Lockdown
President Donald Trump did just that on Jan. 31, by restricting travel into the United States for those who had been in China in the prior 14 days. The CCP virus—also known as the novel coronavirus—first became public the month before in Wuhan, China.“If everyone makes this change or these critical changes and sacrifices now, we will rally together as one nation, and we will defeat the virus, and we’re going to have a big celebration all together,” Trump declared during his daily coronavirus media briefing.
Trump’s experts—most notably Dr. Anthony Fauci, long-time director of the U.S. National Institute of Allergy and Infectious Diseases, and Dr. Deborah Birx, the White House coronavirus response coordinator—declared the measures would “flatten the curve” of new CCP virus cases enough to prevent the health care system from being overwhelmed and thus buy time for effective treatments and a vaccine to be developed.
By March 30, virtually the entire nation was under lockdown for at least another month or until further notice. By the end of April, unemployment was the highest since the Great Depression in the 1930s. More than 33 million Americans are now unemployed.
To date, more than 83,000 Americans have died, most being 65 years or older, or suffering an underlying condition such as heart disease, chronic obstructive pulmonary disease, or diabetes.
Flawed Models
How did America get to this point? Two critical CCP virus response mistakes stand out: relying too heavily on flawed statistical models and failing to target resources primarily to protect the most vulnerable Americans.Trump and other officials in the White House and leaders of both parties in Congress have repeatedly warned that as many as 2.2 million people in the United States could die without urgent official action, a forecast generated by the Imperial model. That forecast, which made a national lockdown seem imperative, wouldn’t hold up.
“Generally speaking, with the data that is available to everybody, people like those who did the Imperial College one, the IHME, they’re all using the same sort of tools, the same sort of statistical models, and they’re all very sensitive to the assumptions you make,” Michel told The Epoch Times in a recent interview.
“So even if you have the best data, forecasting anything is inherently risky, and if you’re trying to forecast over more than a very short period of time, it’s just very dicey,” he said. Thus, statistical modelers must make assumptions about numerous factors that shape projections.
Michel noted the impact of testing. “If you have a lot of new testing going on, that’s going to give you more cases. So, to get a full picture, you really need to know how many new tests are out there and what percentage of those tests were positive. But we don’t have that data.”
An additional problem is the models’ lack of transparency, according to Michel, as the makers of the models don’t make available to other researchers their code.
“You don’t have to give everybody your data, but you can give everybody your code and let everybody see what you’re doing and see if they can replicate what you’re doing,” he said.
“That’s the key to any kind of scientific endeavor. That’s a basic scientific principle, so that’s a big problem. I have a huge problem with that.”
Targeting the Vulnerable
The second mistake flowed directly from the first, according to Karl Dierenbach, a Colorado attorney-engineer who has closely studied COVID-19 death rates.“When New York started publishing age-related/underlying condition data, that was a huge signal the virus is fatal to a very specific group of people,” Dierenbach told The Epoch Times.
“Having 327 million people behave in a way to save maybe a third of the population, it just seemed like there’s a better way, you should be concentrating on those people,” he said.
Dierenbach’s point—prioritize protecting the most vulnerable while allowing most normal activities to continue—is evident in a comparison of New York and Florida.
One in five (20.5 percent) Floridians are 65 or older, compared to one in six (16.4 percent) New Yorkers, making the former the state with the second-largest elderly population and the latter the fourth largest as a percentage of the total.
Dierenbach said he noticed early in the crisis how Florida Gov. Ron DeSantis “just immediately jumped on the old-age communities and how that was where they were concentrating all of their efforts. It just seemed such a logical approach, and I was amazed at how that message never filtered through to the mainstream media.”
Second Outbreak?
The problem now, as the lockdown recedes, is that the lethal virus may come roaring back because the flattened curve delayed but didn’t arrest it.“I think in the back of people’s heads is this idea that we can somehow eradicate the disease if we just stay locked down,” Bhattacharya said. “That is not possible. We have to come to terms with that.”