Did Rochelle Walensky Just Demolish The Credibility Of PCR Testing?

Viral Fragments Are Not Virus. But That's What We've Been Testing

Just in case there was not enough confusion and contradiction in the government policies (and the accompanying media narrative), CDC Director Rochelle Walensky went on CBS News Wednesday morning and dropped this tiny truth bomb regarding the CDC's decision to not longer require a negative PCR in order to exit COVID-19 isolation:

On why a negative test is not required to leave isolation, Walensky said PCR tests would "not be viable" because they can detect remnants of the virus for up to 12 weeks, even after a person is no longer contagious.

Let that thought sink in for a moment: the PCR tests that both individual doctors and healthcare systems have characterized as the “gold standard”, a view echoed by the media, are, according to Director Walensky, easily led astray by “viral fragments”. The “gold standard” of diagnostic testing is likely to generate false positives in individuals who have recovered from COVID-19 illness for as long as three months.

That is the official position of the CDC.

However, while such viral fragments are easily understood after symptomatic infection, they would also appear in those who have recovered from even asymptomatic infection. They could appear in potentially anyone exposed to the SARS-CoV-2 virus, regardless of whether that exposure led to symptomatic illness.

If PCR tests hit on viral fragments for three months post-infection (and arguably post-exposure, with or without an active infection resulting), then it follows that the tests are reliably detecting viral fragments, and may or may not be detecting live virus.

Viral fragments are not how infectious respiratory disease is spread, yet that is what the world has been testing for since early 2020.

That is the logical and practical consequence of this new official position of the CDC.

Not A New Controversy

Those who have followed the trajectory of the pandemic closely are already familiar with the questions the accuracy and propriety of the PCR tests. While in theory PCR testing is an excellent way to quickly diagnose potential viral infection, in application the technology has a rather glaring Achilles Heel that has been curiously ignored by much of the media as well as most public health “experts”—it works by replicating a sample over and over until a minimum amount of virus is detected.

To understand how this can be a problem, we should first step back and understand what PCR (polymerase chain reaction) testing is and how it works.

The polymerase chain reaction (PCR) test for COVID-19 is a molecular test that analyzes your upper respiratory specimen, looking for genetic material (ribonucleic acid or RNA) of SARS-CoV-2, the virus that causes COVID-19. Scientists use the PCR technology to amplify small amounts of RNA from specimens into deoxyribonucleic acid (DNA), which is replicated until SARS-CoV-2 is detectable if present. The PCR test has been the gold standard test for diagnosing COVID-19 since authorized for use in February 2020. It’s accurate and reliable.

Each replication represents a doubling of the previous replication’s sample, making the increase in the amount of RNA exponential (2^x instead of 2 * x, where x is the number of replications, or cycles). Thus, if a sample is run through 40 replication cycles via PCR, the amount of the sample is 2^40 ( the amount of the original sample raised to the 40th power, or 1,099,511,627,776 times the original sample.

It should be intuitively obvious that errors can creep into the process, and undermine the test’s credibility, particularly over time and replication cycles. This was explored briefly by the New York Times in August of last year, which found that the high number of replication cycles (the “cycle threshold”) used in PCR testing for SARS-CoV-2 virus could result in a false positive as much as 90% of the time.

The PCR test amplifies genetic matter from the virus in cycles; the fewer cycles required, the greater the amount of virus, or viral load, in the sample. The greater the viral load, the more likely the patient is to be contagious.

This number of amplification cycles needed to find the virus, called the cycle threshold, is never included in the results sent to doctors and coronavirus patients, although it could tell them how infectious the patients are.

In three sets of testing data that include cycle thresholds, compiled by officials in Massachusetts, New York and Nevada, up to 90 percent of people testing positive carried barely any virus, a review by The Times found.

The Times concluded the cycle thresholds used were simply too high.

