CDC Specifies PCR Test Cycle Threshold For Vaccinated Individuals: What Does This Mean?
The CDC is monitoring COVID-19 "vaccine breakthrough" cases at the moment. This means that those who are fully vaccinated with the COVID-19 vaccine can still become infected. According to the CDC, "a small percentage of people who are fully vaccinated against COVID-19 will get sick and some may be hospitalized or die from COVID-19."
Throughout this pandemic, the tests used to identify "positive" COVID-19 cases has been the reverse transcriptase-polymerase chain reaction (RT-PCR) test, which can detect the virus in nasal swabs (RT-PCR). The PCR test is not actually designed to identify active infectious disease, instead, it identifies genetic material, be it partial, alive, or even dead. PCR amplifies this material in samples to find traces of COVID-19.
The CDC is requiring that clinical specimens for sequencing should have an RT-PCR Ct value ≤28 when conducting tests for vaccinated individuals. "Ct" refers to cycle threshold.
According to Public Health Ontario,
The cycle threshold (Ct) value is the actual number of cycles it takes for the PCR test to detect the virus. It indicates an estimate of how much virus was likely in the sample to start with – not the actual amount. If the virus is found in a low number of cycles (Ct value under 30), it means that the virus was easier to find in sample and that the sample started out with a large amount of the virus. Think about it like the zoom button on your computer, if you only have to zoom in a little (zoom at 110%), it means that item was big to start with. If you have to zoom a lot (zoom at 180%), it means that the item was small to start with.
Why This Is Important: It's been difficult to find what PCR Ct value tests have been using during this pandemic, and it's important because at a value at 35 or more for example, an individual is more likely to test "positive" when they are not infected and/or do not even have the ability to transmit. This is commonly known as a "false positive."
There are multiple studies showing that the number of "cycles" performed by PCR to amplify the genetic sample is directly correlated with infectiousness. The more cycles needed to get positivity from a sample, the less viral replication, or "positivity" for lack of a better word, the sample shows.
For example, an article published in the journal Clinical Infectious Diseases found that among positive PCR samples with a cycle count over 35, only 3 percent of the samples showed viral replication. The cycle number is associated with the chances of infectiousness, yet this has never really been available to the patient nor the public. Most people don't even know about it. The study examined 3790 positive samples with known CT values to see whether they harbored viable virus, indicating the patients were likely infectious. La Scola and his colleagues found that 70% of samples with CT values of 25 or below could be cultured, compared with less than 3% of the cases with CT values above 35. Cultured basically refers to the ability of the sample to find the virus and determine an infection.
This could be interpreted as,
"if someone is tested by PCR as positive when a threshold of 35 cycles or higher is used (as is the case in most laboratories in Europe & the US), the probability that said person is actually infected is less than 3%, the probability that said result is a false positive is 97%." (source)
According to Stanford Medical Professor Dr. Jay Bhattacharya, PCR samples with a cycle count over 35 is a common lab occurrence. This means that if during this pandemic this was the case, the number of false positives could have been over 90 percent, meaning the vast majority of positive cases weren't really positive. It means the number of positive "cases" were not an accurate picture of how many people were actually infectious and capable of transmitting the virus. This was and still remains a concern, because "cases" all over the world are being used to set health policy.
Bhattacharya explains in his article,
Dr. Anthony Fauci himself told This Week in Virology in July, "If you get a cycle threshold of 35 or more ... the chances of it being replication-competent are minuscule." Why then has our national testing standard never reflected this? PCR providers should work with other labs to perform a random viral culture on those who received positive results, to validate their tests in terms of being an indicator of infectiousness. Other states should emulate Florida in requiring laboratories to report cycle times to providers and to public health officials so they can provide better advice to patients and make more nuanced decisions about mandatory quarantine orders.
The World Health Organization (WHO) didn't properly address this issue, it seems, until nearly a year into the pandemic, when they put a notice on their website. They did however already make it clear that WHO guidance Diagnostic testing for SARS-CoV-2 states that careful interpretation of weak positive results is needed (1). The cycle threshold (Ct) needed to detect virus is inversely proportional to the patient’s viral load. That being said, I still couldn't find what cycle threshold was being used in any part of the world, you would think this type of information wouldn't be so hard to find?
