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
Debbie's tweet was about her case against @HHSGov when her son developed Type 1 Diabetes after a routine vaccine, when he had a negative glucose test prior.
So it was clearly vaccine linked, but her case was denied.
Not only was the case denied (despite clear evidence of a new diagnosis immediately after vaccination) but the case was used by the "judge" to essentially ban ANY further cases that alleged a link between new diabetes and a routine vaccine.
I'll say it again. The vaccine industry [KNOWINGLY] hijacked cell pathways that cause cancer in order to induce antibody responses so that they can claim that their product "worked" by demonstrating those antibodies - even if they offered zero protection.
To explain, when you induce an immune response you have an immune debt to pay. You can't just keep creating an immune response - or, as in the case of cancer, you will die.
A vaccine creates an artificial immune response...
Which might be fine if it was done every now and again. But what they didn't tell you was that the human body will not respond to an injected antigen alone. It will ignore it (thankfully) and the generic immune system will mop it up, no antibodies required.
Just putting this into context. @DrCatharineY was originally DOD then published on a DARPA grant. One of her few co-authors is Stephanie Petzing of the "Center for Global Health Engagement"
All one big OneHealth family to nudge you into believing this @epiphare slop is real.
For the explanation as to why these "real world data" with "data not available" publications are absolutely junk and shouldn't be accepted to any major journal please see arkmedic.info/p/pharma-hell-β¦
Dr Young (DARPA/DOD) is clearly now working as an ambassador to cover for the actions of the corrupt Biden regime who we are learning covered up huge amounts of adverse events from their COVID program whilst funding pharma in the "cancer moonshot"
It looks like we found our vector.
They moved from spraying live (cloned) viruses to putting them in drinking water.. which we thought wasn't possible due to chlorine.
Well, it turns out that it is, if you use a stabiliser.
The @NIH told us that they stopped funding GOFROC research but they clearly didn't.
This is a modified live virus. That is, they took a pathogenic influenza and genetically modified it and propagated it using infectious clones (reverse genetics). nature.com/articles/s4154β¦
"MLVs were diluted in distilled water containing Vac-Pac Plus (Best Veterinary 418 Solutions, Columbus, GA, USA) to neutralize residual chlorine and adjust the pH"
There are a lot of pharma agents celebrating on twitter recently because the now-conflicted @cochranecollab dropped their standards and published something on HPV vaccination they didn't understand.
To explain it you need to understand the difference between the two studies quoted.
The first (Bergman) analysed a bunch of real studies (including RCTs) and concluded that the effect on cancer couldn't be seen - despite nearly 20 years of follow up.
The second (Henschke) cherry picked a bunch of "real world data" studies and concluded that the vaccine prevented a gazillion cervical cancers, pretending that it analysed 132 million patient records. It did nothing of the sort. What it did was look at two studies, take out the bit where it showed that the vaccine increased the risk of cancer (Kjaer 2021, over 20s) - replicated in multiple country statistics, split them into three studies, ignore the other studies showing the opposite, and ignore the fact that none of this data is verifiable.
Notably, one of the major studies (Palmer 2024, which was found to be seriously flawed) has been excluded from the meta-analysis because it did not show a cancer benefit in the under 16 age group.
It is very difficult to "fix" a randomised controlled trial.
It is very easy to "fix" a meta-analysis of observational studies where the data is "not available".
There is a huge difference between "real" studies and "real world data" studies because the latter are cherry picked or even fully synthetic, and the authors don't have access to the data. They are produced by vested interests groups to sell a narrative.
This was the most corrupted review that Cochrane have ever performed and this time they shot themselves in the foot by contradicting their own reviews. cochranelibrary.com/cdsr/doi/10.10β¦