One solution would be to adjust the cycle threshold used to decide that a patient is infected. Most tests set the limit at 40, a few at 37. This means that you are positive for the coronavirus if the test process required up to 40 cycles, or 37, to detect the virus.

Tests with thresholds so high may detect not just live virus but also genetic fragments, leftovers from infection that pose no particular risk — akin to finding a hair in a room long after a person has left, Dr. Mina said.

Note that the Cleveland Clinic’s explanation of PCR testing quoted above makes the same observation about viral fragments.

The test could also detect fragments of the virus even after you are no longer infected.

In July of 2020, no less than Anthony Fauci conceded in an interview on This Week in Virology that high cycle thresholds were not detecting live virus.

As recounted by the independent media outlet Just The News, Fauci is quoted thus:

"What is now sort of evolving into a bit of a standard," Fauci said, is that "if you get a cycle threshold of 35 or more ... the chances of it being replication-confident are minuscule." 

"It's very frustrating for the patients as well as for the physicians," he continued, when "somebody comes in, and they repeat their PCR, and it's like [a] 37 cycle threshold, but you almost never can culture virus from a 37 threshold cycle." 

"So, I think if somebody does come in with 37, 38, even 36, you got to say, you know, it's just dead nucleotides, period." 

Yet the instructions for PCR testing developed and issued by the FDA allow for cycle thresholds up to 40.

2019-nCoV Markers (N1 and N2)
• When all controls exhibit the expected performance, a specimen is considered negative if all 2019-nCoV marker (N1, N2) cycle threshold growth curves DO NOT cross the threshold line within 40.00 cycles (< 40.00 Ct) AND the RNase P growth curve DOES cross the threshold line within 40.00 cycles (< 40.00 Ct).
• When all controls exhibit the expected performance, a specimen is considered positive for 2019-nCoV if all 2019-nCoV marker (N1, N2) cycle threshold growth curves cross the threshold line within 40.00 cycles (< 40.00 Ct). The RNase P may or may not be positive as described above, but the 2019-nCoV result is still valid.

Despite the nation’s putative top authority on COVID and infectious disease stating explicitly that cycle thresholds above 35 is detecting only “dead nucleotides” (viral fragments), the FDA has persisted in a standard well above that—a standard that in August of 2020 was suggested by the New York Times to be generating 90% false positives.

It is quite possible the CDC has understood this potentially huge flaw in the testing methodology for quite some time, as in April of this year they updated their guidance for tracking “breakthrough” infections of vaccinated individuals to exclude samples where the cycle threshold was above 28.

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.)

Note the parenthetical admission “Sequencing is not feasible with higher Ct values.”

The CDC explicitly told state-level hospital officials that specimens with a PCR cycle threshold above 28 could not be sequenced to determine the specimen’s viral lineage—which sounds very much like a tacit admission that even above 28 cycles, let alone 35, the PCR test is only detecting viral fragments.

There is also clinical research that argues against the FDA’s high cycle threshold. A study appearing in the September, 2021 issue of the Journal Of Infection And Public Health found that secondary transmission rates (one person spreading COVID-19 to another) were significantly stronger when the cycle threshold was below 30.

Our study showed that there was significant relation between Ct value cut off 30 and secondary transmission. Using ROC analysis, the ideal cut off was found to be 30.4 for any significant secondary transmission. Some experts suggest using RT-PCR Ct value or to calculate viral load which can help refine decision-making (shorter isolation etc). However, the evidence is not robust enough to definitively support this assumption.

A study appearing in the November, 2020 issue of Clinical Infectious Diseases suggested that cycle thresholds above 24 were potentially suspect.

These results demonstrate that infectivity (as defined by growth in cell culture) is significantly reduced when RT-PCR Ct values are > 24. For every 1-unit increase in Ct, the odds ratio for infectivity decreased by 32%.

Yet the 40-cycle limit remains the current FDA instruction.

Is This Why Pfizer Used Serology Testing?

