Forgets Reporting That Upwards Of 90% Of COVID-19 Test Results May Be Inaccurate
Great Game India recently published an article written by Dr. Malcolm Kendrick, doctor and author who works as a General Practitioner in the National Health Service in England. That article – “The Coronavirus Mathematical Blunder That Plunged The World Into Chaos & Lockdown” – addresses the mathematical errors that occurred early on in the coronavirus crisis.
“When you strip everything else out, the reason for lockdown comes from a single figure: one percent. This was the prediction that COVID, if left unchecked, would kill around one percent of us.”
Dr. Kendrick explains that two different fatality rate figures were mixed up.
First, there’s the Infection Fatality Rate (IFR). This is the total number of people who are infected by a disease and the number of them who die. This figure includes those who have no symptoms at all, or only very mild symptoms – those who stayed at home, coughed a bit and watched Outbreak.
Then there’s the Case Fatality Rate (CFR). This is the number of people suffering serious symptoms, who are probably ill enough to be in (a) hospital. Clearly, people who are seriously ill – the “cases” – are going to have a higher mortality rate than those who are infected, many of whom don’t have symptoms.
Put simply – all cases are infections, but not all infections are cases.
Which means that the CFR will always be far higher than the IFR. With influenza, the CFR is around ten times as high as the IFR. COVID seems to have a similar proportion.
So, they matched up the one percent CFR of COVID with the incorrect 0.1 percent CFR of flu. Suddenly, COVID was going to be ten times as deadly.
world, panicked. Because they were told COVID was going to be ten times worse than influenza. They could see three million deaths in the US alone, and 70 million around the world.
If influenza killed 50, COVID was going to kill 500. If influenza killed a million, COVID was going to get 10 million. No wonder Congress, then the world, panicked. Because they were told Covid was going to be ten times worse than influenza. They could see three million deaths in the US alone, and 70 million around the world.
On February 28 it was estimated that COVID was going to have about the same impact as a bad influenza season – almost certainly correct. Eleven days later, the same group of experts predicted that the mortality rate was going to be ten times as high. This was horribly, catastrophically… wrong.Dr. Kendrick, Great Game India
To restate: Positive test results do not indicate a COVID-19 case.
This does not include inaccurate lab results – where labs in Florida and elsewhere had extremely high positive COVID test results. This is the CDC saying that the testing threshold for COVID-19 was never properly set for all of these tests.
How can anyone – the public or even doctors and health officials – actually know what is going on when the testing is now reported to be this faulty.
How are parents supposed to evaluate whether their children should be in “in-person” school? Whether they or their children should wear masks? Colleges are sending home students because “large numbers” have tested positive. Are they symptomatic?
Perhaps we should be reporting on actual cases, as we have done in the past – those who are symptomatic and being treated for COVID-19 symptoms whether in a doctor’s office or hospital setting.
A new medical study, notes that based on the lack of thresholds set for the COVID-19 PCR based tests and the number of false positive results that “positive result in asymptomatic individuals that haven’t been confirmed by a second test should be considered suspect.”
Unlike previous epidemics, in addressing COVID-19 nearly all international health organizations and national health ministries have treated a single positive result from a PCR-based test as confirmation of infection, even in asymptomatic persons without any history of exposure. This is based on a widespread belief that positive results in these tests are highly reliable. However, data on PCR-based tests for similar viruses show that PCR-based testing produces enough false positive results to make positive results highly unreliable over a broad range of real-world scenarios. This has clinical and case management implications, and affects an array of epidemiological statistics, including the asymptomatic ratio, prevalence, and hospitalization and death rates. Steps should be taken to raise awareness of false positives, reduce their frequency, and mitigate their effects. In the interim, positive results in asymptomatic individuals that haven’t been confirmed by a second test should be considered suspect.