Second Wave Faked On False-Positive Tests

Michael Yeadon, a former Chief Science Officer for the pharmaceutical giant Pfizer says "there is no science to suggest a second COVID 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." Yeadon warns that half or even "almost all" of tests for COVID are false positives and argues that the threshold for herd immunity may be much lower than previously thought, reached in many countries already.

In an interview last week Dr. Yeadon was asked: "Are we 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, and deaths, "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 U.S. states likewise, that the shape of the daily deaths vs. time curves is similar to ours in the UK. Many of these curves are not just similar, but almost super imposable."

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 U.S. is already ramping up expectations of a "second wave." The survival rate of COVID-19 has been upgraded since May to 99.8% of infections. 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. The Infection Fatality Rate (IFR) value accepted by Yeadon et al in the paper is .26%. 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 characterised 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." The scientists 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 COVID-19.

The scientists write: "A major component of 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." Introducing the 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 U.S., 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. This touches Yeadon's and his colleagues' threshold for herd immunity.

Yeadon's warnings are confirmed by a new study from the Infectious Diseases Society of America. Anyone still presuming that a Positive PCR test is showing a COVID case needs to read this very carefully:

• even 25 cycles of amplification, 70% of "positives" are not "cases." virus cannot be cultured. it's dead.

• by 35: 97% non-clinical.

• the US runs at 40, 32X the amplification of 35.

A lot of people who should understand still seem to not understand what this means, so let's lay it out for a minute.

PCR tests look for RNA. There is too little in your swab for an effective test, so they 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 the virus. If you cannot culture the virus, then the virus is "dead." it's inert. if it cannot replicate, it cannot infect you or others. it's just innocuous 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 pivot. 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. it did find RNA, afterall, 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.

• this study 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. That's the Science, yet no one has adjusted these tests.

Presuming it bears out, this is a key finding: It shows that many patients that are PCR+ for COV-19 are not shedding infectious virus. This would imply shorter quarantine needed and provide a testable basis for discharge of isolated patients.

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... because it's nonsense. And this same test is used for "hospitalizations" and "death with covid".

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. The last major false positive pseudo-epidemic was Swine Flu in 2009. Everyone said we would never let it happen again.

In conclusion, 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 previously in April. If there is lots more trace virus around, more people who have recovered and have fragments left over, this test could be finding a 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.

The situation we find ourselves in is that we're basing policy that is affecting billions of humans on data that is uninterpretable gibberish. 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 problem. 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 course, precisely the kind of person who winds up running a government agency. The head of the NIH is not the best scientist, but the best politician for the job. All this wild and reckless government policy has never been about the science. It's purely politics and purposeful panic.

Extracted from Tyler Durden article in ZeroHedge.com, November 22, 2020