PCR and the Prevalence Problem

“WHO reminds IVD users that disease prevalence alters the predictive value of test results; as disease prevalence decreases, the risk of false positive increases (2). This means that the probability that a person who has a positive result (SARS-CoV-2 detected) is truly infected with SARS-CoV-2 decreases as prevalence decreases, irrespective of the claimed specificity.


Maybe someone who believes in Germ Theory and “SARS-COV-2” can explain this conundrum to me:

PCR accuracy depends on disease prevalence.

Prevalence is calculated using the number of cases of a disease in a given population at a given time.

How the CDC calculates prevalence:


“Covid-19” can not be diagnosed based on clinical symptoms alone as they overlap with the common cold, allergies, the flu, and pneumonia. In order to confirm a case, a PCR test is used.

This creates the conundrum:

If PCR is needed to figure out how many cases of a disease is present in order to determine prevalence, yet prevalence is needed to be known in order to know whether any PCR result is accurate in order to determine cases, how can either measure (which depends on the other to be correct) be accurate?

Some background info on Prevalence:

Prevalence is a measure of how common a disease is in a specified at-risk population at a specific time point or period [2]. It measures the disease burden for the specified population [2]. Prevalence affects the pre-test probability of a disease being present and consequently impacts on the Positive Predictive Value (PPV) (the probability that subjects with a positive test truly have the disease) and the Negative Predictive Value (NPV) (the probability that subjects with a negative test truly do not have the disease) [3]. As the prevalence increases the PPV increases but the NPV decreases. Similarly, as the prevalence decreases the PPV decreases while the NPV increases [3]. The adverse outcomes associated with false positive results will be proportionally more significant during periods of low prevalence [3]. COVID19 provides a unique challenge because the prevalence of the disease is changing in real time and in line with prevention measures, principally the lockdown. This moving prevalence impacts on testing strategies and the interpretation of results. It also enables clinicians to witness the effects of prevalence and interpretation of results based on PPV and NPV in real time.”


According to this, prevalence must be known as it will have an effect on the positive and negative predictive value of any PCR test. It is known that if prevalence is low, false-positives will be high. The problem, however, is that determining prevalence based on clinical symptoms alone is impossible thus they use PCR to confirm cases. PCR can not be used to determine prevalence as it must be known beforehand to determine PCR accuracy. Prevalence must be based on symptoms and clinical diagnosis and not on PCR results. The researchers below also admit that prevalence is essential to determine the predictive value of any PCR test:

“We have developed a tool to calculate the probability of encountering an asymptomatic Covid-19 patient missed by PCR-based swab testing, using information on the known sensitivity (detection rate) and estimated specificity (1—false positive rate) of the diagnostic test, but also using information on the prevalence of disease [2], which is essential to calculate the predictive value of a positive or negative test.

To estimate the prevalence of Covid-19 we utilized a real-time database of self-reported symptoms captured through mobile phones. While not without limitations, these estimates have been validated against the results of swab testing and have predicted spikes of infection several days before they were detected [3].”


The researchers estimated prevalence based on self-reported symptoms gathered through mobile phones. They then try to claim that these results were confirmed by PCR swab testing. However, this creates a problem. As I stated previously, cases are supposed to be determined by clinical diagnosis based on symptoms. PCR can not be used to confirm that the self-reported symptoms were actually “Covid” as it’s accuracy as a test is dependent on whether disease prevalence is high/low and that the reported symptoms were actually cases of “Covid” and not, say for instance, the flu. Diseases such as the flu and “Covid-19” can NOT be distinguished based on symptoms alone as they overlap thus the self-reported symptoms would be useless as a measure of determining “Covid.” The same symptoms associated with “Covid” belong to allergies, the common cold, the flu, pneumonia, etc. and because the clinical symptoms are the same, clinical diagnosis based on symptoms alone is not enough to differentiate these diseases in order to determine prevalence.

Same symptoms, same disease.

To further establish the impossibility of diagnosing “Covid-19” based on clinical symptoms alone , the below sources are in reference to trying to distinguish between the flu and “Covid-19:”

“Because Covid-19 and the flu present very similarly, they are nearly impossible to differentiate based on symptoms alone. Accurate diagnosis requires laboratory testing to identify genetic or molecular components of the infecting virus.”


“Because some of the symptoms of flu and Covid-19 are similar, it may be hard to tell the difference between them based on symptoms alone, and testing may be needed to help confirm a diagnosis.


“This is going to be a really challenging flu season because it’s very difficult to tell the difference between Covid-19 and the flu based on symptoms alone. We don’t have a great way of differentiating the two other than testing,” Dr. Favini said.”


According to the above sources, it is impossible to differentiate between the flu and “Covid-19” based on clinical symptoms and diagnosis. They claim testing is needed in order to confirm the diagnosis. If that is the case, prevalence can not be known for “Covid-19” as there is no way to distinguish it from the flu via symptoms alone without the use of PCR.

PCR results can not be interpreted accurately without knowing prevalence.

By this measure alone, PCR tests are not accurate as prevalence can not be determined without using PCR to confirm cases.

A test can not be used to determine the accuracy of itself.

So how would one determine the accuracy of the PCR test if prevalence is impossible to determine based on symptoms alone? The only way is through calibration and validation of the PCR tests using properly purified/isolated “virus” taken directly from a sick human. An important excerpt from the amazing article  “COVID19 PCR Tests are Scientifically Meaningless” by Torsten Engelbrecht solidifies this point:

Apart from the fact that it is downright absurd to take the PCR test itself as part of the gold standard to evaluate the PCR test, there are no distinctive specific symptoms for Covid-19, as even people such as Thomas Löscher, former head of the Department of Infection and Tropical Medicine at the University of Munich and member of the Federal Association of German Internists, conceded to us[2].

And if there are no distinctive specific symptoms for Covid-19, Covid-19 diagnosis — contrary to Watson’s statement — cannot be suitable for serving as a valid gold standard.

In addition, “experts” such as Watson overlook the fact that only virus isolation, i.e. an unequivocal virus proof, can be the gold standard.


Properly purified/isolated “virus” is the only way to determine the accuracy of any PCR test. However, this is never done as no actual “viral” isolates exist. Two of the most widely used PCR tests (Drosten and the CDC) created their PCR tests without any “virus” material available.

From the Drosten PCR test paper:

“In the present case of 2019-nCoV, virus isolates or samples from infected patients have so far not become available to the international public health community. We report here on the establishment and validation of a diagnostic workflow for 2019-nCoV screening and specific confirmation, designed in absence of available virus isolates or original patient specimens. Design and validation were enabled by the close genetic relatedness to the 2003 SARS-CoV, and aided by the use of synthetic nucleic acid technology.”


This is from the FDA emergency use authorization of the CDC’s PCR test used in the USA:

Since no quantified virus isolates of the 2019-nCoV are currently available, assays designed for detection of the 2019-nCoV RNA were tested with characterized stocks of in vitro transcribed full length RNA (N gene; GenBank accession: MN908947.2) of known titer (RNA copies/µL) spiked into a diluent consisting of a suspension of human A549 cells and viral transport medium (VTM) to mimic clinical specimen.”


Without properly purified/isolated “virus,” PCR accuracy can not be confirmed. Without PCR, “Covid-19” cases cannot be confirmed and prevalence is unknown. Without knowing disease prevalence, PCR accuracy is unknown. See the problem here?

Prevalence or PCR. Which comes first? The chicken or the egg?

This is an example of circular reasoning at its finest.



Leave a comment

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: