top of page

Do the recent 80k pages of Pfizer documents released really show vaccine efficacy was only 12%?

Updated: May 11, 2022

This week Pfizer released a new stack of documents related to the Pfizer SARS-CoV-2 vaccine, with >80,000 pages of material released. Here is a link to the documents.


In the past couple days there is a viral claim circulating social media that this data dump revealed the actual efficacy of this vaccine was 12%, not 95% as reported, purporting a massive conspiracy. Here are some active tweets repeating this claim:

These tweets and accompanying threads lack documentation of where exactly in the documents it is revealed that the actual vaccine efficacy for the Pfizer vaccine was 12% not 95%. Many of these twitter threads have a few people asking for such documentation, but without response or clarification.


Best as I can tell, this claim originates from a substack post by Sonia Elijah on May 3rd.

Her claims are based on the December 2020 Pfizer FDA briefing document for the Vaccines and Related Biological Products Advisory Committee (VRBPAC) meeting deciding the EUA on December 10, 2020. Incidentally, this document was transparently released to the public the week before the meeting, so is not new to this 80k page document dump this week.


In this SubStack post, she claims that the 95% VE computed based on the fact that 162 of placebo patients had confirmed (PCR+) COVID infections and the vaccine arm only 8 was misleading. She claims the "real VE" should be computed based on the "suspected but unconfirmed" COVID-19 cases in the study, which she claims is "buried" in the document (implying some sort of intentional obfuscation).

From the fact that there were 3410 total "suspected but unconfirmed" cases, with 1594 occurring in the vaccine group vs. 1816 in the placebo group, she estimates that the "true VE" should actually be reported as 1-1594/1816 x 100% = 12.2%. This is seemingly where the viral claim of 12% comes from. Now, if there were indeed 1594 COVID-19 cases in vaccine arm and 1816 in placebo, indeed she would be correct that the VE would be 12%. However, we have to look at what is meant by "suspected but unconfirmed" cases in the Pfizer/BioNTech trial.


If you look through the protocol, which again was transparently posted in its entirety , you see no explicit mention of a category of COVID-19 cases that are "suspected but unconfirmed," but from the protocol the implication is clear.


The only time the idea of "suspected" is used in the protocol is in the context of determining when a unplanned potential COVID-illness visit should be scheduled to give a SARS-CoV-2 PCR test based on reported symptoms. As described in Section 8.13, page 93/146, of the protocol, they did this by instructing subjects to immediately contact the site to set up an unplanned potential COVID-illness visit, ideally within 3 days, if they experienced any of the following symptoms anew that COULD indicate potential COVID-19: fever, cough, shortness of breath, chills, muscle pain, sore throat, loss of taste/smell, diarrhea, and vomiting. Anyone reporting one of these symptoms is a "suspected" COVID-19 case who is to report for an unplanned clinical visit to determine whether it meets the COVID-19 case definition or not.


The protocol clearly states (in the table on Section 1.3.2 on page 23, in Section 8.13.1 on page 95, and in Section 8.15 on page 97) that these unplanned potential COVID-illness visits are to include a nasal swab (PCR test) to determine whether the symptoms experienced by the participant fulfill the COVID-19 test definition. If the test is positive, they are a "confirmed" COVID-19 case, and by context it is clear that the others are "suspected but unconfirmed." Those who are "confirmed COVID-19 cases" are included in the primary efficacy analysis.


So these 3410 "suspected but unconfirmed" cases were people who any symptom mentioned in the list, which of course could come from many causes not just COVID-19 infections, triggering an unplanned COVID-19 visit (for which a PCR test was indicated), and for whom the SARS-CoV-2 test was not positive. Since obviously the SARS-CoV-2 vaccine was not intended to prevent all coughs, fevers, chills, sore throats, muscle pain, shortness of breath, vomiting, etc., from any cause, it would be ridiculous to include all reports of such common symptoms as COVID-19 cases for the purpose of computing Vaccine Efficacy. The only way one might propose this as appropriate is if they assume the false positive rate of the PCR test was >>95%. We of course have plenty of data demonstrating that the false negative rate of these tests is nowhere near that high; it was 4% in this FDA report for the precise PCR test used for the trial. Even if higher, it is not plausible to propose a false negative rate >>95%. And even if they wanted to make that argument, given that the trial was double-blinded, i.e. neither the participants or health care workers knew who received active vaccine and who received placebo, it would be impossible for the vaccinated would have 162 true positives and placebo 8 true positives if indeed the underlying rate of disease was indeed equivalent in the two arms.


