My last post had some pictures to remind us that we’re not in Kansas anymore - Lord only knows where the hell we actually are, but we need to tap the red shoes and get back home again. In this post I’d like to discuss some of the charts, old and recent, that have been generated to illuminate (or obfuscate) the course of this (cough, cough) pandemic.
The Telegraph chart made me LOL. Good for them. Reminds me of a graphic I saw on another paper's website that purported to show how covid spreads using a bunch of little dots that bumped into each other and changed color. If people can look at such things and think, "Brilliant! Now I understand viral transmission," no wonder they consider themselves experts on the Glorious Goo because they read about how messenger RNA works in the Times.
I guess they have to "model" because if they presented actual data (as in the rest of the charts you show), they couldn't claim the sky is falling and that the only cure is the GG.
I saw this morning that in the UK and the USA "they" are trying to pass laws against protesting, peaceful or otherwise. What seems to be coming upon us all is what has me fearful and anxiety ridden. God save us all!
Last graph seems a little sticky (gooey?) as far as interpretation is concerned. The higher gradient in numbers for the vaxxed probably also reflects age- and ill health-selection; i.e., those resorting to vaccination are, with little doubt, relatively more feeble (and anxious) to begin with, and so are more prone to die than the few remaining non-vaxxed. Also, acquired immunity for this self-selected (and doctor-selected) group is generally harder to establish (T-cells? T-cells? Where are my T-cells?), and, admittedly, the added stress of demanding a immune response by vaccination probably doesn't help this relatively feeble group of people sail along unharmed, either. (I think I recall the author of this last chart in this post making some of these same qualifications about this particular chart of his).
Keep these coming. Your calm, scientific and amusing approach helps enormously. I still struggle at containing my incredulity that people can’t see what is so obvious.
The difference in gradient might be due to confounding: both vaxx rate and infection fatality rate increase with age.
That notwithstanding, very good points! A few slightly technical remarks:
1. What is considered a model in public discourse would be called a scenario in financial risk management (about which I know a thing or two). The second crucial component of a model that tries to capture some of the uncertainty in the world is the choice of risk measure. Create many scenarios, assign probabilities, build a distribution, and read off a risk measure (such as 95% quantile, typically for market risk, or 99.9% quantile, typically for credit risk).
2. The pick-2020 quiz would turn out similarly for Germany, even after you consider the ageing population. If you apply the age-stratified death rates 2011-2019 to the population as of end of 2019, the real 2020 will be right in the middle of the fake 2020s.
3. Whatever the actual IFRs, the fact that they increase exponentially with age should have serious implications on vaccination strategies (in particular, when to stop vaccinating; I played with this on my substack: https://cm27874.substack.com/p/credit-for-covid).
5. If you repeat the quiz (2.) for, say, all the monthly October data 2011-2021 for Germany, even after removing Covid deaths, October 2021 will clearly stand out:
2011 : 71825
2012 : 72543
2013 : 71780
2014 : 72597
2015 : 74854
2016 : 76001
2017 : 75229
2018 : 74039
2019 : 77006
2020 : 79781 (thereof 1488 Covid)
2021 : 83699 (thereof 2314 Covid)
On Tuesday, data for November will be published by destatis, and I predict them to be even more worrying.
that 20 year all cause mortality graph is truly mind-shattering. Just wondering: What does "age adjusted" mean regarding all-cause mortality and why is age-adjustment needed?
Excellent and very entertaining, the way that evidence should be presented and the ridiculous made apparent!
(I have some reading to catch up on, I noticed. I literally had to take a break from everything COVID for a few days.)
The Telegraph chart made me LOL. Good for them. Reminds me of a graphic I saw on another paper's website that purported to show how covid spreads using a bunch of little dots that bumped into each other and changed color. If people can look at such things and think, "Brilliant! Now I understand viral transmission," no wonder they consider themselves experts on the Glorious Goo because they read about how messenger RNA works in the Times.
I guess they have to "model" because if they presented actual data (as in the rest of the charts you show), they couldn't claim the sky is falling and that the only cure is the GG.
Solid stuff, that, Rudolph. Thankyou. Great point on gradients.
great article
I saw this morning that in the UK and the USA "they" are trying to pass laws against protesting, peaceful or otherwise. What seems to be coming upon us all is what has me fearful and anxiety ridden. God save us all!
Last graph seems a little sticky (gooey?) as far as interpretation is concerned. The higher gradient in numbers for the vaxxed probably also reflects age- and ill health-selection; i.e., those resorting to vaccination are, with little doubt, relatively more feeble (and anxious) to begin with, and so are more prone to die than the few remaining non-vaxxed. Also, acquired immunity for this self-selected (and doctor-selected) group is generally harder to establish (T-cells? T-cells? Where are my T-cells?), and, admittedly, the added stress of demanding a immune response by vaccination probably doesn't help this relatively feeble group of people sail along unharmed, either. (I think I recall the author of this last chart in this post making some of these same qualifications about this particular chart of his).
Keep these coming. Your calm, scientific and amusing approach helps enormously. I still struggle at containing my incredulity that people can’t see what is so obvious.
The difference in gradient might be due to confounding: both vaxx rate and infection fatality rate increase with age.
That notwithstanding, very good points! A few slightly technical remarks:
1. What is considered a model in public discourse would be called a scenario in financial risk management (about which I know a thing or two). The second crucial component of a model that tries to capture some of the uncertainty in the world is the choice of risk measure. Create many scenarios, assign probabilities, build a distribution, and read off a risk measure (such as 95% quantile, typically for market risk, or 99.9% quantile, typically for credit risk).
2. The pick-2020 quiz would turn out similarly for Germany, even after you consider the ageing population. If you apply the age-stratified death rates 2011-2019 to the population as of end of 2019, the real 2020 will be right in the middle of the fake 2020s.
3. Whatever the actual IFRs, the fact that they increase exponentially with age should have serious implications on vaccination strategies (in particular, when to stop vaccinating; I played with this on my substack: https://cm27874.substack.com/p/credit-for-covid).
5. If you repeat the quiz (2.) for, say, all the monthly October data 2011-2021 for Germany, even after removing Covid deaths, October 2021 will clearly stand out:
2011 : 71825
2012 : 72543
2013 : 71780
2014 : 72597
2015 : 74854
2016 : 76001
2017 : 75229
2018 : 74039
2019 : 77006
2020 : 79781 (thereof 1488 Covid)
2021 : 83699 (thereof 2314 Covid)
On Tuesday, data for November will be published by destatis, and I predict them to be even more worrying.
that 20 year all cause mortality graph is truly mind-shattering. Just wondering: What does "age adjusted" mean regarding all-cause mortality and why is age-adjustment needed?