An article published in September of 2020 in Sciencemag also brings up this issue and explains it quite well:
Ever since the coronavirus pandemic began, battles have raged over testing: Which tests should be given, to whom, and how often? Now, epidemiologists and public health experts are opening a new debate. They say testing centers should report not just whether a person is positive, but also a number known as the cycle threshold (CT) value, which indicates how much virus an infected person harbors.
Advocates point to new research indicating that CT values could help doctors flag patients at high risk for serious disease. Recent findings also suggest the numbers could help officials determine who is infectious and should therefore be isolated and have their contacts tracked down. CT value is an imperfect measure, advocates concede. But whether to add it to test results “is one of the most pressing questions out there,” says Michael Mina, a physician and epidemiologist at Harvard University’s T.H. Chan School of Public Health
Standard tests identify SARS-CoV-2 infections by isolating and amplifying viral RNA using a procedure known as the polymerase chain reaction (PCR), which relies on multiple cycles of amplification to produce a detectable amount of RNA. The CT value is the number of cycles necessary to spot the virus; PCR machines stop running at that point. If a positive signal isn’t seen after 37 to 40 cycles, the test is negative. But samples that turn out positive can start out with vastly different amounts of virus, for which the CT value provides an inverse measure. A test that registers a positive result after 12 rounds, for a CT value of 12, starts out with more than 10 million times as much viral genetic material as a sample with a CT value of 35.
But the same sample can give different CT values on different testing machines, and different swabs from the same person can give different results. “The CT value isn’t an absolute scale,” says Marta Gaglia, a virologist at Tufts University. That makes many clinicians wary, Mina says. “Clinicians are cautious by nature,” Mina says. “They say, ‘If we can’t rely on it, it’s not reliable.’” In an August letter in Clinical Infectious Diseases, members of the College of American Pathologists urged caution in interpreting CT values.
Nevertheless, Mina, Gaglia, and others argue that knowing whether CT values are high or low can be highly informative. “Even with all the imperfections, knowing the viral load can be extremely powerful,” Mina says.
Early studies showed that patients in the first days of infection have CT values below 30, and often below 20, indicating a high level of virus; as the body clears the coronavirus, CT values rise gradually. More recent studies have shown that a higher viral load can profoundly impact a person’s contagiousness and reflect the severity of disease.
They are now specifying CT values for vaccinated individuals. It's nice to see that the CDC is specifying cycle threshold, as mentioned above, for vaccinated individuals. It simply makes the detection of "positive" cases much more accurate and, as explained above, the chances of a false positive far are less when doing so. But the concern is, the testing of vaccinated individuals with this cycle threshold is less likely to reveal false positives, yet prior to the rollout of the vaccine there is reason to believe that the cycle threshold was 35 or higher, as mentioned earlier in the article. Why all of a sudden change it for vaccinated individuals? Does this mean that those who are unvaccinated will still be tested at a cycle threshold that is more likely return a false positive? Does this mean that unvaccinated individuals are likely to test positive more so than vaccinated ones, not as a result of the test but rather the cycle threshold used?
It's interesting to think about how simple adjustments of the PCR test could either increase positive cases, or decrease them. This has been an issue for quite some time. For example, earlier on in the pandemic a Portuguese appeals court ruled against the Azores Regional Health Authority, declaring the quarantining of four individuals was unlawful. One of them tested positive for COVID using a PCR test, and the other three were deemed to be high risk due to exposure, and as a result, the regional health authority forced them to undergo isolation. The appeal court heard scientific arguments from several scientists and doctors who made the case for the lack of reliability of the PCR tests in detecting the COVID-19 virus and as a result the decision was overturned.
Here's study showing that recovered patients who test negative and are non-infectious can still come up positive for COVID-19 repeatedly in the following months. These are neither new cases nor infectious ones needing quarantine but could be incorrectly counted as such.
