Ioannidis pushes circular ‘safe and effective’ vaccine assumptions
Imagine that we want to test the claim that a special diet – let’s call it D – that consists of consuming 10,000 calories a day without any exercise will lead to weight loss of 50 pounds in five weeks
To make such a bold claim you would expect us to examine the evidence by comparing the recorded weight of people before and after being on the diet.
But suppose instead our ‘evidence’ is nothing other than following mathematical model:
Weight loss after n weeks in pounds = n x efficiency_D
where efficiency_D is the average weekly weight loss of diet D.
Suppose further that we assume:
efficiency_D = 10
Then, with these assumptions we compute
Weight loss after 5 weeks in pounds = 5 x 10 = 50
QED! We can now trust the claim that the special diet D does indeed lead to weight loss of 50 pounds in five weeks and we can believe this with full certainty (hand on heart).
Would you be convinced by this argument? Or would you be very uncomfortable and highly suspicious that there is some sleight of hand here?
Bearing in mind the objective of the study is to test the claim don’t you find it odd that the main assumption in the model (namely efficiency_D = 10) is essentially the very claim we are endeavouring to test?!
Isn’t it all a bit circular and self-serving?
Well, it turns out that a study claiming to test the claim that the covid vaccine has saved millions of lives (just like a previous study from Imperial) is based not on any comparison of empirical mortality data between populations of vaccinated and unvaccinated, but rather on the above ‘scientific’ methodology.
This scientific study applied the same highly sophisticated logic and similar circular assumptions used to test the claims about the special diet, D, namely that:
- Without vaccination Covid infects and kills a lot of people.
- The vaccine is effective; specifically, people who do not get the vaccine are four times more likely to get covid than those who do.
- The vaccine is perfectly safe, i.e. nobody dies as a side effect from the vaccine.
Here is the paper. Take special note of the identity of the first named author:
The first named author of this paper is none other than one of the most highly respected scientists in the world, John Ioannidis of Stanford University, who used real-world data in 2020 to demonstrate that Covid was nothing like as deadly as was being claimed.
And here, in its entirety, is the mathematical model contained within the paper which was used to claim that 14.8 million life years were saved by the vaccine:
For each population age group, the number of lives saved L in that age group is:
L = N x PI x IFR x VE
Where:
- N: number of people in that age group
- PI: number of people in that age group who (absent a vaccine) would be infected with covid
- IFR: infection fatality rate in that age group (i.e. the proportion of people infected who die)
- VE: the vaccine efficacy in the age group (which is one minus the ratio of the percentage vaccinated who get covid and the percentage unvaccinated who get covid)
With the exception of N, each of the actual values assumed in the equation are fanciful, being based on a myriad of unproven the assumptions, such as that Covid ‘case’ numbers were accurate.
Specifically:
- PI is assumed to be 20 percent (i.e. in the absence of the vaccine it is assumed 20 percent of the population are assumed to have got Covid).
- IFR in each age group is based on Ioannidis’s work which showed that the elderly were at much higher risk; but the values are still based on the (flawed) assumptions that those classified as being Covid cases did in fact have the disease and those that died did indeed die from Covid disease.
- The VE is based on the assumption that those classified as Covid cases did in fact have the disease. More importantly, the data used is based on studies that we have shown are systemically flawed. Likewise, the paper assumes (pre-Omicron) that VE = 75 percent, i.e. that an unvaccinated person is four times as likely to get covid than a vaccinated person. This is nonsense.
While a number of people have publicly criticised the paper, one point that nobody seems to have raised is that it does, unwittingly, demonstrate an extremely important point, namely:
Since no real-world data provide evidence that the vaccines saved lives then we know that the estimates of vaccine effective – such as the 75 percent assumed in the study – are, empirically, wrong.
Perhaps this was the real discrete conclusion that Ioannidis hoped would be inferred from the paper? If not, why would he wish to be associated with garbage work operating under the misnomer that it is genuine ‘research’ is inexplicable if not mysterious.
