Publisher's note: The author of this post is Mitch Kokai for the John Locke Foundation.
Michael Fumento argues
at Issues and Insights that it's time to "dump" models used to predict epidemics'
- "The ... crisis we face is unparalleled in modern times," said the World Health Organization's assistant director, while its director general proclaimed it "likely the greatest peacetime challenge that the United Nations and its agencies have ever faced." This was based on a CDC computer model projection predicting as many as 1.4 million deaths from just two countries.
- So when did they say this about COVID-19? Trick question: It was actually about the Ebola virus in Liberia and Sierra Leone five years ago, and the ultimate death toll was under 8,000.
- With COVID-19 having peaked (the highest date was April 4), despite the best efforts of the Centers for Disease Control and Prevention to increase numbers by first saying any death with the virus could be considered a death from the virus and then again this week by saying a positive test isn't even needed, you can see where this is going.
- Since the AIDS epidemic, people have been pumping out such models with often incredible figures. For AIDS, the Public Health Service announced (without documenting) there would be 450,000 cases by the end of 1993, with 100,000 in that year alone. The media faithfully parroted it. There were 17,325 by the end of that year, with about 5,000 in 1993. SARS (2002-2003) was supposed to kill perhaps "millions," based on analyses. It killed 744 before disappearing. ...
- ... Model defenders declare the plummets were based on the success of severe restrictions of civil liberties. "It just means we won," declared an article in The Atlantic. Wrong. The bottom range of the models presumes the best-case scenario. If the low end is 100,000, that's the low end.
- If epidemic models were just haphazardly wrong, we would expect about half the time they would be too low. Instead, they're almost universally vastly too high. This isn't happenstance but intentional.
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