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officially called SARS-COV-2.
on Monday, March 16, Imperial College publicly released its now-infamous research report (https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf) predicting coronavirus might kill a half-million Britons and two million Americans if governments didn’t act immediately to close schools and businesses.
When I read the report that Monday night, I noticed a chart on page 5 showing the likelihood of death in different age ranges. The chart showed coronavirus was more than 100 times as likely to kill people over 80 than under 50. Yes, 100 times. People under 30 were at very low risk. The
Why wasn’t the media telling the truth about the huge difference in risk by age?
March 25, the lead author of the Imperial College report, professor Neil Ferguson, testified about coronavirus to a committee of the British Parliament. Ferguson calls himself an epidemiologist, though he is not a physician and his doctorate is in theoretical physics.
was in a self-imposed home quarantine. (Later, a British newspaper would break the news that Ferguson had violated his isolation to have sex with a married
woman he met on ...
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he was forced to resign in disgrace from a scientific committee advising the British government on the epidemic. But at the time his reputation was sterling and his previous forecasting mistakes – which are legion and in some cases comical – largely forgotten.) Ferguson’s testimony to the committee received no attention in the US. American media were focused on the emerging crisis in New York City. But British newspapers reported that Ferguson had dramatically changed his predictions. He now said his new best estimate was 20,000 Britons would die from the virus even with just weeks of
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Investigative reporters have an old saw: If your mother says she loves you, check it out.
The day after Ferguson’s testimony, March 26, I raised questions about his revised estimate in a series of tweets. For better or worse, people noticed. The most notable was Elon Musk, who besides being the founder of Tesla and SpaceX has a huge Twitter
University of Washington used to predict hospitalizations and intensive care needs was proving hugely wrong in its forecasts – even in New York, where the problems were worst.
models were profoundly overestimating the number of people who would need to be hospitalized with SARS-COV-2 became self-evident. Despite repeated revisions, the model from the University of Washington continued to fail – not after months or even weeks, but on a daily basis.
Hospitals outside New York were mostly empty and furloughing workers. Worse, in some cases they were shutting down because they had so few patients – a bizarre paradox in what was supposed to be the worst epidemic since the Spanish Flu a century before. (https://www.alvareviewcourier.com/story/2020/04/10/regional/oklahoma-city-hospital-closed-amid-coronavirus-spread/62038.html)
In late March, New York governor Andrew Cuomo had said the state might need 140,000 hospital beds and up to 40,000 ventilators. “Everybody’s entitled to their own opinion, but I don’t operate here on opinion. I operate on facts and on data and on numbers and on projections,” Cuomo said. https://www.syracuse.com/coronavirus/2020/03/cuomo-refutes-trump-insists-ny-needs-up-to-40000-ventilators-i-operate-on-facts.html
In the end, New York never had more than 4,000 coronavirus patients on ventilators – making Cuomo’s facts and data and numbers and projections off by about tenfold.
By mid-April, it was obvious to me – and anyone who was paying attention – that the coronavirus epidemic simply was not going to be anywhere near as bad as the early predictions, and that the lockdowns were an extreme overreaction.
Third, and most importantly, the topline death figure does not account for the fact that the deaths will be heavily concentrated among the very old and sick. More than half would likely have died within weeks or months in any case, as Neil Ferguson said in his British testimony.
the reason we initially agreed to lockdowns was to “flatten the curve,” which is a polite way of saying “to prevent coronavirus patients from collapsing our health-care system.”
Early Chinese data suggested the virus might have an “infection fatality rate” as high as 1.4 – 2 percent.
If 10,000 people die out of 100,000 infections, that means the virus kills 10 percent of all the people it infects – making it very, very dangerous. But if 10,000 people die from 10 million infections, the death rate is actually 0.1 percent – similar to the flu.
Many people who are infected with SARS-COV-2 don’t even know it.
The most important estimate came on May 20, when the Centers for Disease Control reported its best estimate was that the virus would kill 0.26 percent of people it infected, or about 1 in 400 people. (The virus would kill 0.4 percent of those who developed symptoms. But about one out of three people would have no symptoms at all, the CDC said.) (
The best estimates are that the virus probably can infect somewhere between 50 to 70 percent of people. For example, on one French aircraft carrier, 60 percent of sailors were infected (none died and only two out of 1,074 infected sailors required intensive care). https://www.navalnews.com/naval-news/2020/05/covid-19-aboard-french-aircraft-carrier-98-of-the-crew-now-cured/
completely unchecked coronavirus might kill between 0.075 and 0.28 percent of the United States population – between 1 in 360 and 1 in 1,300 Americans. This is higher than the seasonal flu in most years. Influenza is usually said to have a fatality rate among symptomatic cases of 1 in 1,000 and an overall fatality rate of around 1 in 2,000. However, influenza mutates rapidly, and its dangerousness varies year by year. The coronavirus appears far less dangerous than the Spanish flu a century ago, which was commonly said to kill 1 in 50 of the people it infected.
