Tyler Durden explains at Zero Hedge Caught Red-Handed: CDC Changes Test Thresholds To Virtually Eliminate New COVID Cases Among Vaxx’d. Excerpts in italics with my bolds.
New policies will artificially deflate “breakthrough infections” in the vaccinated, while the old rules continue to inflate case numbers in the unvaccinated.
The US Center for Disease Control (CDC) is altering its practices of data logging and testing for “Covid19” in order to make it seem the experimental gene-therapy “vaccines” are effective at preventing the alleged disease.
They made no secret of this, announcing the policy changes on their website in late April/early May, (though naturally without admitting the fairly obvious motivation behind the change).
The trick is in their reporting of what they call “breakthrough infections” – that is people who are fully “vaccinated” against Sars-Cov-2 infection, but get infected anyway.
Essentially, Covid19 has long been shown – to those willing to pay attention – to be an entirely created pandemic narrative built on two key factors:
- False-positive tests. The unreliable PCR test can be manipulated into reporting a high number of false-positives by altering the cycle threshold (CT value)
- Inflated Case-count. The incredibly broad definition of “Covid case”, used all over the world, lists anyone who receives a positive test as a “Covid19 case”, even if they never experienced any symptoms.
Without these two policies, there would never have been an appreciable pandemic at all, and now the CDC has enacted two policy changes which means they no longer apply to vaccinated people.
Firstly, they are lowering their CT value when testing samples from suspected “breakthrough infections”.
From the CDC’s instructions for state health authorities on handling “possible breakthrough infections” (uploaded to their website in late April):
For cases with a known RT-PCR cycle threshold (Ct) value, submit only specimens with Ct value ≤28 to CDC for sequencing. (Sequencing is not feasible with higher Ct values.)
Throughout the pandemic, CT values in excess of 35 have been the norm, with labs around the world going into the 40s.
Essentially labs were running as many cycles as necessary to achieve a positive result, despite experts warning that this was pointless (even Fauci himself said anything over 35 cycles is meaningless).
But NOW, and only for fully vaccinated people, the CDC will only accept samples achieved from 28 cycles or fewer. That can only be a deliberate decision in order to decrease the number of “breakthrough infections” being officially recorded.
Secondly, asymptomatic or mild infections will no longer be recorded as “covid cases”.
That’s right. Even if a sample collected at the low CT value of 28 can be sequenced into the virus alleged to cause Covid19, the CDC will no longer be keeping records of breakthrough infections that don’t result in hospitalisation or death.
From their website:
As of May 1, 2021, CDC transitioned from monitoring all reported vaccine breakthrough cases to focus on identifying and investigating only hospitalized or fatal cases due to any cause. This shift will help maximize the quality of the data collected on cases of greatest clinical and public health importance. Previous case counts, which were last updated on April 26, 2021, are available for reference only and will not be updated moving forward.
Just like that, being asymptomatic – or having only minor symptoms – will no longer count as a “Covid case” but only if you’ve been vaccinated.
The CDC has put new policies in place which effectively created a tiered system of diagnosis. Meaning, from now on, unvaccinated people will find it much easier to be diagnosed with Covid19 than vaccinated people.
Consider…
- Person A has not been vaccinated. They test positive for Covid using a PCR test at 40 cycles and, despite having no symptoms, they are officially a “covid case”.
- Person B has been vaccinated. They test positive at 28 cycles, and spend six weeks bedridden with a high fever. Because they never went into a hospital and didn’t die they are NOT a Covid case.
- Person C, who was also vaccinated, did die. After weeks in hospital with a high fever and respiratory problems. Only their positive PCR test was 29 cycles, so they’re not officially a Covid case either.
The CDC is demonstrating the beauty of having a “disease” that can appear or disappear depending on how you measure it.
To be clear: If these new policies had been the global approach to “Covid” since December 2019, there would never have been a pandemic at all.
If you apply them only to the vaccinated, but keep the old rules for the unvaccinated, the only possible result can be that the official records show “Covid” is much more prevalent among the latter than the former.
This is a policy designed to continuously inflate one number, and systematically minimise the other.
What is that if not an obvious and deliberate act of deception?
Background: Four Myths Drove Covid Madness
Myth: Sars-CV2 is a new virus and we have no defense.
Fact: Sars-CV2 has not been scientifically established as a virus.
Myth: Testing positive for Sars-CV2 makes you a disease case and a spreader.
Fact: PCR tests say nothing about you being ill or infectious.
Myth: Millions of people have died from Covid19.
Fact: Life expectancy is the same before and after Covid19.
Myth: Wearing masks prevents viral infection.