The front cover of the paper states that there was no funding or conflicts of interest associated with the paper, although it states that “The work of John Ioannidis is supported by an unrestricted gift from Sue and Bob O’Donnell to Stanford University.”
Although this Ioannidis paper has not yet been peer-reviewed it is already being used as ‘overwhelming evidence’ of how great the vaccines were.
The 2022 Imperial paper, which claimed 20 million lives saved by the vaccine, was published in no less a journal than the Lancet despite being based on similar circular ludicrous assumptions.
It has since been used in multiple reports and high-level forums as justifying the motivation to push for the continued roll-out of the vaccine.
As explained in this brief video we cannot simply ignore or laugh at such nonsense:
Update: Jessica Hockett has written an excellent article about Ioannidis’s questionable record of covid papers.
Update: The comment by Francesco Pansera on this article provides some very interesting background on the Italian co-authors of the Ioannidis article.
Update: Fred Stalder has written an excellent letter to Ioannidis here.
Update: Ronald Meester has done a comprehensive review of the Ioannidis article.
See more here substack.com
Please Donate Below To Support Our Ongoing Work To Expose The Lies About COVID19
PRINCIPIA SCIENTIFIC INTERNATIONAL, legally registered in the UK as a company 
incorporated for charitable purposes. Head Office: 27 Old Gloucester Street, London WC1N 3AX.
Trackback from your site.
Jerry Krause
| #
Hi Martin Neil and Norman Fenton and PSI Readers,
Martin and Norman have written an article about ‘circular reasoning. What they seem not to recognize is that Ioannidis and his followers do not recognize what they are doing. Ioannidis, and his followers, believe every word he writes as he does this very common thing which is commonly termed “circular reasoning”.
I realize Martin and Norman are not at all likely to read this but if you read this you are reading this about what Richard Feynman spoke to members of the Nation Academy of Science at its 1955 autumn meeting about “The Value of Science”. This address has been published at the end of his book “What Do You Care What Other People Think?” in 1988.
Midway through the address he stated: “I would now like turn to a third value that science has. It is a little less direct, but not much. The scientist has a lot of experience with ignorance and doubt and uncertainty, and this experience is of very great importance, I think. When a scientist doesn’t know the answer to a problem , he is ignorant. When he has a hunch as to what the result is, he is uncertain. And when he is pretty darn sure of what the result is going to be, he is still in some doubt. We have found it of paramount importance that in order to progress we must recognize our ignorance and leave room for doubt. Scientific knowledge is a body of varying degrees of certainty–some most unsure, some nearly sure, but none absolutely certain.”
In his book he continues this theme for 3 pages and concludes: “It is our responsibility as scuientists, knowing the great progress which comes from a satisfactory philosophy of ignorance, the great progress which is the font of freedom to teach how doubt is not to be feared but welcomed and discussed, and to demand this freedom as our duty to all coming generations,”
I doubt that Feynman fore saw in 1988 where we could be in 2024; but maybe he did.
Have a good day
Reply
Wilson Sy
| #
Exactly the same type of circular argument has been used in climate models to “prove” global warming – the assumptions contain the conclusion. Few understand science where all models are wrong, but some are useful.
Reply
Jerry Krause
| #
Hi Wilson,
Reproducible observations can prove WRONG models (ideas, theories) to be absolutely wrong. Galileo proved by dropping, at the same time, two bodies, with significantly different (10-1) masses, from a high place and observed that they both struck the ground near the same time. Hence, the general idea that things twice as heavy, did not fall twice as fast was wrong.
Darwin proposed that many, many very small changes over a period of billions of years could create life. However, I pointed to the commonly observed fact that the first female bird, to lay a fertile egg, had to sit on the egg to keep it warm (incubate it) for any little bird to hatch. Hence, Darwin’s idea had to be absolutely WRONG.
A scientist, whose name I cannot remember has stated we scientists only do experiments to prove our ideas are wrong. For if an experimental result does not prove this; the idea remains a possibility.
Have a good day
Reply