So Sonia Elijah is making the same specious argument Peter Doshi did in his editorial in British Medical Journal in January 2021, which I refuted in detail in my blog post that same month. It seems she is making the mistake of not realizing that "suspected but unconfirmed cases" in the protocol refers to individuals receiving PCR tests because that had a symptom from a large pre-specifed list that triggered a PCR test, but for which the PCR test was negative. The authors of the FDA briefing document choosing the term "suspected but unconfirmed cases" for those with negative PCR tests was a poor choice that has contributed to this confusion and led many to misinterpret what it means.


So the argument made by Sonia Elijah suggesting the "real VE" of the Pfizer vaccines is 12% is an old one dating back to January 2021, and an erroneous one. The fact this claim is spreading virally around social media without confirmation or justification, and with very few questioning where it came from or whether it was a legitimate claim, shows how easy it is for unsubstantiated and false claims to quickly spread on social media, where they find a large set of receptive ears ready to believe and promote the claim without any documentation or justification, primarily because it feeds the narrative they believe and are promoting.


As I mentioned, it is not explicitly clear in these viral tweets from whence the claim of 12% efficacy comes. I'll keep my eyes opened and if someone posts a link for documentation other than the substack post I linked here, I'll evaluate and comment on that evidence.

91,366 views122 comments

Recent Posts

See All

Explanation of "Healthy Vaccinee Effect" and Confounding

Healthy vaccinee effect (HVE) has become frequent topic of discussion these days. I am glad to see this, as I have been talking about this phenomenon for the past 2.5 years, and for a long time no one

122 Comments


Unknown member
Jun 03

Kediniz için en iyi kedi kumunu bulun! Ekonomik fiyatlarla kaliteli kedi kumu seçenekleri için hemen tıklayın ve rahatlığı keşfedin.

Like

Unknown member
Jun 03

Güvenilir online mağazamızdan en uygun fiyatlarla Vozol Puff satın alın. Kaliteli buhar deneyimi için sınırlı stokları kaçırmayın!

Like

Radu 001
Radu 001
Jan 06

As i read this article than it means we have no evidence at all that this vaccine works at all.

Like

Jeffrey Morris asserts that he has "no affiliation with pharma and no conflict of interest."


I note that he is "a professor and Director of Biostatistics at the Perelman School of Medicine at the University of Pennsylvania."


Apparently, a company called Verismo Therapeutics sponsors research funding at the Perelman School, and I expect that this is not the sole source of funding at the School.


I'm sure readers would be grateful to Professor Morris if he would clarify the following:


1. Which other biotech / pharma companies fund his employer?


2. What are the potential implications for that funding and his employment at the School if he published views contrary to the commercial interests of those companies?


Many thanks.

Like
Jeffrey Morris
Jeffrey Morris
Jun 25, 2022
Replying to

Any biomedical research institution, especially one as large as PSOM, will have projects funded by all kinds of sources — most are funded by NIH but also by other private research foundations, some from pharmaceutical companies. And some researchers spin off their own biotech companies based on their research. But I don’t have any conflict of interest on any of this — all of my salary and research finding comes from NIH grants in areas unrelated to Covid, and I have no affiliation or investment in any pharmaceutical company or biotech company, nor am I doing any consulting or is my research funded by them. And professionally I am a tenured professor at UPenn with lifetime tenure and full academic freedom. I hav…

Like

elijah3570
elijah3570
Jun 02, 2022

So funny. To read your article, you cover Sonia’s claims with ‘she misinterpreted the intention/meaning of the date set’, and then you lend a helping hand to Pfizer by saying that what they ‘really meant to say was …. Lol your position is wallpapered with conjecture. Science doesn’t do politics.

Like
Jeffrey Morris
Jeffrey Morris
Aug 20, 2022
Replying to

My goal is not to get anyone “for” or “against” me.


It is to just state what the data say and in the case of this post and others correcting blatant and clear misinterpretations and misrepresentations . You may think misrepresenting data and making demonstrably false claims is fine in the name of what you are convinced is a “righteous cause”, but I do not. If claims are true they should be supported by legitimate data and arguments and if they are then I am willing to consider and believe them. Debunking demonstrably false arguments is not even taking a position on the matter but pointing out others have not made their case.


And I would not say the “masses…


Like
Post: Blog2_Post
bottom of page