November , 2020
This far below video provides one of the most erudite and informative looks at
Covid-19 and the consequences of lockdowns.
AIER notes, it was
remarkable this week to watch as it appeared on YouTube and was
forcibly taken down only 2 hours after posting.
The copy below is hosted on LBRY, a blockchain video application. In
a year of fantastic educational content, this is one of the best
Consider the presenter's
Yeadon is an Allergy & Respiratory Therapeutic Area expert with
23 years in the pharmaceutical industry. He trained as a
biochemist and pharmacologist, obtaining his PhD from the
University of Surrey (UK) in 1988.
Dr. Yeadon then worked at the Wellcome Research Labs with
Salvador Moncada with a research focus on airway
hyper-responsiveness and effects of pollutants including ozone
and working in drug discovery of 5-LO, COX, PAF, NO and lung
With colleagues, he was the first to detect
exhaled NO in animals and later to induce NOS in lung via
Joining Pfizer in 1995, he was responsible for the growth and
portfolio delivery of the Allergy & Respiratory pipeline within
He was responsible for target selection and the
progress into humans of new molecules, leading teams of up to
200 staff across all disciplines and won an Achievement Award
for productivity in 2008.
Under his leadership the research unit invented oral and inhaled
NCEs which delivered multiple positive clinical proofs of
concept in asthma, allergic rhinitis and COPD.
He led productive
collaborations such as with Rigel Pharmaceuticals (SYK
inhibitors) and was involved in the licensing of Spiriva and
acquisition of the Meridica (inhaler device) company.
Dr. Yeadon has published over 40 original research articles and
now consults and partners with a number of biotechnology
Before working with Apellis, Dr. Yeadon was VP and
Chief Scientific Officer (Allergy & Respiratory Research) with
triggered the Silicon Valley censor-mongers is the fact that a
former Chief Science Officer for the pharmaceutical giant Pfizer
"there is no science to suggest a second wave should happen"...
The "Big Pharma" insider asserts that false positive results from
inherently unreliable COVID tests are being used to manufacture a
"second wave" based on "new cases."
As Ralph Lopez write at
Yeadon warns that half or even
"almost all" of tests for COVID are false positives.
Dr. Yeadon also
argues that the threshold for herd immunity may be much lower than
previously thought, and may have been reached in many countries
an interview last week (see below) Dr.
Michael Yeadon was asked:
"we are basing
a government policy, an economic policy, a civil liberties
policy, in terms of limiting people to six people in a
meeting... all based on, what may well be, completely fake data
on this coronavirus?"
Dr. Yeadon answered
with a simple "yes."
Even more significantly, even if all positives were to be correct,
Dr. Yeadon said that given the "shape" of all important indicators
in a worldwide pandemic, such as
hospitalizations, ICU utilization,
"the pandemic is fundamentally over"...
Yeadon said in the interview:
"Were it not
for the test data that you get from the TV all the time, you
would rightly conclude that the pandemic was over, as nothing
much has happened.
Of course people go to the hospital, moving
into the autumn flu season...but there is no science to suggest
a second wave should happen."
In a paper
published this month, which was co-authored by Yeadon and two of his
colleagues, "How Likely is a Second Wave?", the scientists write:
"It has widely
been observed that in all heavily infected countries in Europe
and several of the US states likewise, that the shape of the
daily deaths vs. time curves is similar to ours in the UK.
of these curves are not just similar, but almost super
In the data for UK,
Sweden, the US, and the world, it can be seen that in all cases,
deaths were on the rise in March through mid or late April, then
began tapering off in a smooth slope which flattened around the end
of June and continues to today.
The case rates however, based on
testing, rise and swing upwards and downwards wildly.
Media messaging in the US
is already ramping up expectations of a "second wave"
The survival rate of COVID-19 has been upgraded since May to 99.8%
This comes close to
ordinary flu, the survival rate
of which is 99.9%. Although COVID can have serious after-effects, so
can flu or any respiratory illness.
The present survival rate is far
higher than initial grim guesses in March and April, cited by Dr.
Anthony Fauci, of 94%, or 20 to 30 times deadlier.
