The COVID Debacle has been characterized as a ‘clown show’ such as that in the circus when 35 clowns sequentially come out of a parked, compact car. It is too much to be believed.
A helpful tool would be something that let’s you determine when it’s logically proper to rule out or exclude a statement that is made, potentially dismissing it as being actually absurd in the process.
By implication, the speaker may then need a “hearing” in the court of public opinion.
A Coin Flip
Any two statements can be compared for absurdity, or more precisely, for whether the existing evidence allows for you to rule them out of a rational, problem-centered, solutions-based discussion. Here are two simple statements:
This coin is a fair coin. It will turn up heads 50% of the time that it is flipped.
This coin is not a fair coin.
After a certain level of evidence, one or the other of these statements will be able to be ruled out or dismissed with. A good rule of thumb — good enough to settle legal proceedings regarding paternity tests — is to carry on an experiment of coin flipping until the probability of finding the evidence dips below 1 in 20,000, or p < 0.00005.
If nothing but heads (or nothing but tails) show up in every coin flip, then you would need to see 16 heads in a row, or 16 tails in a row, in order to rule-out that you have a fair coin (probability: p = 0.00003).
Probabilities higher than that — such as 14 heads in 14 coin flips — are not “small enough” to rule out that you have a fair coin. Too many of the coins in circulation really are fair ones, so you have to set the cutoff point lower to account for that.
Knowing when you do not have enough evidence to rule something out is also helpful.
Paternity Test Probabilities are a good guide
In this Substack, it is argued that a statement has to have at least 1 chance in 20,000 of being true of the world, in order to be acceptable material for rational discussion. An impetus for that figure is a report about when it becomes proper in a legal paternity case (involving genetic testing) to say that a defendant has been, for all practical purposes, “proven” to be the father.
Three possible levels of “proof” are:
proof beyond the shadow of a doubt (e.g., no squares are round)
proof for all practical purposes (e.g., this man is proven to be the father)
evidence that does not reach the level of proof (e.g., most findings of science)
A quote from C.S. Pierce is “It is easy to be certain. One has only to be sufficiently vague.” It is when we try to get precise in our language that we can make the mistake of saying things which, on further review, can be ruled-out, and possibly even as being absurd.
The COVID models which were used in order to justify lockdowns, for instance, postulated that the infection fatality rate (IFR) for COVID was 0.9% (1 death per 111 infections). Can that claim be ruled out, and even characterized as absurd?
Let’s let the evidence speak for itself.
To do that, I took 52,000 COVID infections which had been tracked by the UK government over time (to see who died within 28 days). Adjusting the deaths up to account for deaths which occur beyond Day 28, I ran 100 million computer simulations to see which IFR values were capable of reproducing the known evidence:
[output of R software; click image to enlarge]
The central estimate of the true IFR of COVID (wild-type/Alpha variant) was 0.23%. To capture the middle 99.99% of all probability, I added a 99.99% Bayesian Credible Interval — which maxed out at 0.3%.
The IFR in the COVID models was 3 times higher than the highest IFR value that has a realistic (greater than 1 chance in 20,000) chance of being true. Not only can an IFR of 0.9% be ruled out of a rational, problem-centered, solutions-based discussion — but it is also patently absurd.
Given the sharp reduction in probability on the histogram for IFR values in the right side of the image above, an IFR of 0.9% would have much less than a 1-in-a-trillion chance of being true.
Note:
Estimate of the probability that the Tony Fauci/Neil Ferguson IFR of 0.9% is rightWhen you look on a probability distribution called a “Poisson distribution” — and you use the expected deaths in 52,000 infections that the 0.9% IFR represents (n=468 deaths) — then the chance of witnessing the 117 deaths (the actual UK deaths) actually happening is 4.95 * 10^-84.
That’s 83 zeroes after the decimal place, before the “4” shows up. Besides the physically impossible things (e.g., round squares, etc), there are very few claims which have THAT low of a chance of being right.
There are not many claims under the sun which can be said to be as absurd as the claim that the IFR of COVID is 0.9%. Most claims aren’t that unhinged from reality.
When the COVID modelers said the IFR was that high, it would have been proper to tell them that that is absurd, and to go back to the drawing board — and to not come back — until they have a model which has at least 1 chance in 20,000 of being accurate.
Critics and detractors may complain that it looks like I’m adopting the position of a “Monday Morning Quarterback” (someone with full perspective on the Sunday Night football game, criticizing what players did).