Fact: Evidence shows masks are symbolic, not effective.
Jack Kerwick has written a series of articles at FrontPage Mag over the last year discussing how facts have been overwhelmed by fears, a mythology replacing scientific knowledge and reason. From the beginning this contagion was different, being the first one in an age of 24/7 cable news and rampant social media. So emotion and exaggeration were spread and political leaders pressured to act as protectors, clamping down on social and economic transactions. This post provides a synopsis of what went wrong, based on Kerwick’s recent essay Masks and Stopping COVID. Excerpts in italics with my bolds.
What the science – lots of science – really tells us.
In previous essays, I argued for three theses against the prevailing COVID Orthodoxy:
(1)SARS-CoV-2 has never been isolated, purified, and extracted in accordance with the scientific method that has long been in place for isolating, purifying, and extracting other viruses (like bacteriophages and “giant viruses”), and neither has the scientific method been observed with respect to establishing whether this virus is in fact the cause of a disease called “COVID-19.”
Discussion:
Has the existence of “the Virus” been established according to a universally acknowledged set of scientific procedures that must be observed to establish the existence of any and all other viruses?
From the sounds of it, the answer is a resounding no.
Dr. Tom Cowan, Dr. Andrew Kaufman, and Sally Fallon Morell, are among those who have noted in a paper published last year that in demonstrating the existence of a new virus, samples must, firstly, be taken from the blood, phlegm, or other secretions of hundreds of people exhibiting symptoms that are “unique and specific enough to characterize an illness.”
Then, “without mixing these samples with ANY tissue or products that also contain genetic material, the virologist macerates, filters, and ultracentrifuges, i.e. purifies the specimen.” This, the authors explain, is a “common virology technique, done for decades to isolate bacteriophages [viruses that infect bacteria and reproduce within them] and so-called giant viruses [a virus larger than typical bacteria].”
Thirdly, once virologists perform this procedure, they are then able to “demonstrate with electron microscopy thousands of identically sized and shaped particles.” The latter are “the isolated and purified virus.”
Fourthly, upon determining the purity of these particles, virologists are able to examine their “structure, morphology, and chemical composition [.]”
Fifthly, “the genetic makeup” of the particles [the virus] “is characterized by extracting the genetic material directly from” them and “using genetic-sequencing techniques” that have long been in existence.
Finally, an analysis must be conducted to prove that “these uniform particles are exogenous (outside) in origin” as viruses are held to be and not just “the normal breakdown of products of dead and dying tissues.”
The authors conclude: “If we have come this far then we have fully isolated, characterized, genetically-sequenced an exogenous virus particle” .
They add that nowhere in the literature does it show that any of these steps have been taken with respect to SARS-CoV-2.
Neither—and this is crucial—have the scientific steps for determining that SARS-CoV-2 is the cause of a disease, COVID-19, been taken. What are these steps? There really isn’t much to it:
A group of healthy subjects, typically animals, is first exposed to “this isolated, purified virus in the manner in which the disease is thought to be transmitted.”
Subsequently, virologists will wait to determine whether these subjects fall ill with “the same disease, as confirmed by clinical and autopsy findings [.]” If so, “one has now shown that the virus actually causes a disease.” In other words, the “infectivity and transmission of an infectious agent” will have been demonstrated.
Again, according to the authors, nothing like this has been performed to show that
there is a virus, SARS-CoV-2, that causes what has become known as COVID-19.
An ever growing number of citizen journalists in over ten different countries from around the world have, via the Freedom of Information Acts of their respective homes, requested from scores of health agencies an account of the process by which SARS-CoV-2 has been isolated (i.e. separated out from all other stuff). To date, no account has been provided.
(2) The explosion of COVID “cases” is an illusion generated by a combination of two things: (a) the redefining of a “case” from meaning “infection in need of medical attention”—which is how it was defined in the pre-COVID era—to meaning “anyone who is presumed to have, or to have had, COVID and/or anyone who tests positive for COVID” plus (b) an intrinsically limited PCR test that is deliberately run at a number of cycles guaranteed to produce a tsunami of false-positives.
The official case numbers, in other words, are meaningless.
Discussion:
Right from the jump, it’s crucial to take note of the fact that for the first time ever, beginning just last year, “cases” was radically redefined in such a way that would have been unthinkable in just February of 2020 (one month before The Virus Apocalypse engulfed the universe).
For starters, as indicated above, many of these “cases,” per the CDC, included those patients who were labeled as “probable” carriers of the virus. This means that they were diagnosed as “cases” in the absence of any “confirmatory laboratory testing.” And yet they were identified as COVID “cases.”