Fatality Rate (IFR) value accepted by Yeadon et al in the paper is
The survival rate of a disease is 100% minus the IFR.
Dr. Yeadon pointed out that the "novel" COVID-19 contagion is novel
only in the sense that it is a new type of coronavirus. But, he
said, there are presently four strains which circulate freely
throughout the population, most often linked to the common cold.
In the scientific paper, Yeadon et al write:
"There are at
least four well characterized family members (229E, NL63, OC43
and HKU1) which are endemic and cause some of the common colds
we experience, especially in winter.
They all have striking
sequence similarity to the new coronavirus."
argue that much of the population already has, if not antibodies to
COVID, some level of "T-cell" immunity from exposure to other
related coronaviruses, which have been circulating long before
The scientists write:
component our immune systems is the group of white blood cells
called T-cells whose job it is to memorize a short piece of
whatever virus we were infected with so the right cell types can
multiply rapidly and protect us if we get a related infection.
Responses to COVID-19 have been shown in dozens of blood samples
taken from donors before the new virus arrived."
idea that some prior immunity to COVID-19 already existed, the
authors of "How Likely is a Second Wave?" write:
"It is now
established that at least 30% of our population already had
immunological recognition of this new virus, before it even
arrived... COVID-19 is new, but coronaviruses are not."
They go on to say
that, because of this prior resistance, only 15-25% of a population
being infected may be sufficient to reach herd immunity:
"...epidemiological studies show that, with the extent of prior
immunity that we can now reasonably assume to be the case, only
15-25% of the population being infected is sufficient to bring
the spread of the virus to a halt..."
In the US,
accepting a death toll of 200,000, and a survival rate of 99.8%,
this would mean for every person who has died, there would be about
400 people who had been infected, and lived.
This would translate to
around 80 million Americans, or 27% of the population.
Yeadon's and his colleagues' threshold for herd immunity.
Finally, the former Pfizer executive and scientist singles out one
former colleague for withering rebuke for his role in the pandemic,
Professor Neil Ferguson.
Ferguson taught at Imperial College while
Yeadon was affiliated.
computer model provided the
rationale for governments to launch draconian orders which turned
free societies into virtual prisons overnight.
Over what is now
estimated by the CDC to be a 99.8% survival rate virus...
Dr. Yeadon said in the interview that,
"no serious scientist gives
any validity" to Ferguson's model.
Speaking with thinly-veiled contempt for Ferguson, Dr. Yeadon took
special pains to point out to his interviewer:
that you know most scientists don't accept that it [Ferguson's
model] was even faintly right... but the government is still
wedded to the model."
Yeadon joins other
scientists in castigating governments for following Ferguson's
model, the assumptions of which all worldwide lockdowns are based
One of these scientists is Dr.
Johan Giesecke, former chief
scientist for the European Center for Disease Control and
Prevention, who called Ferguson's model,
"the most influential
scientific paper" in memory, and also "one of the most wrong."
It was Ferguson's model which held that "mitigation" measures were
necessary, i.e. social distancing and business closures, in order to
prevent, for example, over 2.2 million people dying from COVID in
Ferguson predicted that Sweden would pay a terrible price for no
lockdown, with 40,000 COVID deaths by May 1, and 100,000 by June.
Sweden's death count is
Swedish government says
this coincides to a mild flu season.
Although initially higher,
Sweden now has a lower death rate per-capita than the US, which it
achieved without the terrific economic damage still ongoing in the
Sweden never closed restaurants, bars, sports, most schools, or
The government never ordered people to wear masks.
Dr. Yeadon speaks bitterly of the lives lost as a result of lockdown
policies, and of the "savable" countless lives which will be further
lost, from important surgeries and other healthcare deferred, should
lockdowns be re-imposed.
Watch the full discussion below:
Yeadon's warnings are confirmed by a new study from the Infectious
Diseases Society of America., summarized succinctly in the following
twitter thread from al gato malo (@boriquagato)
Anyone still presuming that a
Positive PCR test is showing a COVID case needs to read this very
25 cycles of amplification, 70% of "positives" are not
"cases." virus cannot be cultured. it's dead.
