Stanford scientist, Nobel laureate says lockdowns were a waste, may have killed more than were saved

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Stanford University Prof. Michael Levitt is claiming that governors who locked down their states and economies in order to ‘flatten the coronavirus curve’ likely cost more lives than they saved.

The Nobel laureate scientist who correctly forecast the initial scope of the COVID-19 pandemic also observed that forcing people to self-quarantine was mostly driven by “panic” instead of the best science available, the UK’s Daily Mail reports.

In addition, Levitt said that an initial model used by the government to shutter the country and choke off the economy, which was produced by British scientist Neil Ferguson, overestimated the virus death toll by as much as 10 to 12 times.

Levitt’s observations mirror those contained in a report released this week by JP Morgan which found that lockdowns did nothing to change the course of the coronavirus outbreak but rather “destroyed millions of livelihoods” instead.

According to Marko Kolanovic, an analyst for JP Morgan and author of the report, noted that governments around the world were frightened by “flawed scientific papers” which led them to impose widespread lockdowns that were “inefficient or late,” thus having little real effect in mitigating the spread of COVID-19.

Kolanovic said that declining infection rates after lockdowns have been lifted also points to the suggestion that coronavirus “likely has its own dynamics” that are “unrelated to often inconsistent lockdown measures.”

Countries like Denmark and Germany that have reopened schools and retail outlets have seen their infection rates decline, the Daily Mail reports. In the U.S., meanwhile, states that have reopened have also seen falling infection rates or, at a minimum, no real spikes.

“I think lockdown saved no lives. I think it may have cost lives. It will have saved a few road accident lives, things like that, but social damage – domestic abuse, divorces, alcoholism – has been extreme,” Levitt told the Daily Mail. “And then you have those who were not treated for other conditions.”

The scientist, who won the Nobel Prize for chemistry in 2013 for his “development of multiscale models for complex chemical systems,” has been saying for months he believes most of the other ‘experts’ who predicted mass infection and death were wrong.

Wearing masks could help mitigate illness, as well as continued social distancing, Levitt said, but otherwise people should be allowed to get on with their lives.

Initially, Ferguson’s model predicted 2.2 million deaths in the United States and 500,000 in Britain, figures which spooked governments in both countries.

“For an uncontrolled epidemic, we predict critical care bed capacity would be exceeded as early as the second week in April, with an eventual peak in ICU or critical care bed demand that is over 30 times greater than the maximum supply in both countries,” his Imperial College report claimed.

But within weeks of releasing his initial figures, Ferguson began walking them back; in late March he declared that the UK would have more than enough ICU and hospital bed space to deal with COVID-19 patients and that fewer than 20,000 people in the country would die from the disease (as of this writing, the figure is around 37,000, still far below Ferguson’s initial estimate).

Ferguson’s forecast has been alternately described by four experienced modelers as having code that was “deeply riddled” with bugs, “a fairly arbitrary Heath Robinson machine,” replete with “huge blocks of code – bad practice,” and is “quite possibly the worst production code” ever seen.

But Ferguson wasn’t the only one whose coronavirus modeling was garbage. COVID Act Now, a project founded by a few Democratic activists in Silicon Valley, produced an online mapping tool that generated models allegedly predicting the number of coronavirus hospitalizations, but it, too, was widely inaccurate.

As for Levitt, he added, “For reasons that were not clear to me, I think the leaders panicked and the people panicked. There was a huge lack of discussion.”

Though not an immunologist, Levitt nevertheless assessed the outbreak in China at the beginning of the pandemic, which led him to produce alternative predictive analysis based on his calculations.

Levitt acknowledged that lockdowns can be effective to some degree, but they are “medieval.” Also, he believes that some epidemiologists exaggerate claims to gain attention and be followed.

The Nobel laureate isn’t the only expert who believes the lockdowns were an overreaction. In mid-April, Stanford University professor of medicine Dr. Jay Bhattacharya said he disagreed with the death rate put forth by the World Health Organization, saying he believed, in the end, they’d be much lower (and it is).

“I think, based on the evidence I’ve seen so far, it’s likely orders of magnitude lower than the initial estimates,” he told Fox News’ Tucker Carlson.

And, in a late April column, Chief of Neuroradiology at Stanford University Medical Center Dr. Scott Atlas, now a senior fellow at the Hoover Institute, argued that the data proved the lockdowns were ineffective and that it was past time to reopen the country.


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