Moreover, even when testing is figured into it, with respect to no other virus or disease has the CDC ever counted as a “case” a merely positive test. A positive test, in other words, has never been regarded by the medical establishment as sufficient grounds upon which to determine a “case.” Rather, in order for something to count as a “case,” a person had to have been sick and in need of medical attention like, say, hospitalization.
In the COVID era, however, the CDC began accumulating positive PCR test results (about more of which will be said below) from people the vast majority of whom are “asymptomatic,” meaning they feel just fine, and combining them with positive antibodies tests from people who also feel just fine: The final sum, this compound, comprises all “cases.”
Now, as for those PCR tests: There are two problems.
First, as Karry Mullis bluntly remarked: “Quantitative PCR is an oxymoron.” Who was Karry Mullis? He was the inventor of the PCR test. And he won a Nobel Prize in Science for this achievement. What did the late Dr. Mullis mean by his characterization of his own invention?
“PCR is intended to identify substances qualitatively, but by its very nature is unsuited for estimating numbers [of viruses]. Although there is a common misimpression that the viral load tests actually count the number of viruses in the blood, these tests cannot detect free, infectious viruses at all; they can only detect proteins that are believed, in some cases wrongly, to be unique to HIV. The tests can detect genetic sequences of viruses, but not viruses themselves” (emphases added).
Lauitsen explains further:
“What PCR does is to select a genetic sequence and then amplify it enormously. It can accomplish the equivalent of finding a needle in a haystack; it can amplify that needle into a haystack. Like an electronically amplified antenna, PCR greatly amplified the signal, but it also greatly amplifies the noise” (emphases added).
What this implies is that given that “the amplification is exponential, the slightest error in measurement, the slightest contamination, can result in errors of many orders of magnitude.”
There is still another problem with the PCR test as it is currently being used that guarantees its utter worthlessness. More exactly, that guarantees that the “case” numbers built upon it are wholly inaccurate and, hence, meaningless.
This past fall, none other than the New York Times noted that possibly as high as 90% of all positive test results are false.
Per the CDC and FDA guidelines, the vast majority of PCR tests are run at a threshold of 40 cycles. Dr. Michael Mina, an epidemiologist from Harvard who is quoted in the Times piece, notes that when PCR tests are run at 35 or more cycles, they “may detect not just live virus but also live fragments, leftovers from infection that pose no particular risks—akin to finding a hair in a room long after a person has left.”
The French researcher Didier Raoult has shown that when the PCR test is run at 25 cycles, about 70% of samples were genuinely positive—meaning infectious. However, when the test is run at a threshold of 30 cycles, only 20% of samples were infectious. At 35 cycles, but three percent of samples were infectious.
And when the test was run above 35 cycles? Zero samples were infectious.
(3)People are getting sick and dying from all manner of things from which people get sick and die each and every year. Only throughout this past year, these causes of sickness and death have been repackaged as COVID sickness and death.
Discussion:
Think about it: a cough, running nose, sore throat, chills, chest congestion, fever, loss of taste and smell—these are all symptoms of a plethora of things, from the common cold to seasonal influenza and a whole lot else. Particularly since the vast majority of COVID cases are “mild,” it’s with the greatest of ease that any single one of these symptoms or any number of combinations of them can be used as a pretext by which to establish a “COVID case.”
This is not necessarily to say that the symptoms in question are not signs of COVID or the SARS-CoV-2 virus that is claimed to be its cause. It’s only to note that in the absence of scientifically confirming definitively that (a) there is a unique strain of a coronavirus called SARS-CoV-2, (b) that it is the cause of something called COVID-19, and that, (3) given the scandalously unreliable PCR test, people do in fact have COVID, symptoms that are associated with the latter are more economically, more plausibly explained by way of reference to illnesses that have long been with us.
The Principle of Parsimony—better known since the 14th century as “Ockham’s Razor”—applies: When confronted with two or more explanatory hypotheses, all things being equal, reason dictates that we opt for the one that is simplest.
Since many of the symptoms now being associated with COVID until recently were explained in terms of, say, the flu, and, given the foregoing facts regarding the science—or lack of science—behind the COVID Narrative, it makes better sense to continue explaining those symptoms in terms of the flu.
Indeed, there is no doubt that a great shell game has been transpiring for a year now as cases of various illnesses have been re-labeled as COVID cases.
For example, over at John Hopkins University, Genevieve Briand, assistant program director of the Applied Economics master’s program, used data from the CDC to analyze the effect of COVID-19 deaths in America on all other deaths. Reasonably enough, she had expected to witness a substantial number of excess deaths in 2020, i.e. deaths by all other causes plus the orgy of COVID deaths with which politicians and those in the media had been singularly preoccupied.
