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IPFS News Link • Social Engineering

LOCKDOWN LUNACY: the thinking person's guide

• J B Handley Blog

By J.B. Handley

For anyone willing to look, there are so many facts that tell the true story, and it goes something like this:

Knowing what we know today about COVID-19's Infection Fatality Rate, asymmetric impact by age and medical condition, non-transmissibility by asymptomatic people and in outdoor settings, near-zero fatality rate for children, and the basic understanding of viruses through Farr's law, locking down society was a bone-headed policy decision so devastating to society that historians may judge it as the all-time worst decision ever made. Worse, as these clear facts have become available, many policy-makers haven't shifted their positions, despite the fact that every hour under any stage of lockdown has a domino-effect of devastation to society. Meanwhile, the media—with a few notable exceptions—is oddly silent on all the good news. Luckily, an unexpected group of heroes across the political landscape—many of them doctors and scientists—have emerged to tell the truth, despite facing extreme criticism and censorship from an angry mob desperate to continue fighting an imaginary war.

My goal is to engage in known facts. You, the reader, can decide if all of these facts, when you put them together, equate to the story above.

Fact #1: The Infection Fatality Rate for COVID-19 is somewhere between 0.07-0.20%, in line with seasonal flu

The Infection fatality Rate math of ANY new virus ALWAYS declines over time as more data becomes available, as any virologist could tell you. In the early days of COVID-19 where we only had data from China, there was a fear that the IFR could be as high as 3.4%, which would indeed be cataclysmic. On April 17th, the first study was published from Stanford researchers that should have ended all lockdowns immediately, as the scientists reported that their research "implies that the infection is much more widespread than indicated by the number of confirmed cases" and pegged the IFR between 0.12-0.2%. The researchers also speculated that the final IFR, as more data emerged, would likely "be lower." For context, seasonal flu has an IFR of 0.1%. Smallpox? 30%.

As the first study to peg the IFR, the Stanford study came under withering criticism, prompting the lead researcher, Dr. John Ioannidis to note,

"There's some sort of mob mentality here operating that they just insist that this has to be the end of the world, and it has to be that the sky is falling. It's attacking studies with data based on speculation and science fiction. But dismissing real data in favor of mathematical speculation is mind-boggling."

Like all good science, the Stanford data on IFR has now been replicated so many times that our own Centers for Disease Control came out this week to announce that their 'best estimate' showed an IFR below 0.3%. In this article on the CDC's new data, they also highlighted how the cascading declines in IFR has removed all the fears of doomsday:

That "best estimate" scenario also assumes that 35 percent of infections are asymptomatic, meaning the total number of infections is more than 50 percent larger than the number of symptomatic cases. It therefore implies that the IFR is between 0.2 percent and 0.3 percent. By contrast, the projections that the CDC made in March, which predicted that as many as 1.7 million Americans could die from COVID-19 without intervention, assumed an IFR of 0.8 percent. Around the same time, researchers at Imperial College produced a worst-case scenario in which 2.2 million Americans died, based on an IFR of 0.9 percent.

If you're still unconvinced that the IFR of COVID-19 is roughly in line with a bad flu season, the most comprehensive analysis I have seen comes from Oxford University, who recently stated:

"Taking account of historical experience, trends in the data, increased number of infections in the population at largest, and potential impact of misclassification of deaths gives a presumed estimate for the COVID-19 IFR somewhere between 0.1% and 0.41%."