How COVID-19 Jab Benefits are exaggerated


> One of the most commonly used tricks to make a drug look more effective than it is in a
real-world setting is to conflate absolute and relative risk reduction. While AstraZeneca
boasted a relative reduction of 100%, the absolute reduction was 0.01%. For the Pfizer
shot, the relative risk reduction was initially 95%, but the absolute risk reduction was only

> In AstraZeneca’s trial, only 0.04% of people in the vaccine group, and 0.88% in the
placebo group were infected with SARS-CoV-2. When the background risk of infection is
that low, even a 100% absolute risk reduction becomes near-meaningless

> Research shows the majority of SARS-CoV-2-specific antibodies in obese COVID-19
patients are autoimmune and not neutralizing. This means that if you’re obese, you’re at
risk of developing autoimmune problems if you get the natural infection. You’re also at
higher risk of a serious infection, as the antibodies your body produces are not the
neutralizing kind that kill the virus. Does the same hold true for antibodies made in
response to the COVID jab?

> At nearly 72%, Vermont has the highest rate of “fully vaccinated” residents in the country,
yet COVID cases are suddenly surging to new heights. During the first week of November
2021, cases increased by 42%. The hospital admission rate for fully vaccinated patients
increased by 8%, while the admission rate for those who were not fully vaccinated
decreased by 15%. Local health authorities blame the surge on the highly infectious delta
variant, which would be odd if true, since the first delta case in Vermont was detected
back in mid-May

> Data from physician assistant Deborah Conrad show vaccinated people — counting
anyone who got one or more shots, regardless of time since the injection — are nine
times more likely to be hospitalized than the unvaccinated

In a November 12, 2021, blog post, Maryanne Demasi, Ph.D., reviews how the benefits
of the COVID-19 shots have been exaggerated by the drug companies and
misrepresented to the public by an uncritical media. She has previously given many
lectures on how the drug companies conflated absolute and relative risks for statin

Demasi was a respected Australian science presenter at ABC television until she
produced a Catalyst report on the dangers of Wi-Fi and cellphones. In the wake of the
controversy it raised, she and 11 of her staff members were axed and the episode
retracted. That was 2016. Today, Demasi is one of the few professional journalists
seeking and publishing the truth about COVID-19.

Absolute Versus Relative Risk Reduction

In her post, Demasi highlights one of the most commonly used tricks in the book —
conflating absolute and relative risk reduction. As noted by Demasi, AstraZeneca and
Australia’s health minister, Greg Hunt, claimed the AstraZeneca injection offered “100%
protection” against COVID-19 death. How did they get this number? Demasi explains:
“In the trial of 23,848 subjects … there was one death in the placebo group and
no deaths in the vaccinated group. One less death out of a total of one, indeed
was a relative reduction of 100%, but the absolute reduction was 0.01%.”
Similarly, Pfizer’s COVID shot was said to be 95% effective against the infection, but this
too is the relative risk reduction, not the absolute reduction. The absolute risk reduction
for Pfizer’s shot was a meager 0.84%.

It’s worth noting that an incredibly low number of people were infected in the first place.
Only 8 out of 18,198 vaccine recipients developed COVID symptoms (0.04%), and 162 of
Data from physician assistant Deborah Conrad show vaccinated people — counting
anyone who got one or more shots, regardless of time since the injection — are nine
times more likely to be hospitalized than the unvaccinated the 18,325 in the placebo group (0.88%).

Since your risk of COVID was minuscule to begin with, even if the shot was able to
reduce your absolute risk by 100%, it would still be trivial in real-world terms.
According to Gerd Gigerenzer, director of the Harding Centre for Risk Literacy at the Max
Planck Institute, only quoting the relative risk reduction is a “sin” against transparent
communication, as it can be used as a “deliberate tactic to manipulate or persuade
people.” Demasi also quotes John Ioannidis, professor at Stanford University, who told
“This is not happening just for vaccines. Over many decades, RRR [relative risk
reduction] has been the dominant way of communicating results of clinical
trials. Almost always, RRR looks nicer than absolute risk reductions.”

