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Wednesday, January 22, 2025

Creating numbers for the pandemic industry

Last month, I wrote an article for the Canberra Daily titled โ€œHow to create a pandemicโ€. It outlined how pandemics can be declared more easily, if not misleadingly, since 2009 when the WHO unilaterallyย redefiined the definition of โ€˜pandemicโ€™ย and the words, โ€œwith enormous numbers of deaths and illnessโ€ were suddenly excluded from the existing meaning. Hence, in the past two decades, all that has been required to declare a โ€œpandemicโ€ is cases.

Even within the medical world, a โ€œcaseโ€ is not the same as a clinical diagnosis or a disease. In general, a clinical diagnosis is based on symptoms (what the patient reports), signs (what is physically detected by the clinician), and sometimes laboratory test results. The definition of a case can mean โ€œinstance of diseaseโ€ in the narrower sense, but in the wider epidemiological sense, it simply means โ€œthe criteria for categorising an individual as a case.โ€ In other words, a case is whatever the inventor wants it to be.

Defining cases can have a role in helping us understand and manage disease outbreaks. For example, the sudden appearance in the 1950s and 1960s of cases of โ€˜phocomeliaโ€™, a condition where babies have seriously malformed limbs was linked to the drug thalidomide. In that instance, the case definition was very specific due to the newbornโ€™s unmistakable physical deformities and the unique correlation to the toxic pharmaceutical taken during the pregnancy.

Conversely, if a case definition is too broad or non-specific this can result in completely meaningless data. For example, if a case was defined by a test that could detect the presence of red blood cells then every one of us would test positive and be counted as cases.

COVID-19 cases were nonsensical because the World Health Organization published its officialย case definitionย in 2020 stating that a confirmed case was, โ€œa person with laboratory confirmation of COVID-19 infection, irrespective of clinical signs and symptoms.โ€ It meant that the cases were ultimately created through a test result that had nothing to do with whether the person had a specific disease or was even unwell at all. It is why statisticians such as Pierre Chaillot demonstrated how there was no new disease outbreak by using the official โ€œcaseโ€ numbers and other population data. The huge number of cases included individuals who were sick for all kinds of reasons and in a large proportion, individuals who had no symptoms as all.

The use of this technique to make cases appear out of thin air is surprisingly well established as we documented in our book The Final Pandemic. In fact, it can also be used in the opposite direction to make case numbers go down or even disappear, particularly when a vaccine has been introduced and needs to be portrayed as effective.

COVID-19 cases typically relied on either a polymerase chain reaction (PCR) test or a rapid antigen test (RAT) – the former amplifies selected genetic sequences, the latter reacts to particular proteins. These genetic sequences and proteins were said to be specific to SARS-CoV-2, a virus particle – that is, an infectious, disease-causing parasite consisting of genetic material surrounded by a protein coat.

The claim was that if one of these tests was positive, then the person was infected with the virus and had a disease called COVID-19. In 2020, the president of Tanzania, John Magufuli showed how preposterous this was when he had one of his laboratories apply the PCR test to non-human sources including a papaya, a quail and a goat. The result: all were positive. Did this mean that tropical fruit could also be infected with the โ€œvirusโ€ and come down with COVID-19? Clearly, these so-called diagnostic tests were not fit for purpose.

The fact that these genetic sequences and proteins can be detected on or in humans, animals, fruit and sewer water makes it plain to see that they are not specific clinical diagnostic tools. To illustrate this point further, imagine an individual who has inhaled some pollen, something we all do in our lives. If we took a nasal swab and performed a PCR test we may have a positive result for the pollenโ€™s genetic sequences. However, it would tell us nothing about the individual in question – they could be completely well, they could have symptoms of โ€˜hay feverโ€™ or they could even have died a week ago.

In this application the facts are clear: the PCR simply amplifies whatever sequences it is designed to detect, it cannot determine the relevance of their presence or whether the person (or papaya!) is afflicted with anything. (The same principle applies to the RATs.)

It is important to understand some of the key points about these tests in order to appreciate their limitations. Their widespread application and the finding of many โ€œpositivesโ€ creates not only meaningless case numbers but also an illusion that there is an โ€˜itโ€™ – that is, a claimed virus or a specific disease. It is one of the reasons that our book Virus Mania has the subtitle, โ€œHow the Medical Industry Continually Invents Epidemics, Making Billion-Dollar Profits at Our Expenseโ€. As my co-author Dr Claus Kรถhnlein explained in 2020, the only pandemics we are witnessing are those of testing.

Given the recent threats of a โ€˜bird fluโ€™ outbreak, it is vital to appreciate the true nature of these โ€œpandemicsโ€ and why there is no โ€˜itโ€™ to fear.

Dr Sam Bailey is a medical author and health educator from New Zealand. Her books include Virus Mania, Terrain Therapy and The Final Pandemic.

  • Subscribe and follow her onย Substack
  • Access Drs Mark & Sam Baileyโ€™s articles and videos atย drsambailey.com

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