This concern was also raised in an article published in The Lancet medical journal titled “Clarifying the evidence of SARS-CoC-2 antigen rapid tests in public health responses to COVID-19."
In the Lancet article, the authors explain that most people infected with COVID are contagious for approximately one week, and that “specimens are generally not found to contain culture-positive (potentially contagious) virus beyond day 9 after the onset of symptoms, with most transmission occurring before day 5.” They go on to explain:
This timing fits with the observed patterns of virus transmission (usually 2 days before to 5 days after symptom onset), which led public health agencies to recommend a 10-day isolation period. The sort window of transmissibility contrasts with a median 22-33 days of PCR positivity (longer with severe infections and someone shorter among asymptomatic individuals). This suggests that 50-75% of the time an individual is PCR positive, they are likely to be post-infectious.
This means that 50-75 percent of the time, just because an individual is PCR positive does not mean they have the virus or can transmit, and this is for what seems to be someone who most likely had positive. This is not referring to false positives.
Once SARS-CoV-2 replication has been controlled by the immune system, RNA levels detectable by PCR on respiratory secretions fall to very low levels when individuals are much less likely to infect others. The remaining RNA copies can take weeks, or occasionally months, to clear, during which time PCR remains positive.
They explain:
However, for public health measures, another approach is needed. Testing to help slow the spread of SARS-CoV-2 asks not whether someone has RNA in their nose from earlier infection, but whether they are infectious today. It is a net loss to the health, social, and economic wellbeing of communities if post-infectious individuals test positive and isolate for 10 days. In our view, current PCR testing is therefore not the appropriate gold standard for evaluating a SARS-CoV-2 public health test.
An article published in the British Medical Journal explains:
It’s also unclear to what extent people with no symptoms transmit SARS-CoV-2. The only test for live virus is viral culture. PCR and lateral flow tests do not distinguish live virus. No test of infection or infectiousness is currently available for routine use. As things stand, a person who tests positive with any kind of test may or may not have an active infection with live virus, and may or may not be infectious.
The relations between viral load, viral shedding, infection, infectiousness, and duration of infectiousness are not well understood. In a recent systematic review, no study was able to culture live virus from symptomatic participants after the ninth day of illness, despite persistently high viral loads in quantitative PCR diagnostic tests. However, cycle threshold (Ct) values from PCR tests are not direct measures of viral load and are subject to error.
Searching for people who are asymptomatic yet infectious is like searching for needles that appear and reappear transiently in haystacks, particularly when rates are falling. Mass testing risks the harmful diversion of scarce resources. A further concern is the use of inadequately evaluated tests as screening tools in healthy populations.
The UK’s testing strategy needs to be reset in line with the Scientific Advisory Group for Emergencies’ recommendation that “Prioritizing rapid testing of symptomatic people is likely to have a greater impact on identifying positive cases and reducing transmission than frequent testing of asymptomatic people in an outbreak area.”
This doesn't mean the test isn't useful, but there are clearly concerns. I have emailed the CDC asking them if there was a specific cycle threshold that was being used during this pandemic, prior to the rollout of the vaccine. I also asked if they will be changing the recommended threshold for unvaccinated individuals being tested.
The below comes from an anonymous source, but clams 40-45 cycles are typically used in the UK. Again, as Bhattacharya says above, in the US it seems to be 35 and above.
Corroborating Information: The Deputy Medical Officer of Ontario, Canada, Dr. Barbara Yaffe stated earlier in the pandemic that COVID-19 testing may yield at least 50 percent false positives. This means that people who test positive for COVID may not actually have it.
In July, professor Carl Heneghan, director for the centre of evidence-based medicine at Oxford University and outspoken critic of the current UK response to the pandemic, wrote a piece titled “How many Covid diagnoses are false positives?” He has argued that the proportion of positive tests that are false in the UK could also be as high as 50%.
Former scientific advisor at Pfizer, Dr. Mike Yeadon, also one of the authors of the paper discussed at the beginning of this article, argued that the proportion of positive tests that are false may actually be as high as 90%.