Readers will recall my October article outlining the curious deviation of the Pfizer, Moderna, and Johnson and Johnson (Janssen) vaccine trials, which consistently reported within the trial pool as little as 1/10 the amount of COVID-19 infection as was being reported in the United States at the time the trials were being conducted. That deviation was very much in line with the 90% false positive rate suggested by the New York Times could be occurring.

That article also noted Pfizer used not PCR testing but serology testing to determine COVID-19 infection.

As I stated then, if the test positivity rates for the US for the time frame of the clinical trials are reduced by 90%, they line up surprisingly well with the rates of infection observed within all three clinical trials by all three vaccine manufacturers.

Was this the reason for Pfizer using serology testing as opposed to PCR testing in its trial? That information has not (yet) been disclosed by Pfizer, and the FDA continues to move at a glacial pace in releasing Pfizer’s full clinical trial documentation. For now we can—and should—ask the question, but it may be a long time before we can get a definitive answer.

We we can say now is that there is even more reason to question Pfizer’s low incidence of disease in comparison to what was happening “in the real world.” Intentionally or no, Rochelle Walensky made the damning admission that makes that question highly relevant.

Asymptomatic Cases…Not Really Cases?

In my November jeremiad on Jeffrey Zients and his execrable “winter of death” comments, I summarized the data showing that as many as 50% of COVID-19 “cases” are either asymptomatic or mild, and that as many as 50-60% of COVID-19 “hospitalizations” were patients admitted for other ailments, either without COVID symptoms or only mild symptoms, and only became “COVID” patients after testing positive post-admission.

In light of Rochelle Walensky’s statement, perhaps we can (should?) say those asymptomatic cases are not really cases at all?

Certainly the World Health Organization appears to think so. In their 13 January 2021 advisory for users of WHO-sanctioned PCR tests, they included the following guidance:

Most PCR assays are indicated as an aid for diagnosis, therefore, health care providers must consider any result in combination with timing of sampling, specimen type, assay specifics, clinical observations, patient history, confirmed status of any contacts, and epidemiological information.

In other words, a positive test alone does not a case make, but requires also a full patient workup—implying that symptoms of some sort should present before a positive test can become a case.

As I noted last year, this is actually the historical standard for diagnosis of infectious respiratory disease: a “case” is symptoms and a positive test result.

If that standard had been applied to COVID-19 the pandemic would be of far smaller dimensions.

“Casedemic”?

Those who ascribe to various alternative narratives and viewpoints on the pandemic will, with some justification, claim vindication for their view that the pandemic is nothing more than a fake “casedemic” with nothing but made up numbers, some even going so far as to argue the virus itself does not exist.

I am quite deliberately stopping short of agreeing with or accepting that perspective, but at the same time there is no denying that such perspectives must now be regarded with significantly more credulity that might have previously been the case. Certainly, if the PCR tests used to diagnose COVID-19 cases are egregiously flawed, and if the number of false positives is truly as high as 90%, the scope and nature of the pandemic as presented in the media must be substantially revised downward.

Moreover, if the tests are as fatally flawed as Rochelle Walensky’s statement implies, the diagnosis and ultimately failed treatment of those who succumbed to the disease must be re-examined—it becomes distinctly plausible that a substantial percentage of those deaths are attributable instead to misdiagnosis and medical error, that patients did not receive the proper treatment for their actual illness, but rather treatment for an illness they did not have at the time.

Short of re-evaluating prior tests in light of their cycle thresholds—which may not even be possible if that data has not been archived somewhere—there can be no definitive answers on these points. While the possibility can now be described as a probability, without that cycle threshold analysis across all cases, we can have no more certitude than this.

However, that we can reasonably have even that much certitude that the COVID-19 pandemic has been at the very least greatly exaggerated is appalling. Healthcare professionals and public health “experts” are supposed to be better than this; they are supposed to apply a prudentially skeptical mindset (a “scientific” mindset) to their analytical and diagnostic protocols.

Rochelle Walensky has all but admitted that did not happen.