She was mistaken. Sorely mistaken. Yanni Gu, a writer for the university’s student newspaper, reports: “Surprisingly, the deaths of older people stayed the same before and after COVID-19.”
This was surprising because COVID (not unlike virtually everything else) overwhelmingly affects elderly people. Thus, “experts expected an increase in the percentage of deaths in older age groups. However, this increase is not seen from the CDC data.” Furthermore, “the percentages of deaths among all age groups remain relatively the same” (emphases added).
Whoa. Briand would soon discover that the plot was just beginning to thicken. What the “data analyzes suggest,” Gu writes, is “that in contrast to most people’s assumptions, the number of deaths by COVID-19 is not alarming. In fact, it has relatively no effect on deaths in the United States” (emphases added).
There is a perfectly rational, and simple, explanation to account for the unbridgeable chasm between the media-concocted perception of COVID and the reality that Briand discovered:
Deaths from all other causes were being re-classified—misclassified—as death from COVID. And how did Briand determine this?
For the first time ever, deaths from all other causes—heart diseases, respiratory diseases, influenza, and pneumonia—decreased.
Especially shocking was the realization that heart disease, which has always been the number one killer in America, appeared to have suddenly lost that distinction with the onset of COVID.
Moreover, deaths from all other causes decreased just in proportion to the extent to which COVID deaths increased. “This trend is completely contrary to the pattern observed in all previous years. Interestingly…the total decrease in deaths by other causes almost exactly equals the increase in deaths by COVID-19.”
Within 24 or so hours of the publication of the article relaying Genevieve Briand’s discoveries, the student paper at John Hopkins University retracted it. They never, however, denied the truth of a single syllable of either Briand’s analysis nor its summary of it. That it was political pressure, and not shoddy scholarship that informed its decision is clear, for the school paper saved its article in a PDF file (to which I link above) for all of the world to read.
Wearing of Masks is Not Supported by Scientific Evidence
In this essay, we will revisit the topic of masks. I’ve already written about the psychological, moral, and social costs of mask-wearing. Here, I will focus specifically on the science—or lack of science—behind it.
Scientists recognize that the RCT—Randomized Control Trial—is the “gold standard” as far as “effectiveness research” is concerned. Drs. Eduardo Hariton and Joseph J. Locasio explain that randomization “reduces bias” while providing “a rigorous tool” by which “to examine cause-effect relationships between an intervention and outcome.” RCTs eliminate the risk of confirmation bias, something that is “not possible with any other study design” (emphases added).
This is critical for our purposes, for the largest study of the effectiveness of mask-wearing by the general public to thwart the transmission of COVID utilized not one, not two, not three, but a staggering 14 randomized control trials.
The study was performed at the University of Hong Kong. What Dr. Jingyi Xiao and her team of researchers there concluded will doubtless be written off as the stuff of “conspiracy theorists” by Mask Nation. So be it. But those on the editorial board of Emerging Infectious Diseases, the widely esteemed journal of none other than the Centers for Disease Control and Prevention (CDC), determined that the findings were worth publishing.
The verdict: Masks are ineffective.
The authors of a review of studies on face masks published last year by the Oxford Centre for Evidence-Based Medicine determined that there is no evidence indicating the effectiveness of cloth masks when it comes to COVID. They lament how the “abandonment of the scientific modus operandi and lack of foresight has left the field [of science] wide open for the play of opinions, radical views and political influence.”
The authors, one an epidemiologist, the other a professor of Evidence-Based Medicine at Oxford, do note that all randomized control trials that have been conducted over the last decade or so have demonstrated that “masks alone have no significant effect in interrupting the spread of ILI [Influenza-Like-Illness] or influenza” in neither “the general population…nor in healthcare workers” (emphases added).
We could continue in this same repetitive vein. Readers who are interested in pursuing this topic further can check out this piece of mine from October of last year. I review still other studies there, including remarks from such media-adored “Experts” as Anthony Fauci that dovetail seamlessly with these findings on the essential uselessness of masks with respect to COVID. More research confirming these findings are here, here, here, here, and here. Neither have we yet touched upon the numerous studies showing that countries and states with mask mandates did no better and, in some instances, worse than those places that had no such mandates. Nor have we looked at those studies demonstrating that those who faithfully wore masks were not less likely to contract COVID than those who did not wear masks, with some of these—like this one from the CDC—showing that most people who became infected with COVID wore a mask “always” or “often.”
The science, it should now be obvious, does not support Mask dogma.
Science Matters 