Exploring regulatory data sets of the Comirnaty vaccine - 11f
Where’s the plague?
Yes, we are back on the Comirnaty series; even old geezers need some light relief.
This post is brief; the first part has a background, some facts, and a question. There’s a short second part with what we think is remarkable about the facts. Not clear? Wait.
Part 1
In July 2024, we posted this, 11d in the Comirnaty series:
In it, we explained some of the uses of data from placebo arms in randomised controlled trials. Although controlled (as in, run by researchers following a protocol) and on selected populations, placebo arms tell you much about what is going on without the intervention (drug, vaccine, device, whatever). A real placebo is an inert substance that is visually the same as the real stuff. In the Comirnaty case, it was a saline placebo.
So in 11c
and 11d, we looked at the definition of the effectiveness outcomes (vague) and the incidence of Covid according to the Pfizer BioNTech trial, which was very low. At the time, we were looking at mid-2021 data presented to regulators.
The panic meter was in the red, and consequently, Comirnaty had received an EUA or CMA (regulatory speak for emergency registration on both sides of the Atlantic); by now, you know these cussed respiratory viruses obey Farr’s Law; they go up, and they go down. So maybe this was a predominantly down phase (never mind the panic meter run by the media and CDC).
However, one night, a clinical study report fell into our laps. While we typically enjoy diving into such extensive documents—often spanning tens of thousands of pages—let's be honest: we immediately focused on the Integrated Summary of Efficacy BNT162b2 (Part 2.7.3), which contained all the essential information we needed.
Our eyes fell on this:
The table screams at you that vaccine effectiveness is very high, over 95%. But in reality, when the table was assembled in November 2020, it showed more or less the same as the later table: 165 cases 7 days after dose 2 in 18,570 people, i.e. roughly 9 cases per 1,000 weekly.
So, where’s the plague gone?
Part 2
This case rate is almost certainly an overestimation. The definitions reported in the clinical study report and those used by the EMA in its EPAR have no cutoff for the likelihood of viral load; hence, infectivity is assumed, not proved. Many so-called cases could be contaminated or past-infected and do not exclude co-infection with another agent.
No one remarked on this strange phenomenon, not the EMA, the FDA, or the secret squirrels of the MHRA, who were supposed to examine the harms data. However, to make a decision, you have to assess benefits-to-risk ratios. At low case rates, the plague disappears, making the relative measures look impressive. This means that any absolute expression of the effect also disappears.
For more background, also see this:
Does it work? (4) A response to Chad’s comment
Two puzzled old geezers wrote this post.
So, allow me to surface. RRs are like a whirlpool: I tend to drown rather than keep up w the flow of information. But I gather their purpose is to inform us of hypothetical risk of suffering ill health following infection by the hypothetical germ called Covid-19 if ‘vaccinated’ with the concoction under scrutiny ie Comirnaty versus the same risk if not so ‘vaccinated’. And at a point in time vaccine ‘efficacy’ can look stronger than it does if you take into account the cumulative effects of the course of infection in the population over time, and logic demonstrates the ‘vaccine’ effectiveness is likely overstated by the efficacy figures from the trials.
Then there is the small but sticky consideration of how we know someone has a case of Covid or not. And there is a bit of tail-chasing here in that your study review illustrates that there are a range of symptoms and signs of Covid infection, but no one sign or symptom is unique to Covid, all being found a multitude of common respiratory illnesses.
Furthermore the symptoms are not uniformly found in all cases identified as Covid via the rt-PCR test.
And the rt-PCR itself is incapable of differentiating between whether DNA scraps are currently infecting and producing the illness felt by a sick person, or are leftovers from a historic covid infection no longer affecting the person, or are present without a person having ever had any symptoms.
Then to top it off, it didn’t spread like a highly contagious virus is expected to.
So all in all, this suggests the virological evidence relating to the so-called pandemic, Covid-19, is dodgy in the extreme. Have I got all that right?
2 points.
The lottery ticket analogy helped me to understand RRR & ARR better.
Take a lottery with 10 million players. If I buy a 2nd lottery ticket I improve my ARR of winning by 1 in 5m, - terrible odds, why bother.
However, my RRR has doubled, - good odds, I'll have some of that!
Secondly.There was a lot of speculation about the false positive rate of lateral flow tests. It was often cited at 0.8%. Clearly, with a positive rate of 0.9% in the trial period, quoted above, the influence of false positives was significant in the population in general. With PCR tests the cycle threshold potentially achieved the same effect by inflating 'case' numbers.