‘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.
Later, avian flu strain A/H5N1, “even in the best-case scenarios” was to “cause 2 (million) to 7 million deaths” worldwide. A British professor named Neil Ferguson scaled that up to 200 million. It killed 440. This same Ferguson in 2002 had projected 50-50,000 deaths from so-called “Mad Cow Disease.” On its face, what possible good is a spread that large? (We shall return to this.) But the final toll was slightly over 200.
In the current crisis the most alarming model, nay probably the most influential in the implementation of the draconian quarantines worldwide, projected a maximum of 2.2 million American deaths and 550,000 United Kingdom deaths unless there were severe restrictions for 18 months or until a vaccine was developed. The primary author: Neil Ferguson. Right, Mad Cow/Avian Flu Fergie.
Then a funny thing happened. A mere nine days after announcing his model, Ferguson said a better number for the U.K. would be only 20,000. The equivalent would be fewer than 80,000 American deaths. Technically, that U.K. number was buried in a table in the report under what might be called “a fantastic case scenario.” But could that reduction possibly reflect a mere nine days of restrictions? No.
Soon all the numbers were tumbling. Yet as late as March 31, the New York Times declared: “White House Projects Grim Toll from Virus” citing White House Coronavirus Task Force head Deborah Birx and director of the National Institutes of Allergies and Infectious Diseases Anthony Fauci, who in turn cited a model showing deaths up to 240,000. Still awful, but Birx explicitly backed off the Ferguson projection for which she had previously been the Grey Lady’s pompom girl.
Then suddenly Fauci announced a flat figure of “more like 60,000,” the same number the CDC says died of flu two years ago. Probably not coincidentally, until quite recently the agency said there were 80,000 flu victims that year, before lowering it to 61,000 – presumably because people were using that figure to compare to COVID-19 deaths. In any event, the 1968-1969 “Hong Kong flu” killed an estimated 100,000 Americans, or 165,000 adjusted to today’s population.
Moreover, as noted, the CDC now encourages coding a death of anyone “if the circumstances are compelling” even though they haven’t been tested at all. Yeah, wow; it’s not a “conservative myth.” During flu season, that means a lot of flu victims have magically become COVID-19 victims in addition to people who would have otherwise had cause of death listed as heart attack, diabetes, and other co-morbid conditions.
One reason Italy had so many “coronavirus deaths” seems to be coding, even though it’s still far more strict than the new CDC guidelines. Re-evaluation of death certificates by the country’s National Institute of Health showed only “12% with direct causality from coronavirus, while 88% of patients who have died have at least one pre-morbidity – many had two or three.”
Then Fauci finally said it. “I’ve spent a lot of time on the models. They don’t tell you anything.” A few days later CDC Director Robert Redfield also turned on the computer crystal balls. “Models are only as good as their assumptions, obviously there are a lot of unknowns about the virus” he said. “A model should never be used to assume that we have a number.”
Which, of course, is exactly how both a number of public health officials and the media have used the them.
Only one significant model appears to have been correct. But wasn’t. The University of Washington’s Institute for Health Metrics and Evaluation has actually been dramatically reduced and reduced.
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. The single most cynical model is probably one regarding Sweden. Released online after the Swedish epidemic had already peaked, and with deaths at about 1,300, it nonetheless predicted a median of 96,000 Swedish COVID-19 deaths with a maximum of 183,000. WTH?
Basically the Swedes have shown dictatorial methods aren’t needed and thereby pose an incredible threat to all those who claim otherwise. This was apparently (yet another) desperate effort to convince the Swedes to lock down like everyone else – never mind that it comes after their epidemic has already crested.
The only “model” with any success is actually quite accomplished and appeared in 1840, when a “computer” was an abacus. It’s called Farr’s Law, and is actually more of an observation that epidemics grow fastest at first and then slow to a peak, then decline in a more-or-less symmetrical pattern. As you might guess from the date, it precedes public health services and doesn’t require lockdowns or really any interventions at all. Rather, the disease grabs the low-hanging fruit (with COVID-19 that’s the elderly with co-morbid conditions) and finds it progressively harder to get more fruit.
That’s not proof that public health interventions are worthless; merely that since the Plague of Athens four centuries B.C. and before, epidemics have risen and fallen quite on their own. Nobody needed Big Brother looking over their shoulder and cracking a whip; nobody needed to implode their economies and leave their citizens with tops reading: “I survived the ‘worst epidemic in history’ and all I have left is this crummy t-shirt.”
The models essentially have three purposes: 1) To satisfy the public’s need for a number, any number; 2) To bring media attention for the modeler; and 3) To scare the crap out of people to get them to “do the right thing.” That can be defined as “flattening the curve” so health care systems aren’t overridden, or encouraging people to become sheeple and accept restrictions on liberties never even imposed during wars. Like Ferguson, all the modelers know that no matter what the low end, headlines will always reflect the high end.
Assuming it’s possible to model an epidemic at all, any that the mainstream press relays will have been designed to promote panic. Take it from Fauci, who early on so eagerly employed them – they are to be ignored. Now and forever.
Read the full article here: https://issuesinsights.com/2020/04/18/after-repeated-failures-its-time-to-permanently-dump-epidemic-models/