By 35: 97%
The US runs
at 40, 32X the amplification of 35,
...a lot of people
still seem to not understand what this means, so let's lay that out
for a minute.
PCR tests look for RNA.
There is too little in your swab.
amplify it using a primer based heating and annealing process.
Each cycle of this process doubles the material, the US (and much of
the world) is using a 40 Ct (cycle threshold).
So, 40 doublings, 1
trillion X amplification...
This is absurdly high.
The way that we know this is by running this test, seeing the Ct to
find the RNA, and then using the same sample to try to culture
If you cannot culture the virus, then the virus is "dead."
If it cannot replicate, it cannot infect you or others.
just traces of virus, remnants, fragments etc
PCR is not testing for
disease, it's testing for a specific RNA pattern and this is the key
When you crank it up to 25, 70% of the positive results are not
really "positives" in any clinical sense.
I hesitate to call it a "false positive" because it's really not.
did find RNA, but that RNA is not clinically relevant.
It cannot make you or anyone else sick, so let's call this a
non-clinical positive (NCP).
if 70% of
positives are NCP's at 25, imagine what 40 looks like. 35 is
1000X as sensitive.
found only 3% live at 35
40 Ct is
32X 35, 32,000X 25,
...no one can
culture live virus past about 34 and we have known this since march.
yet no one has adjusted these tests.
This is more very strong data refuting the idea that you can trust a
PCR+ as a clinical indicator.
That is NOT what it's meant for... at all.
Using them to do real time epidemiology is absurd.
The FDA would never do it, the drug companies doing vaccine trials
would never do it... it's because it's nonsense.
And this same test is used for "hospitalizations" and "death with
Covid" (itself a weirdly over inclusive metric)
PCR testing is not the answer, it's the problem.
It's not how to get control of an epidemic, it's how to completely
lose control of your data picture and wind up with gibberish and we
have done this to ourselves before.
A quick word
what this data does and does not mean
Saying "a sample requiring 35 Ct to test + has a 3% real clinical
positive rate" does not mean "97% of + tests run at 35 Ct are NCP's".
People seem to get confused on this, so lets explain:
Most tests are just amplified and run.
They don't test every cycle
as these academics do.
That would make the test slow and expensive,
so you just run 40 cycles then test.
Obviously, a real clinical positive (RCP) that would have been + at
20 is still + at 40, but when you run the tests each cycle as the
academics do, that test would already have dropped out.
So saying that only 3% at 35 are RCP really means that 3% of those
samples not PCR + at 34 were PCR and RCP + at 35.
This lets us infer
little about overall NCP/RCP rate.
So we cannot say "at 25 Ct, we have a 70 NCP rate."
In fact, it's
hard to say much of anything.
It depends entirely on what the source
material coming in looks like.
You cannot even compare like to like...
This is what I mean by "the
data is gibberish"
Today at 40 Ct, 7% PCR positive rate could be 1% RCP prevalence when
that same thing meant 6% RCP prev in April.
If there is lots more trace virus around, more people who have
recovered and have fragments left over, etc this test could be
finding virus you killed 4 months ago...
So if we consider RCP rate/PCR+ rate, we would expect that number to
drop sharply late in an epidemic because there is more dead virus
around for PCR to find, but we have no idea what that ratio is or
how it changes.
This spills over in to deaths, reported hospitalization etc.
Testing is being made out to be like the high beams on a car, but
when it's snowing like hell at night, that is the LAST thing you
want. It is not illuminating our way, it's blinding us.
A bad inaccurate map is much worse than no map at all, and this is a
world class bad map...
We're basing policy that is
affecting billions of humans on data that is uninterpretable
It's a deranged technocrat's wet dream, but for those of us along
for the ride, it's a nightmare.
Testing is not the solution, it's the
Any technocrat or scientist that does not know this by now is either
unfit for their job or has decided that they just don't care and
prefer power to morality.
This is, of curse, precisely the kind of person who winds up running
a gov't agency... oopsie.
head of the NIH is not the best
scientist, it's the 'best' politician...
All this wild and reckless government policy has never been about
It's politics and
You can read the whole paper