germany 444, 0 deaths, France 444, 6 deaths, and so on.

        The bottom line is it is one always has to look deeper than the scare headlines, and regardless of whether the CDC had enough hazmat suits for another crisis that wasn’t, their data are generally very reliable, and a good place to start looking.

    3. Lugnut you are ENTIRELY WRONG.
      Mortality vs. morbidity cannot be determined until the case is resolved.
      Mortality rate = # of deaths divided by the total number of RESOLVED cases.
      Especially with 16 to 18 percent of cases in the severe to critical bracket.
      That method of calculating mortality is deliberate deceit by your information source regardless if it is a so called expert or not.

      1. Mortality rate = # of deaths divided by the total number of RESOLVED cases.

        Mortality rate and case fatality rate are two different things, and there are many different mortality rates (crude, proportionate, cause specific, etc,), the nearest to CFR is the cause specific mortality rate.

        By definition, straight out of the textbook, mortality rate = (deaths in a given time/population in which the deaths occurred) x 100,000 (or other multiple of 10 depending on the size of the population)

        As an example, the cause specific mortality rate from flu in the US during the 2018 season was (rounding) (80,000/320,000,000) x 100,000 or 25/100,00 people.

        In this instance, speaking of COVID-19 the cause specific mortality rate from onset to present would also be calculated by region for example, South Korea, (25 deaths/51,000,000) x 100,000,000 or 0.5/1,000,000 which is a pretty meaningless number, and why, in situations like this, CFR is a more accurate assessment of a disease severity.

        I have given textbook definitions, you can look them up if you don’t believe them.

        1. Oops – S. Korea – (25 deaths/51,000,000) x 1,000,000 or 0.5/1,000,000 – not 100 million in the denominator.

    4. “By definition: Case Fatality Rate = number of dead / number diagnosed”

      Technically correct and entirely irrelevant when the recovery rates are in single digits. As of noon today the conclusion rate = (# of deaths + # of recoveries) / # reported cases for countries with more than 50 reported cases excluding China and Iran was just opver 6%.. When 94% of cases neither died nor recovered your formula underestimates true death rates. By how much it is impossible to tell by now. In such situation, it makes much more sense to use the following formula: death rate = # of deaths / (# of deaths + # of recoveries). See my post below.

    5. Ludwig, I have been saying the same thing here for weeks but people here would rarher piss their pants and panic. They are not interested in details and facts. Nor are they able to evaluate risk in a rational way. I appreciated your detail. It might convince some people.

      1. Agree with you Ludwig – it’s useless math. Math and data from an incomplete set. It’s still data but about as predictive as drawing a straight line through two data points.

        So What, What factual well reasoned argument from you? Ad hominim flinging is the empty tank of logical and well reasoned argument. Work on your writing skills man because if you were saying what Ludwig was saying prior, it musta been in the spaces between the words. Looking forward to you upping your game. I see no panic here. Just black humor and healthy skepticism. Plus we’ll have toilet paper. Soft, soft toilet paper. Rooms full of it. Going to count it now.

  8. Isn’t this the website with a regular “We Need A Famine” headline?

    Response should be “Faster please”

  10. I played with the numbers earlier today.
    Based on John Hopkins data as of noon today, some numbers have climbed up since then, but not by enough to distort the overall picture. All rates calculated as percentages.

    Location; death rate 1; death rate 2; conclusion rate;
    All countries with more than 100 reported cases, excluding China and Iran; 1.50; 24.96; 4.52;
    All countries with more than 50 reported cases, excluding China and Iran; 1.45; 23.77; 4.64;
    All countries with more than 50 reported cases excluding China, Iran, SK and Italy; 1.16; 12.59; 8.07;
    World; 3.41; 5.80; 55.36;
    South Korea; 0.57; 46.05; 0.67;
    Italy; 3.46; 27.94; 8.93;
    China; 3.75; 5.45; 64.94;
    Iran; 3.05; 12.65; 24.08; 21.04;

    Death Rate 1 = # of deaths / # of reported cases.
    Death Rate 2 = # of deaths / (# of deaths + # of recoveries)
    Conclusion Rate = (# of deaths + # of recoveries) / # of reported cases.

