Unreported Truths about COVID-19 and Lockdowns: Part 1: Introduction and Death Counts and Estimates

by Alex Berenson

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.

A century ago, the Spanish flu killed children and young adults along with the elderly.

Why wasn’t the media telling the truth about the huge difference in risk by age?

And was the coronavirus really as deadly as I and everyone else believed?

For the second time in just over a week, I found myself stunned. Instead of 500,000 British deaths, 20,000? Without months or years of lockdowns? In the absence of a vaccine or effective treatment? Had Ferguson just cut the Imperial College estimate by 96 percent (or 92 percent, if one used the 250,000-person death estimate)? What facts could have changed so much in just a few days? What did the change say about the accuracy of either the old or the new estimate? And, again, why hadn’t the New York Times and other American media outlets – after giving the earlier estimate so much attention – given equal prominence to the new number?

Investigative reporters have an old saw:

If your mother says she loves you, ...

had been a New York Times reporter from 1999 until 2010, but I didn’t work for the Times anymore. Even if I had been working for them, I doubted they would be interested in my efforts to challenge the narrative. They were among the leaders of what I had begun to think of as “Team Apocalypse,” the media outlets that – for reasons I could not fully understand – seemed committed to painting as bleak a picture of the coronavirus as possible.

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 audience, with tens of millions of followers. Musk and others retweeted my primary tweet challenging Ferguson, and it was viewed almost 5 million times.

Nonetheless, this view was less than popular, to say the least. Through late March and early April scorn and hate poured in, especially from my fellow media “blue-checks.” People wished for me to die of coronavirus, which didn’t really bother me, except when they said they hoped my family would too. The fear coming out of New York City, where so many members of the media lived, was palpable.

But as the days passed, the fact that the 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. In turn, the importance of that failure became increasingly obvious to me and a handful of other skeptics. What had happened in New York City in March was not generalizable to the rest of the United States. 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)

Even in New York, the health-care system was never close to being overrun. Field hospitals built at a cost of tens of millions of dollars were dismantled; some had never seen a single patient. Navy hospital ships departed the harbor, searching in vain for new coronavirus hotspots. 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...

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.

had the lockdowns even helped control the spread of the coronavirus at all?

But through April and May, major media outlets resolutely failed to ask that question. Instead, they focused nearly all their attention on COVID death counts, which rose slowly but steadily, eventually surpassing the total of 60,000 deaths initially estimated for the 2017-18 flu season.

German research institute reported in mid-April that lockdowns had been broadly useless.

How lethal is SARS-COV-2? Is it more dangerous than the flu? Who is most at risk? How are SARS-COV-2 deaths coded? What questions does that coding policy raise? What are the main ways in which the coronavirus has spread? How long has it been circulating? How many people have already been infected? Why did the key predictive models that policymakers used when they agreed to lockdowns prove so inaccurate? Do lockdowns slow the spread? What is the evidence for and against lockdowns, viewed on a public health basis, without regard to their economic, educational, and societal harms? What about those other harms? How severe are they already, and how severe might they become? What about the mental health risks of lockdowns? Is requiring people to wear masks in public likely to slow the spread?

First, it assumes that we take NO efforts to protect the elderly, especially those in nursing homes, that we develop no medicines for coronavirus, and that physicians become no better at treating it. All three of those points are clearly wrong. States are moving to protect long-term care facilities (some, like Florida, did so early on). The anti-viral medicine remdesivir has shown modest efficacy against COVID. And physicians have moved away from using ventilators aggressively, realizing that doing so can actually kill many coronavirus patients.

Second, it assumes that we will see a second wave of deaths: that the coronavirus, like the flu, will inevitably return this fall and winter. That view is the consensus among epidemiologists and scientists, and I won’t challenge it (even though many epidemiologists have been badly wrong about COVID for the last three months). One counter-argument comes from Oxford University’s Center for Evidence Based Medicine, which argued that “making absolute statements of certainty about ‘second waves’ is unwise, given the current substantial uncertainties and novelty of the evidence.” (https://www.cebm.net/covid-19/covid-19-epidemic-waves/)