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How Fauci got his sums wrong


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https://www.sott.net/article/441024-The-1-blunder-How-a-simple-but-fatal-math-mistake-by-US-Covid-19-experts-caused-the-world-to-panic-and-order-lockdowns

 

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With Covid, a similar mistake happened. One type of fatality rate was substituted for another. The wrong rate was then used to predict the likely death rate - and, as with NASA, no-one picked up the error. 

In order to understand what happened, you have to understand the difference between two medical terms that sound the same - but are completely different. Rather like a pound second or a Newton second. 

Which fatality rate, did you say? 

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 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. 

Now, clearly, you do not want to get these figures mixed up. By doing so you would either wildly overestimate, or wildly underestimate, the impact of Covid. But mix these figures up, they did. 

The error started in America, but didn't end there. In healthcare, the US is very much the dog that wags the tail. The figures they come up with are used globally. 

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1 hour ago, Southmartin said:

https://www.sott.net/article/441024-The-1-blunder-How-a-simple-but-fatal-math-mistake-by-US-Covid-19-experts-caused-the-world-to-panic-and-order-lockdowns

 

snippet:

 

With Covid, a similar mistake happened. One type of fatality rate was substituted for another. The wrong rate was then used to predict the likely death rate - and, as with NASA, no-one picked up the error. 

In order to understand what happened, you have to understand the difference between two medical terms that sound the same - but are completely different. Rather like a pound second or a Newton second. 

Which fatality rate, did you say? 

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 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. 

Now, clearly, you do not want to get these figures mixed up. By doing so you would either wildly overestimate, or wildly underestimate, the impact of Covid. But mix these figures up, they did. 

The error started in America, but didn't end there. In healthcare, the US is very much the dog that wags the tail. The figures they come up with are used globally. 

In the UK, the group I call the Mad Modellers of lockdown, the Imperial College experts, created the same panic. On March 16, they used an estimated IFR of 0.9 percent to predict that, without lockdown, Covid would kill around 500,000 in the UK.

 

 

Aside from the rough arse numbers, what needs to be asked is - Who's going to die?

If, like Covid, its people in their last ~12 months of life, then its fuck it.

 

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