Analysis of the antibody testing data from the #Pfizerdata dump shows that their "too good to be true" graph - and the famous "95% prevention of infection" claim cannot be real.
You see, the claim was that 162 people in the placebo group got #covid19 *infection* but only 8 in the BNT162b2 group - a 95% reduction.
So was there another way to test infection rates?
Yes. N (nucleocapsid) antibodies.
So since the #Pfizerdump and #site4444 discovery a few of us have been beavering away looking at their own data - which is a mess - and trying to corroborate it.
Here is the N-antibody data from their "adva" file
[warning - it takes some work to get this data]
Note that both groups are similar (we have checked they are not statistically different) EXCEPT in the group which were NEG for N-antibody at the start of the trial, and POS for N-antibody at Visit 3 (1 month after dose 2)
i.e. they were infected with #covid19 in that time
That group (NEG->POS) reflect the groups that got infected with #SARCOV2 during the study period.
Well that's interesting... because the number in the placebo group is similar to the magical 162, but instead of 8 in the vaccine group - there are 75!
On the face of it the vaccine is still "working" (just) because the vaccine efficacy here is about 53% - nowhere near 95%.
But it's worse, because the vaccinated don't produce N-antibody at the same rate as the unvaccinated.
In fact the rate of N-antibody between vaccinated ( with mRNA) and unvaccinated who were known to have #covid19 infection was 40% vs 93%
That is, the vaccinated produce N-antibodies 2.3x less often during infection than the unvaccinated.
Which means we have to adjust the number of patients who tested positive at the 1 month post-vaccination point upwards by 2.3x giving us this:
At best there is NO difference between the groups (the treated group seem to do worse, but it's not significant)
In fact, anything over 130 in the Bnt162b2 group here would mean there was NO significant difference in documented infection rates (chisq p<0.05), so even if the multiplication was a conservative 2.0x instead of 2.3x, there would be no difference
@JesslovesMJK
Presumably they thought nobody would notice. And they could claim that there was a 95% reduction in infection rate - based SOLELY off a PCR test that they controlled in their own lab.
Unfortunately, we did. Their own data says that was false.
Here's the ADVA data file (zipped .csv) for those that are really interested in looking at this for themselves. Converted from the relevant xpt file at ICANdecide.org
Update: Because there are a few people making the same mistake, I'll try and clarify. The sponsor only ever claimed that there was a 95% reduction in "cases" which they defined as being a positive PCR test conducted in their own lab.
@sonia_elijah
This is also strange.
The Quentin registry study shows a big jump in vaccination rate by age group but the Bernard study doesn't show the same.
This is more like what a synthetic data set might show based on assumed characteristics of the underlying data.
There are possible explanations for all of these anomalies, but this is the problem with secret registry data:
It's not credible when it conveniently matches a narrative and nobody is allowed to see it.
I'm going to explain why this chart is so important and why @jsm2334 is being disingenuous by ignoring it - whilst making points that undermine the "real world vaccine data" industry.
It's a Kaplan-Meier curve and it obliterates Jeffrey's argument.
Just to go over it... the lines show what proportion of subjects (children) ended up without chronic disease up to 10 years after being studied.
It's called a survival analysis because it's used for cancer survival.
If the red line was a cancer drug it would be a blockbuster
It shows that by the end of the 10 year follow-up, of those that they could still follow up (who stayed in the study) 57% (100-43%) of vaccinated kids had chronic disease (e.g. asthma) and 17% (100-83%) of unvaccinated kids did.
Janet Diaz was the person that led the #MAGICApp guideline committees that stopped your grandma getting antibiotics for her post-viral pneumonia, leading to her death.
But she did this with the help of @pervandvik who deleted his account
Diaz here tells you that COVID kills you by an overreacting immune response, but that was never true.
She was an intensivist recruited by the WHO in 2018.
None of this was true, but it sold a LOT of drugs and killed a LOT of people
Which US govt organisation blew a hole in the ozone layer in 1958 by sending atomic bombs to the troposphere over the Antarctic in operation Argus - then blaming the resulting destruction of ozone on CFC's?
It wasn't just Pfizer that hid the fact that the mRNA-LNP complex went to the ovaries (where it could not possibly provide its declared function in the lung).
The AMH drop (ovarian reserve) after vaccination was later shown by the Manniche paper after being denied by the Kate Clancy and Viki Males of the world.
But this time the Arnold foundation's @RetractionWatch have not only revealed with their "exclusive" that they were directly involved in trying to get this important paper retracted...