Demasi continues:
“When asked if there was any justification for misleading the public about the
vaccine’s benefits to encourage uptake, Prof Ioannidis rejected the notion.
‘I don’t see how one can increase uptake by using misleading information. I am
all in favor of increasing uptake, but this needs to use complete information,
otherwise sooner or later incomplete information will lead to
misunderstandings and will backfire,’ says Ioannidis.

The way authorities have communicated risk to the public, is likely to have
misled and distorted the public’s perception of the vaccine’s benefit and
underplayed the harms. This, in essence, is a violation of the ethical and legal
obligations of informed consent.”

US Health Authorities Have Misrepresented the Data

U.S. health authorities, like Australia’s, are guilty of misrepresenting the data to the
public. In February 2021, Centers for Disease Control and Prevention director Rochelle
Walensky co-wrote a JAMA paper which stated that “Clinical trials have shown that the vaccines authorized for use in the U.S. are highly effective against COVID-19 infection,
severe illness and death.”
Alas, “there were too few deaths recorded in the controlled trials at the time to arrive at
such a conclusion,” Demasi writes. This observation was made by professor Peter
Doshi, associate editor of The BMJ, during Sen. Ron Johnson’s Expert Panel on Federal
Vaccine Mandates, November 1, 2021. During that roundtable discussion, Doshi stated
“The trials did not show a reduction in deaths, even for COVID deaths … Those
who claimed the trials showed that the vaccines were highly effective in saving
lives were wrong. The trials did not demonstrate this.”
Indeed, the six-month follow-up of Pfizer’s trial showed 15 deaths in the vaccine group
and 14 deaths in the placebo group. Then, during the open label phase, after Pfizer
decided to eliminate the placebo group by offering the actual shot to everyone who
wanted it, another five deaths occurred in the vaccine group.
Two of those five had originally been in the placebo group, and had taken the shot in the
open label phase. So, in the end, what we have are 20 deaths in the vaccine group,
compared to 14 in the placebo group. We also have the suspicious fact that two of the
placebo participants suddenly died after getting the real deal.

How You Express Effect Size Matters

As noted in a July 2021 Lancet paper, “fully understanding the efficacy and
effectiveness of vaccines is less straightforward than it might seem. Depending on how
the effect size is expressed, a quite different picture might emerge.”
The authors point out that the relative risk reduction really needs to “be seen against the
background risk of being infected and becoming ill with COVID-19, which varies
between populations and over time.” This is why the absolute risk reduction figure is so
“Although the RRR considers only participants who could benefit from the
vaccine, the absolute risk reduction (ARR), which is the difference between
attack rates with and without a vaccine, considers the whole population …
ARR is also used to derive an estimate of vaccine effectiveness, which is the
number needed to vaccinate (NNV) to prevent one more case of COVID-19 as
1/ARR. NNVs bring a different perspective: 81 for the Moderna–NIH, 78 for the
AstraZeneca–Oxford … 84 for the J&J, and 119 for the Pfizer–BioNTech
The explanation lies in the combination of vaccine efficacy and different
background risks of COVID-19 across studies: 0.9% for the Pfizer–BioNTech …
1.4% for the Moderna–NIH, 1.8% for the J&J, and 1.9% for the AstraZeneca–
Oxford vaccines.
ARR (and NNV) are sensitive to background risk — the higher the risk, the higher
the effectiveness — as exemplified by the analyses of the J&J’s vaccine on
centrally confirmed cases compared with all cases: both the numerator and
denominator change, RRR does not change (66–67%), but the one-third
increase in attack rates in the unvaccinated group (from 1.8% to 2.4%)
translates in a one-fourth decrease in NNV (from 84 to 64) …
With the use of only RRRs, and omitting ARRs, reporting bias is introduced,
which affects the interpretation of vaccine efficacy.
When communicating about vaccine efficacy, especially for public health
decisions such as choosing the type of vaccines to purchase and deploy, having
a full picture of what the data actually show is important, and ensuring
comparisons are based on the combined evidence that puts vaccine trial results
in context and not just looking at one summary measure, is also important.”
The authors go on to stress that comparing the effectiveness of the COVID shots is
further hampered by the fact that they use a variety of different study protocols,
including different placebos. They even differ in their primary endpoint, i.e., what they
consider a COVID case, and how and when diagnosis is made, and more.
“We are left with the unanswered question as to whether a vaccine with a given
efficacy in the study population will have the same efficacy in another
population with different levels of background risk of COVID-19,” the authors
One of the best real-world examples of this is Israel, where the relative risk reduction
was 94% at the outset and an absolute risk reduction of 0.46%, which translates into an
NNV of 217. In the Phase 3 Pfizer trial, the absolute risk reduction was 0.84% and the
NNV 119. As noted by the authors:
“This means in a real-life setting, 1.8 times more subjects might need to be
vaccinated to prevent one more case of COVID-19 than predicted in the
corresponding clinical trial.”