    The closer the Conclusion Rate is to 100% the closer the Death Rate 1 is to Death Rate 2. With low Conclusion Rates (and these are very low right now) Death Rate 1, which is the officially reported statistic, drastically underestimates the actual death rate. With low Conclusion Rate, Death Rate 2 may underestimate or overestimate (probably overestimate for most countries) the true death rate. The numbers we have, really don’t tell us what is going on even for countries that can reasonably be counted on accurately reporting true detected infection counts.

    Why do I say we know nothing? Those rates vary by orders of magnitude. Both across countries/groups of countries and within the countries across of Death Rate measures used. This is for several reasons. Detection rates vary across countries. The timing of the start of the outbreak varies across countries. The rate of growth of infections varies across countries. The evidence required to clear the recovered patient varies across countries. All those variables and others add incredible amount of noise to the data. The current officially stated death rates whether 1.8% or 3.4% are garbage. Completely worthless. Samples must be much larger and Conclusion Rates must be much higher for us to rely on any derived statistic.

    And this is all before we begin discounting countries based on deliberate efforts of governments to hide the true data. That is why I have reported China and Iran separately. And separately from each other. Chicoms appear to be much more competent at both containing the disease and hiding the true results than Tehran Turbans. Note that at the time of writing this, all countries with 50 or more detected cases can be counted on not consciously hiding true data and having sufficiently reliable health infrastructure to be trusted. This will change as the bug spreads.

    To summarize: we really don’t know how bad it is. It is worse than what we are officially being told but it could be a little worse or much worse, it is NOT cataclysmic worse though.

  11. Death Rate 2 = # of deaths / (# of deaths + # of recoveries)
    Conclusion Rate = (# of deaths + # of recoveries) / # of reported cases.

    Neither of those are measures used in epidemiology, the standard definitions of mortality rate and case fatality rate were given above, and your ” Death Rate 2″ completely ignores those cases where the individual is still ill (e.g., S. Korea 5900 cases left out), so it is meaningless in assessing risk, likewise the “conclusion rate” which has managed to avoid being in any of my three texts at hand, perhaps you were thinking of recovery rate.

    Recovery Rate is used, but that is recovered cases/total cases, and in the case of an epidemic is more useful after to assess both the natural history of the disease and efficacy of any interventions, particularly different interventions. At this point in time (and only this point) we can say the total recovery rate is 65%, but that is misleading because of the low case fatality rate in every major reporting population. As a further example, the recovery rate at this point in time (it could go up or down in the future) for S Korea is 135/6088 or 2.2%, whereas the CFR is 40/6088 or 0.66% so if the disease continues in S Korea as it is now, the expected recovery rate would be just short of 100%.

    Case fatality rate, whether anyone likes it or not, is a (possible the most) commonly used measure, often at the outset of a new epidemic, to assess severity of disease, usually in conjunction with the attack rate which is the number of new cases in a population at risk/number at risk in that population, and is a measure of communicability. For the sake of argument let’s assume all Hubei cases are in Wuhan and that everyone has been at equal risk, the attack rate (again as of today, it can change over time) would be 67,592/11,000,000 or 0.6% or “not much” in technical terms. That, obviously, is a bit simplistic because not everyone is at equal risk (e.g., the Seattle nursing home) but by comparison measles can have around a 90% attack rate among the susceptible.

    Other measures commonly used include incidence which is new cases – if you look at the charts in the lower right corner of the Hopkins link, you will note that the lines indicating the total number of cases is plateauing indicating that the incidence is slowing, i.e, the epidemic is slowing (though there is often a second spike).

    Finally, the disease itself – the main pathophysiological problem causing death is acute respiratory distress syndrome (ARDS), which also can happen in some cases of flu, among other causes. Not everyone develops ARDS, it appears, as mentioned before, to be a problem of those with other conditions, especially among the elderly. Barring that, ARDS is readily treatable if it is properly identified, though some people have residual lung dysfunction after. This isn’t 1918 when there were no effective treatments for the complications of the Spanish flu.

    The bottom line is if one wants to play armchair epidemiologist and scare one’s self making up “what ifs”, knock yourself out, but, having dealt with this sort of thing most of my adult life, I’m going to have another adult beverage and relax.

    1. “Neither of those are measures used in epidemiology.”

      Does not matter, this is not epidemiology, this is basic statistics. Stop hiding behind your (undergraduate ) textbooks and think instead.

