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Ben Profile picture
@USMortality
May 4, 2022 • 12 tweets • 5 min read • Read on X
🔥 Finally we have evidence, how Pfizer came to calculate a 95% vaccine efficacy!
Real efficacy is likely only 19%, with a very bad side effect profile of up to 0.8% severe side effects, as reported by German Hospital Study Charité!

🧵 1/n #Covid #Covid19 #Corona #Coronavirus
As we know from the published study, the vaccine arm suffered from +12.1% and +36.1% more systemic Adverse Events (side-effects) than the placebo group.

These side effects, are indistinguishable from COVID19 in most cases! Image
The following document, just released in the latest Pfizer batch shows, that Pfizer did NOT test patients for COVID-19, unless the investigator suspected COVID-19, and not vaccine side effects. So it is likely that they would almost never test, but classify them as vax reactions. ImageImage
Pfizer reported these side effect as "unconfirmed COVID-19" in the just released documents.

Here we can see, that suspected COVID-19 was reported in 1595 vax recipients, and 1816 placebo recipients.

Based on these numbers VE is about 12%, but ... Image
Of course, in reality one must include the confirmed COVID-19 cases as well, which would yield:

VE = ((1816+162)-(1594+8))/(1816+162) = 19.0%

So overall, we have strong reasons to believe that the vaccine might be just 19% effective in preventing COVID-19, but...
A recent study from Germany's top hospital Charité Berlin, revealed that about 0.8% of vaccinated suffer "severe long-term side effects".

So it becomes quite clear that the cost/benefit overall is very likely there, given the fairly large chance of severe side effects, compared to other vaccines!

Sources:
phmpt.org/pfizers-docume…
cdn.pfizer.com/pfizercom/2020…
blogs.bmj.com/bmj/2021/01/04…
H/t to @justin_hart for providing some of the links and screenshots!
Small addendum & correction, since Twitter still doesn't have an edit button:

3. post: "Pfizer did NOT test patients for COVID-19 *up to 7 days after vaccination*, unless the investigator suspected COVID-19, and not vaccine side effects."
7. post: "So it becomes quite clear that the cost/benefit overall is very likely *NOT* there,"
Summarized:
Pfizer encouraged to generally not test for COVID-19 up to 7 days after each vaccination.
It would have just taken 154 patients to bring VE to 0%.
That represents just 3.1% ( `(162-8)/(2421+2627)` ) of vaccinated patients that experienced any vaccine side effect!
And here's part 2:

In this thread Jikky explains another vector of evidence that proofs that the vaccinated arm also got infected (but since not tested, undetected):

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Ben Profile picture
Jun 5
This may as well be part of the script/disinformation campaign after all:

>> This is important to understand <<

Hypothetical Disinformation Campaign Scenario

1. Initial Denial:
• Key Players: Military, secret agencies, health authorities, virologists, philanthropists, etc.
• Action: Strongly deny any allegations of a secret operation involving a lab-manufactured virus leak (commonly referred to as the “Lab Leak Theory”).
• Narrative: Label the lab leak theory as a baseless conspiracy, dismissing it without thorough investigation.

2. Diversion:
• Media Strategy: Shift the focus of the media to alternative explanations, such as the “Zoonosis Theory” (natural transmission from animals to humans).
• Examples: Highlight potential sources such as bats and pangolins to distract and redirect public attention.
• Impact: This redirection aims to convince the majority of the population (~70%) to believe in a "viral spillover", thus novelty of the virus.

3. False Confirmation:
• Controlled Leaks: Release unverifiable “evidence” that appears to confirm the lab leak theory through credible sources.
• Staged Reports: Media outlets present findings like the Furin Cleavage Site or HIV inserts as proof of the lab-manufactured origin.
• Public Reaction: Skeptics (~25%) quickly adopt this narrative, now able to direct their frustration towards those seemingly responsible.

4. Framing:
• Agenda Alignment: Shape the lab leak confirmation to justify specific actions or policies that stakeholders wish to implement.
• Justifications: Use this narrative to defend the necessity of questionable virological surveillance, mass testing, lockdowns, masking, and mass vaccinations as preventive measures.

5. Public Manipulation:
• Perceived Investigation: Convince the public that the origin of the virus has been thoroughly investigated and validated, creating a false sense of certainty.
• Acceptance: The public now either believes in the perpetual risk of natural spillover or lab leak pandemics, leading to widespread acceptance of continuous countermeasures.
• Focus Shift: Rather than calling for the cessation of Gain-of-Function (GoF) research, the narrative shifts to the inevitability of such research due to its international nature, emphasizing the need for ongoing measures like viral surveillance, mass testing and vaccinations.