SARS-CoV-2 Specific Antibodies Pose Danger for the Obese

In related news, a recent study published in the International Journal of Obesity warns
that “the majority of SARS-CoV-2-specific antibodies in COVID-19 patients with obesity
are autoimmune and not neutralizing.”
In plain English, if you’re obese, you’re at risk of developing autoimmune problems if you
get the natural infection. You’re also at higher risk of a serious infection, as the
antibodies your body produces are not the neutralizing kind that kill the virus. As
explained by the authors:
“SARS-CoV-2 infection induces neutralizing antibodies in all lean but only in few
obese COVID-19 patients. SARS-CoV-2 infection also induces anti-MDA
[malondialdehyde, a marker of oxidative stress and lipid peroxidation] and anti-
AD [adipocyte-derived protein antigens] autoimmune antibodies more in lean
than in obese patients as compared to uninfected controls.
Serum levels of these autoimmune antibodies, however, are always higher in
obese versus lean COVID-19 patients. Moreover … we also evaluated the association of anti-MDA and anti-AD antibodies with serum CRP and found a
positive association between CRP and autoimmune antibodies.
Our results highlight the importance of evaluating the quality of the antibody
response in COVID-19 patients with obesity, particularly the presence of
autoimmune antibodies, and identify biomarkers of self-tolerance breakdown.
This is crucial to protect this vulnerable population at higher risk of responding poorly to infection with SARS-CoV-2 than lean controls.”
Now, these findings apply to obese people who develop the natural infection, but it
makes one wonder whether the same holds true for the COVID jab. If the antibodies
produced in response to the actual virus are primarily autoantibodies, will obese people
develop autoantibodies instead of neutralizing antibodies in response to the COVID shot
as well?
For clarity, an autoantibody is an antibody that is directed against one or more of your
own body’s proteins. Many autoimmune diseases are caused by autoantibodies that
target and attack your own tissues or organs.
So, this is no small concern, seeing how the mRNA in the COVID shots (and subsequent
SARS-CoV-2 spike protein, which is what your body produces antibodies against) gets
distributed throughout your body and accumulates in various organs.