They’d say this because the proof that COVID wasn’t even a third as deadly didn’t come out until the end of January 2021 — while the COVID models came out by March of 2020.
But though the death count (d=7) was small, data from the Diamond Princess Cruise Ship had already excluded the possibility of an IFR as high as 0.9%. IFRs that high could ALREADY be ruled out — i.e., “not even 1 chance in 20,000 of being true” — by known evidence.
Other Statements, and What it All Means
Some other statements which can be put to the test are things like “COVID is 10x worse than flu” (Fauci, Mar 2020) and the repeated mantras of “Masks slow the spread of COVID” and “These shots are safe and effective" and on and on and on.
Even the COVID death count claimed by the WHO for the Diamond Princess Cruise Ship doesn’t have even 1 chance in 20,000 of actually being true. It doesn’t even have 1 chance in 200,000 of being true.
Was there ever a time when the officials were sitting on enough evidence to rule out the contrary statements that COVID is no more than twice as bad as flu, that masks do NOT slow the spread, and that those shots were NOT safe and effective?
That question is rhetorical.
If most of the official statements made in the COVID years can be ruled out as not having any realistic probability of being true of the world, does it mean that the officials making them are “dumb”? No. The statements made are only “apparently dumb.”
Only if you assume the speaker has the same priority of values that you do, can you say that they “spoke stupidly” or something like that.
A Naive View of Perpetuated Human Errors
Here is an over-simplified flow-chart which may lead you to that conclusion though:
This chart only has 3 final options: Dumb, Duped, or Evil. But reality is more complex than that, so the bottom right of the chart needs to be expanded.
An Advanced Model to Explain Sustained Absurdity
Here is the modified chart which captures more of the reality faced in the world:
Bad actors get good at what they do, so good that you can’t even tell that they are there, or that they are behind things. It is said that the greatest trick the Devil ever pulled is convincing others that he did not exist.
But behind a lot of the “apparently dumb” statements made in the COVID era, there is likely to be a lot of people who have been compromised by dark interests. This flow chart shows 4 ways that that can be done to people.
Reference
[99.99% probability represents “practical proof” in court cases] — Veselinović I. [Microsatellite DNA analysis as a tool for forensic paternity testing (DNA paternity testing)]. Med Pregl. 2006 May-Jun;59(5-6):241-3. Serbian. doi: 10.2298/mpns0606241v. PMID: 17039906. https://pubmed.ncbi.nlm.nih.gov/17039906/
Conclusion: The probability of paternity of 99.99% or higher corresponds to the paternity "practically proven", …
[As of 19 Jan 2021, from 52,000 COVID infections with Alpha (SGTF) variant, there were 104 deaths by Day 28 (corrected to 117 total deaths, by using Linton et. al., leads to IFR=0.225%)] — Page 3. Epidemiological findings. UK Technical Briefing #5. https://www.gov.uk/government/publications/investigation-of-novel-sars-cov-2-variant-variant-of-concern-20201201
[“Time-to-death” model for COVID; using the 95% UB of both the mean and SD of the lognormal model that fit the actual deaths best] — Linton NM, Kobayashi T, Yang Y, et al. Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data. Journal of Clinical Medicine. 2020 Feb;9(2). DOI: 10.3390/jcm9020538. PMID: 32079150; PMCID: PMC7074197. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074197/
[WHO COVID-19 Situation Report #72 on 1 Apr 2020 showing 7 Diamond Princess deaths 46 days after all passenger infections had occurred] — WHO. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200401-sitrep-72-covid-19.pdf
[WHO COVID-19 Situation Report #88 on 17 Apr 2020 showing 13 Diamond Princess deaths, 6 of 13 occurring after it became unrealistic for them to occur] — Available from: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200417-sitrep-88-covid-191b6cccd94f8b4f219377bff55719a6ed.pdf
[The Diamond Princess Cruise Ship IFR] — That first “Natural Experiment” of COVID. Deep Dive Substack.
[Masks are not protective] — Revised “Masks can possibly kill you” Substack. Deep Dive Substack.
[COVID jabs are not protective] — Medical NewSpeak. Deep Dive Substack.
[Jabs more likely than COVID to explain excess death] — Official Narratives vs. Truth. Deep Dive Substack.
[probability that Fauci was right about it being 10x worse than flu is 1-in-29 trillion] — Probability and Lies. Deep Dive Substack.
Great post...making stats understandable for the untrained!