      “Case fatality rate, whether anyone likes it or not, is a (possible the most) commonly used measure, often at the outset of a new epidemic, to assess severity of disease, ”

      When an epidemic just started and nearly nobody recovered or died yet, the death rate calculation you propose is meaningless. Suppose you have 100 people infected. On day one, one recovers and one dies, your death rate is 1%, on the next day two more die and two more recover. Your death rate is now 3%. It tripled! No it did not, it is still the same as on the previous day.

      “Death Rate 2″ completely ignores those cases where the individual is still ill”

      Exactly, it only looks at concluded cases. Because the individual who is still ill may either recover or die. So if you’re asking a question “how deadly the disease is” you look at the ratio of deaths to (deaths + recoveries). Not as you propose treat recovered and ongoing cases as if they were the same thing when measuring death rates. That consciously underestimates the death rate. Some of the ongoing cases will die so if we were not to get any new cases your death rate will continue climbing when some of the existing cases die off.

      “As a further example, the recovery rate at this point in time (it could go up or down in the future) for S Korea is 135/6088 or 2.2%, whereas the CFR is 40/6088 or 0.66% so if the disease continues in S Korea as it is now, the expected recovery rate would be just short of 100%.”

      No, the expected recovery rate would be 135/(135+40)=.77 or 77%. It really is simple. Not epidemiology, not bio statistics just basic intro stats.

      Coincidentally: “I am an epidemiologist” and “I have a textbook” are not arguments. If anything, you sound more like a student who has taken intro to bio stats and never analyzed data beyond assignments your professor gave you. And you probably did not get a very good grade at those assignments either. That seems especially likely given your complete lack of understanding of what the formulas I have used mean.

      Take this jewel for example:
      “Recovery Rate is used, but that is recovered cases/total cases, and in the case of an epidemic is more useful after to assess both the natural history of the disease and efficacy of any interventions, particularly different interventions.”

      After the disease is no more, recovery rate is simply one minus death rate (when death rate = # death/ # of cases) . This is not a different statistic. And no I was not trying to use it. I have explained what I was calculating and why. No I, don’t care if it is not in your textbook.

      “i.e, the epidemic is slowing”

      Nope, those graphs are weighted by Chicom cases and Chicom data is consistently doctored.

      “play armchair epidemiologist ”

      Again, this is not playing epidemiologist, this is just basic statistics. Something taught at a second year in most universities. The fact that you refer to this as epidemiology further suggests that you’re merely regurgitating your professor.

    2. To add to above: the reason global death rate estimates jumped from 1.8 to 3.4 is because they were fixating on exactly the meaningless statistic you to are clinging onto. No worries, by your logic when more people get infected your rate will go down… until they too start dying. Lather rinse repeat. Clearly, by your logic, in order to keep the death rate low one needs to keep the rate of new infections increasing exponentially over time… until we run out of humans to infect, then your rate will go up again. Damn.

      1. Colon I take great delight in the fact that you are scared out of your mind and hopefully utterly miserable in your deluded little world.

        2. Shhhh, be quiet this is outside your ability to keep up. Go play with UnMe or stuff crayons up your nose. Fine, you can stuff them there instead.

      2. No worries, by your logic when more people get infected your rate will go down…until they too start dying.

        No. I am not at all sure what part of this you are not understanding.

        A CFR is part of what describes a disease. It is a rate. With a CFR of 3% 3/100 will die, 30/1000 will die, 300/10,000 will die, and so on.

        If you go back retrospectively, almost to the start, the CFR has been hovering around 3% +/- (e.g., 2.8 as of 14 Feb, 3.4 as of 26 Feb, 3.4 as of 2 March, 3.4 today).

        By your notion, the number infected has almost doubled since 14 Feb, so somewhere in there the CFR should have gone down, but the rate at which they die is not, nor has it been, changing radically at all. As new cases are diagnosed, some previously diagnosed cases die, the rate at which this occurs is, in this outbreak to date, fairly constant.

        1. “No. I am not at all sure what part of this you are not understanding.”

          I understand everything. You should start listening instead of trying to lecture me.

          “As new cases are diagnosed, some previously diagnosed cases die, the rate at which this occurs is, in this outbreak to date, fairly constant.”

          Here we go again. This can happen only when the # of deaths increases in the same proportion as the # of cases. Then the ratio is constant.But it is too early to conclude that. Once you throw out China and Iran you simply do not have data to claim that. Bigger outbreaks in Europe just occurred. There hasn’t been enough time for them to die yet and that is where a huge chunk of your remaining data comes from. When a country has 400+ observations and 0 deaths or recoveries (ex: Germany up until minutes ago) this rate is completely irrelevant.

