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
You were lied to about the Merck measles vaccine develop in the 60s. When injected into babies it caused fevers, rashes, diarrhoea and febrile convulsions.
Why?
I'm going to show you.
@SecKennedy @RetsefL @MaryanneDemasi @DrJulieSladden @RWMaloneMD
Merck claimed that the "measles vaccine" was an "attenuated version of measles" giving the impression that it was a virus that was made safe.
That was a lie.
It was just measles, passaged in cells in a lab.
We injected our babies with actual measles.
How do I know?
Recently released Australian Road Deaths data confirm that the @epiphare study claiming that COVID vaccination reduced road deaths by 32% was, as suspected, a complete fake.
Here are the actual road deaths data plotted from the Australian BITRE data repository using a trendline for 2000-2019 (excluding 2020 as it was a quiet year)
The pink area shows the inflection and increase in road deaths over the predicted number.
Note that road deaths have a downward trend despite an increase in population (due to safety measures and slowing of traffic).
So the question becomes...
"what is the probability that - if the @epiphare study was real (showing a 32% reduction in road deaths after vaccination) - the Australian road deaths (where nearly 100% of the adult population was vaccinated) would increase by 36%"?
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.
Here is the clip from the (decent) interview with Pelle Neroth Taylor of @RealTNTRadio.
In it Boyle is asked whether the mRNA vaccines are themselves biological weapons and he explains that because "in your system, it generates the COVID-19 cells" they would be.
But of course that's incorrect, because mRNA vaccines don't recreate the COVID virus (the biological weapon - assuming as we now know that it was synthetic not natural).
So his explanation was incorrect because he misunderstood that the mRNA only provides the spike protein and he would have been destroyed on this point in court.
Of course he never got to court. And never gave an affidavit for the Dutch court - confirmed here (8/3/25):
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.