Vermont’s COVID Cases Despite Highest Vaccination Rate

At this point, there’s an overwhelming amount of evidence showing the COVID shots are
not working. What little protection you do get clearly wanes within a handful of months,
and may leave you worse off than you were before. We’re seeing data to this effect from
a number of different places.
In the U.S., we can now look at Vermont. At nearly 72% vaccinated, it has the highest
rate of “fully vaccinated” residents in the country, according to ABC News, yet COVID
cases are now suddenly surging to new heights.
U.S. Centers for Disease Control and Prevention data show Vermont had the 12th
highest COVID case rate in the nation as of November 9, 2021. Over the previous seven
days, cases had increased by 42%. It couldn’t have been due to a surge in testing,
though, as the weekly average of tests administered had only increased by 9% in that
What’s more, during that first week of November, the hospital admission rate for patients
who were fully vaccinated increased by 8%, while the admission rate for those who were
not fully vaccinated actually decreased by 15%.
“ Data from physician assistant Deborah Conrad
shows vaccinated people are nine times more likely to
be hospitalized than the unvaccinated.”
Keep in mind that you’re not considered “fully vaccinated” until two weeks after your second injection. If you got your second dose a week ago and end up in the hospital with
COVID symptoms, you’re counted as unvaccinated. This gross manipulation of reality
makes it very difficult to interpret the data, but even with this manipulation it is beyond
obvious that the vaccines are failing.
Overall, the case rate in Vermont is FAR higher now than it as in the fall of 2020, when no
one had gotten the “vaccine.” According to Vermont health commissioner Dr. Mark
Levine, the surge is occurring primarily among unvaccinated people in their 20s and
children aged 5 through 11 — a curious coincidence, seeing how the shots are just now
being rolled out for 5- to 11-year-olds.
Levine blames the surge on the highly infectious delta variant, but delta has been around
for months already. The first case of delta in Vermont was identified in mid-May 2021.
Surely, it wouldn’t have taken six months for this most-infectious of variants to make the
rounds and cause an unprecedented spike?
Two clues are given by Levine, however, when he admits that a) Vermont has one of the
lowest rates of natural immunity in the U.S. and b) protection is waning among those who got the COVID shot early to mid-year. Breakthrough cases among the fully
vaccinated shot up 31% during the first week of November.

Fully Vaxxed Are Nine Times More Likely To Be Hospitalized

Coincidentally, data from physician assistant Deborah Conrad, presented by attorney
Aaron Siri October 17, 2021, shows vaccinated people are nine times more likely to be
hospitalized than the unvaccinated.
The key, however, was in what they counted as vaccinated. Rather than only including
those who had gotten the shot two weeks or more before being hospitalized, they simply
counted those who had one or more shots, regardless of when, as vaccinated. This
gives us an honest accounting, finally! As explained by Siri:
“A concerned Physician Assistant, Deborah Conrad, convinced her hospital to
carefully track the COVID-19 vaccination status of every patient admitted to her
hospital. The result is shocking.
As Ms. Conrad has detailed, her hospital serves a community in which less than
50% of the individuals were vaccinated for COVID-19 but yet, during the same
time period, approximately 90% of the individuals admitted to her hospital were
documented to have received this vaccine. These patients were admitted for a variety of reasons, including but not limited
to COVID-19 infections. Even more troubling is that there were many individuals
who were young, many who presented with unusual or unexpected health
events, and many who were admitted months after vaccination.”
Despite these troubling findings, health authorities ignored Conrad when she reached
out. In mid-July 2021, Siri’s law firm also sent formal letters to the CDC, the Health and
Human Services Department and the U.S. Food and Drug Administration on Conrad’s
behalf, and those were ignored as well.
“This again highlights the importance of never permitting government coercion
and mandates when it comes to medical procedures,” Siri writes.
Now, one of the most shocking details gleaned from Conrad’s data collection, which Siri
failed to make clear but Steve Kirsch highlights in a recent substack post is that:
“The only way you can get those numbers is if vaccinated people are 9 times
more likely to be hospitalized than unvaccinated. It is mathematically
impossible to get to those numbers any other way. Period. Full stop. This is
known as an ‘inconvenient truth.’”
Indeed, the more data we gain access to, the worse it looks for these COVID shots.
Unfortunately, those who push them seem hell-bent on ignoring any and all data that
don’t support their stance.
Worse, it seems data and statistics are being intentionally manipulated by our health
authorities to present a false picture of safety and effectiveness. All such tactics are
indefensible at this point, and people who believe the official narrative without doing
their own research do so at their own risk.

Author: maskfree