          1. There hasn’t been enough time for them to die yet…

            Except for the ones who have already died among the 6,100 or so cases in all of Europe, 124 in Italy could not be reached for comment.

            However, I notice that you chose to ignore the 6,983 cases and the deaths of S. Korea which, along with Europe and the rest of the world, makes up about the same as the number of cases China reported on 1 Feb – 15,000 for the rest of the world (less Iran) and a CFR of 2.3, again about what it was 1 Feb in China (2.2).

            The observation to be made at this point is, though it appears that the trajectory of the epidemic outside of China is very much similar to that of inside of China (but lagging a month), knowing the disease exists, and therefore implementing improved preventive measures, surveillance, and earlier detection and intervention, likely help account for the lower number of deaths in S. Korea, Italy, and elsewhere.

          2. “Except for the ones who have already died among the 6,100 or so cases in all of Europe, 124 in Italy could not be reached for comment.”

            Yes, exactly those are still tiny samples and yes exactly why your method of calculating death rates sucks. Your current estimate of death rate in Italy is 197/4636=.04 or 4% Suppose there would be no new infections in Italy. The only way you could maintain that death rate is if not one more of the existing cases died. Only 523 people recovered. That means you still have 3916 and all of them cannot die for your estimate to be accurate. I really can’t be bothered to explain it again.

            “However, I notice that you chose to ignore the 6,983 cases and the deaths of S. Korea”

            No I did not, which is why I reported results for South Korea.

            Speaking of South Korea, their death rate is 42/6593=.006 or 0.6%.
            So now you have 4% in Italy and 0.6% in SK. Tell me again how 3.4% (that used to be 2%) is representative of either large sample? It isn’t. How wide do you need a confidence interval around this estimate to include both numbers? And that brings me back to my original point: the current method of estimating death rates is garbage. No I don’t care if your prof and your textbook say otherwise.

    3. ” if you look at the charts in the lower right corner of the Hopkins link, you will note that the lines indicating the total number of cases is plateauing indicating that the incidence is slowing, i.e, the epidemic is slowing”

      That aged well.

  12. Does not matter, this is not epidemiology…

    Yes it is, epidemiology is the way one studies diseases especially when analyzing outbreaks, not by made up things like “concluded cases”.

    …the death rate calculation you propose is meaningless.

    I am not “proposing” anything, I am using a standard measure. Once again – Case fatality rate=deaths from a given disease/all cases diagnosed with the disease; dead/diagnosed, nothing else. I am sorry you don’t like it.

    100 people are infected=100 cases. Day one, one dies, one recovers, 1 death/100 cases = CFR of 1%. The next day two more die, the CFR is 3/100 or 3%. If everyone else recovers, the CFR was still 3%.

    That is how it is calculated dead/diagnosed, you don’t remove recovered from the denominator. The CFR is not dead/recovered. You don’t get to change it, or make just up some alternative because it fits what you want to believe.

    In the present outbreak, the CFR has remained fairly steady hovering in the 3% range both in the Chinese reported numbers, and the cumulative numbers reported by the rest of the world (that the Chinese don’t massage).

    Not epidemiology, not bio statistics just basic intro stats…After the disease is no more, recovery rate is simply one minus death rate

    Look, once more, you can’t just make up your own definitions. Recovery rate = recovered cases/all cases not recovered + dead/all cases, or 1-“death rate”.

    Nope, those graphs are weighted by Chicom cases and Chicom data is consistently doctored.

    The yellow line at the bottom – “All other locations”. That means not Chinese, not doctored by them.

    If anything, you sound more like a student who has taken intro to bio stats and never analyzed data…

    As I said, you can feel free to make up stuff all you want, I’ve been doing this most of my adult life and everyone else is invited to look up the definitions, (they won’t find yours) or see how other people in the medical community are using CFR and other epidemiological tools (lots more like that) to study this outbreak.

    1. “Yes it is, epidemiology is the way one studies diseases especially when analyzing outbreaks, not by made up things like “concluded cases”.”

      It is not a made up thing, it is a simple ratio. I have explained what it measures and why I used it. Once again for the cheap seats: I used the Conclusion Rate to illustrate how unrepresentative those samples of dead and recovered cases are and how useless the death rate formula you propose is in this situation.