As far back as 2007, Gina Kolata published an article in the New York times about how declaring virus pandemics based on PCR tests can end in a disaster. The article was titled Faith in Quick Test Leads to Epidemic That Wasn’t. You can read that full story here if the previous link doesn't work.
An article written by Robert Hagen, MD for MedPage Today explains the issues with COVID testing as well, especially when it comes to results, false positives and symptomatic people compared to asymptomatic people. This article also goes in depth as to why false positives will be, and probably are very high. It's called, "What's Wrong With Covid Case Counts?"
22 researchers put out a paper explaining why, according to them, it's quite clear that the PCR test is not effective in identifying COVID-19 cases. As a result we may be seeing a significant amount of false positives. This also made a lot of noise.
Elon Musk revealed he had completed four rounds of COVID-19 testing, tweeting that something "bogus" is going on because two of the tests came back false, and the other two came back positive.
Doing tests from several different labs, same time of day, administered by RN & am requesting N1 gene PCR cycle threshold. There is no official standard for PCR testing. Not sure people realize this. - Musk (source)
On the other side of the coin,
According to Dr. Matthew Oughton, an infectious diseases specialist at the McGill University Health Centre and the Jewish General Hospital in Montreal:
”The rate of false positives with this particular test is quite low. In other words, if the test comes back saying positive, then believe it, it’s a real positive.”
According to Dr. Robert H. Shmerling, Senior Faculty Editor at Harvard Health Publishing.
False negatives – that is, a test that says you don’t have the virus when you actually do have the virus – may occur. The reported rate of false negatives is as low as 2% and as high as 37%. The false positive rate – that is, how often the test says you have the virus when you actually do not – should be close to zero. Most false-positive results are thought to be due to lab contamination or other problems with how the lab has performed the test, not limitations of the test itself
The list of these concerns and examples go on and on, yet it's something the everyday person often has no idea about as it's not brought up within the mainstream media or discussion. There are those who believe it's accurate, and there are those who don't and also evidence that goes both ways. This in of itself shows we need better testing tools to detect people who have the virus and those capable of spreading it.
The Takeaway
At the end of the day, these questions and concerns that have been brought up by many in the field have not really been appropriately addressed within mainstream discussion. Most people believe that PCR testing is sound and adequate in identifying people who are infected and also have the ability to transmit COVID, but this simply isn't true and it's very significant because "cases" are being used to set public health policy.
There's a chance that COVID may not be as infectious as the numbers indicate, and this does not mean that it's not serious and that people aren't at risk, it simply calls into question the measures that we've taken which have caused harm.
Discussing the harms of these measures is being labelled as nonsense within the mainstream. For example, anything that calls into question lockdowns as a means for helping to stop the transmission of the virus for is labelled as "anti-lockdown." World renowned scientists have been censored and ridiculed and pushed into silence. PCR tests are the basis of initiatives like vaccine passports as well.
An example I often use is of Jonas F Ludvigsson, a paediatrician at Örebro University Hospital and professor of clinical epidemiology at the Karolinska Institute is quitting his work on covid-19 because of harassment from people who dislike what he discovered. He published data showing that no school children in Sweden died of COVID during the first wave despite no mask and lockdown measures. You can read more about that story here.
It's unfortunate that the mainstream can't have these conversations regarding information, opinion and evidence that contradicts the official narrative. This type of information always seems to be labelled as "anti-something", and as a result of mainstream media ridiculing something, a large portion of the citizenry does the same. There are discussions to be had that are simply not being had, and no time or attention is being paid to experts in the field providing a perspective that opposes what our government is telling us. Why?
As a result of mass censorship, the COVID pandemic has definitely served as a catalyst for more people to question what exactly is happening on our planet. Are things really as we are told? Does government and the wealthy "1 percent" really act in ways that best serve humanity, especially in a time of crisis? Are they interested in our well being as a number one priority, or something else? Can we have appropriate conversations with people who disagree with us? Can we get along regardless of what we believe is happening?