Summary: Stakeholders deny the “Lab Leak Theory,” redirect media to natural origins, then release false evidence supporting the lab leak to win over skeptics. This frames their original techniques and countermeasures as necessary, manipulating the public into accepting any future measures.Image
Instead, people like Dr. Binder have pointed out since 2020, that the use of mass PCR testing, is entirely responsible for this phenomenon:
In addition, Dr. Rancourt has shown strong epidemiological evidence, that the mass casualties that were observed in some regions cannot be caused by a novel risk-additive pathogen:
Read 4 tweets
Ben Profile picture
May 7
🧵Thread of posts showing no COVID-19 vaccine efficacy!

Read 17 tweets
Ben Profile picture
Apr 25
There are several problems with the reference genome (b) published by Wu et al. 2020 (a):

1. The sequenced patient sample contained genetic material from different sources: human, bacterial, viral, etc. Although known sequences were filtered out after sequencing, there is no guarantee that all non-novel-viral sequences were actually removed.

2. The patient's human genome was not sequenced for control.

3. Reassembly of the dataset published by Wu using Megahit does not provide the exact or complete sequence as published.

4. Trinity, the second program used for de novo sequencing, is unable to generate the identical contig.

5. When using untrimmed or protocol-trimmed reads (Takara), no reads are found that perfectly match both ends of the genome. This is unusual because, according to a theoretical simulation, several ends should be found in the sample. (c)

6. It has not yet been proven that the entire sequence (~30 KB) actually occurs in this form in the samples, e.g. by agarose gel electrophoresis or (Sanger/whole genome) sequencing.

7. Wu et al. published three versions of the reference genome, the first of which contained known sequences from the human reference genome. The fact that the first version contained human sequences suggests possible problems with sequencing or analysis.

8. The amplicons, i.e. the sequences of the ends found using RACE, have not been published. The non-publication of the amplicon sequences raises questions about the transparency and reproducibility of the study.

9. The only non-Chinese author of this paper, Eddie Holmes, confirmed to me by email that he had no detailed knowledge of these issues. There was silence from the Chinese side, although questions were asked via Holmes. (d)

These clear scientific problems therefore clearly call into question the validity of the SARS-CoV-2 sequence.

(a)
(b)
(c)
(d) ncbi.nlm.nih.gov/pmc/articles/P…
ncbi.nlm.nih.gov/labs/virus/vss…
usmortality.substack.com/p/why-the-ends…
usmortality.substack.com/p/why-do-wu-et…
10. Wu et al., only published a single run, which is supposed to prove the sequence.
11. Wu claims they found a complete sequence before they actually knew its true length - they were just missing the ends, which they then added manually via RACE.
That's a fallacy - because how can one determine the length of a new sequence without first finding the ends, and thus the true length?
Read 7 tweets
Ben Profile picture
Mar 17
There's a large pharma funded Measles Scare Campaign ongoing.
The actual data doesn't support this.Image
ecdc.europa.eu/sites/default/…
World:
Read 8 tweets
Ben Profile picture
Mar 7
‼️ Phantom Vaccine Efficacy!

A list of statistical tricks, that can be used to calculate an illusion of vaccine efficacy with a placebo alone.

For this exercise, I have used a sine wave to simulate weekly deaths:Image
... and a logistic growth function to simulate placebo vaccination from 0 to 75% of the population.
By the green/red dots, we can see no difference/effect, as no statistical tricks are applied yet. Image
Trick 1: Unknown Vaccination Status --> Unvaccinated.

If 50% of Unknown vaccination status is treated as unvaccinated, almost 3x higher mortality rates appear for unvaccinated. This is entirely an illusion. Image
Read 6 tweets
Ben Profile picture
Mar 1
🔥 All-cause mortality by vaccination status from the Netherlands shows likely no vaccine efficacy, possible harm!
Deaths per 100k population by vaccination status shows an initial spike for the vaccinated during the vaccination rollout, and consistently higher mortality levels.Image
The initial peak may be related to confounding as more elderly/frail were prioritized, to reporting artifact (Fenton et al.), or vaccine harm.
Only focusing on the mid 2021 data, where the lines move in tandem, we still see a diverging of rates after the late 2021 winter peak.
Here adjusted for the levels during extremely low COVID-19 prevalence in Summer of 2021, we can possibly see, no efficacy and a drop for unvaccinated and slight increase for vaccinated, possibly even indicating negative efficacy?Image
Read 7 tweets

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