      “I am not “proposing” anything, I am using a standard measure. Once again – Case fatality rate=deaths from a given disease/all cases diagnosed with the disease; dead/diagnosed, nothing else. I am sorry you don’t like it.”

      Yes, you can repeat yourself again if you like. You can do it ad infinitum. It still does not change the fact that this measure is useless when 95% of cases are neither dead nor recovered. Get it through your skull, saying “because it is how things are being done” does not help your case.

      “You don’t get to change it, or make just up some alternative because it fits what you want to believe.”

      Of course, I get to change it. I document the changes, I don’t pretend they measure something else and get to change it. Everyone can do it. There is nothing sacred of advanced about this ratio. It is just that, a simple ratio, nothing more. And it is an arbitrary and biased measure of true death rate unless you are measuring historical events.

      “In the present outbreak, the CFR has remained fairly steady hovering in the 3% range both in the Chinese reported numbers, and the cumulative numbers reported by the rest of the world”

      Not true https://www.cnbc.com/2020/03/03/who-says-coronavirus-death-rate-is-3point4percent-globally-higher-than-previously-thought.html

      “Look, once more, you can’t just make up your own definitions. Recovery rate = recovered cases/all cases not recovered + dead/all cases, or 1-“death rate”.”

      Omg are you seriously that dense? Assume you have 100 cases, 75 recovered and 25 died. Death rate = .25, recovery rate = .75. 1- death rate = recovery rate. It really isn’t rocket science, it is not epidemiology either. For homework see what happens when death rate is .20 and recovery is .80?

      “The yellow line at the bottom – “All other locations”. That means not Chinese, not doctored by them.”

      Yes, and it is upward sloping and convex. The rate of growth increases. The second derivative is positive.
      It has always been concave on the last day segment of the curve and convex until then. That is because data from the last day takes a day or two to trickle in, given the number of sources they collect it from. Once updated it becomes convex again. Please don’t tell me you did not know even that. Look at it in 24 hours, you’ll see.

      “As I said, you can feel free to make up stuff all you want, I’ve been doing this most of my adult life”

      Don’t believe you. I have been analyzing data my entire professional life. You come across as someone who never actually written a line of code. Never loaded raw data into statistical software and always hid behind formulas because thinking what they mean was too hard. It is either that or you are just a student pretending to be an accomplished epidemiologist.

  13. all I am concerned about is that from the base data my age and underlying condition means I have about a 9% chanced of dying from this. I think I will stay home for a few weeks.

  14. … never actually written a line of code. Never loaded raw data into statistical software and always hid behind formulas…

    Being able manually to dredge through raw data and to calculate things using proven methods and formulæ instead of just shoving numbers into a computer is not exactly the insult you think it is.

    Not true…

    I see. To you 3.4 is not in the 3%+/- range, or, as I said earlier,

    …the CFR has been hovering around 3% +/- (e.g., 2.8 as of 14 Feb, 3.4 as of 26 Feb, 3.4 as of 2 March, 3.4 today).

    OK, then.

    Get it through your skull, saying “because it is how things are being done” does not help your case.

    My skull, and the skulls of the entire infectious disease and epidemiological communities who do things that way as evidenced by any number of reports and papers written to date about the outbreak.

    Being, as you apparently fancy yourself, to epidemiology what Galileo was to astronomy, you should probably quit wasting your time here and go about straightening them all out with your “Conclusion Rate” (along with your carburetor that gets 100 mpg on water) because you, and only you, know more than them and can with perfect geometric logic prove the messboys made a copy of a key to eat the stolen strawberries.

    1. “Being able manually to dredge through raw data and to calculate things using proven methods and formulæ instead of just shoving numbers into a computer is not exactly the insult you think it is.”

      Except that you’re not dredging through any data. And when I did that you nearly had an aneurysm, and screamed “nein nein nein textbooks”. And that is all you have been repeating again and again.

      “I see. To you 3.4 is not in the 3%+/- range, or, as I said earlier,”

      The link I gave you clearly states that the official, divine, and the only one to be used by true scientists and epidemiologists estimate used to be 2% and now is 3.4%. 2% is not in 3% range. and icnrease from 2% to 3.4% is a 70% increase over the initial estimate. Do try to keep up and read beyond first few syllables.

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