The tightening grip of restrictions on American communal life, the intentional tanking of the U.S. economy, the coming $2 trillion bailout in mostly borrowed money to try to soften the nearly certain recession, all follow the premise that the coronavirus is a health threat the likes of which this nation has not seen in a century.

Most of the doomsday projections being cited to support the partial lockdown of Mississippi and the rest of the country are indeed startling: One half to two-thirds of the nation infected; as many as 1 out of 16 Americans requiring hospitalization; 200,000 to 1.7 million deaths.

But what if those numbers, which originated with the U.S. Centers for Disease Control and Prevention, are wildly wrong? What if the toll, as President Trump said before he was convinced otherwise and is now steering back toward, is about like a bad case of the seasonal flu? Would all of this trauma inflicted on the nation’s pocketbook and psyche be worth it?

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Those are the types of questions being raised by John P.A. Ioannidis, a Stanford University professor of medicine, epidemiology, biomedical data science and statistics. One of Ioannidis’ specialties is doing research on research. He regularly finds that it does not meet good scientific standards of evidence.

Ioannidis does not say he can calculate with any certainty what the infection and death rates will be in the United States from COVID-19, but he says no one else can either. That’s because there is no reliable data available on how prevalent the virus actually is, and how many it kills, in a sample of the general population.

For example, the World Health Organization estimates a mortality rate of 3.4%, although the documented figure so far is 4.4%. In the United States, the mortality rate has been about a fourth of that, 1.2%.

All of these numbers are inflated, though, because the vast majority of those being tested for the virus are disproportionately those with severe symptoms and bad outcomes. Consider Mississippi’s testing standards, which are similar to those throughout the country. Because test kits are having to be rationed, only those with fever and a severe cough or trouble breathing are being tested. That means none of those who are infected but have mild to no symptoms are being counted.

One situation where an entire, closed population was tested was the Diamond Princess cruise ship, the vessel that was quarantined for nearly a month off the coast of Japan. Of the 712 crew members and passengers infected, eight have died, roughly 1.1%. Because the travelers skewed older and because the data pool was small, Ioannidis said the fatality rate to project from that sample on the general U.S. population could be as high as 1 percent or as low as 0.05%. In other words, the range could be anywhere from 1 in 100 infected Americans dying to 1 in 2,000.

Without good data, there is no scientific way to project the true death rate. But if it winds up being similar to the flu, what the world and U.S. have done to slow the transmission of the coronavirus — that is, “flatten the curve” — has been irrational and possibly counterproductive. Instead of overwhelming the health-care system quickly and getting it over with, hospitals could be overwhelmed for not just months, but maybe years.

Ioannidis compares the potential fiasco to an elephant being attacked by a house cat. “Frustrated and trying to avoid the cat, the elephant accidentally jumps off a cliff and dies,” he writes.

Only problem with his analogy is that it would be no accident. It would have been an intentional, though unwitting, series of decisions that ultimately did more harm than good.

(1) comment


This is a very misleading article. First, it is not true that we are relying on CDC data from the United States to get a picture of the death rates. This is a pandemic & we have data from around the world. We can compare trend-lines from various countries based on levels of intervention. Our trend-line is much more like Italy than Japan or South Korea.we have much less testing and targeted intervention than Italy so far. If you want a model of virtually no intervention, look at Iran.

But let's take the data from the cruise ship as a model. If we assume that the disease "washes through" without intervention, it would affect about 70% of the population. At 1.1% that is about 3 million deaths. The idea that a 1.1% rate is just like the seasonal flu is absurd. It is 10 times greater.

But looking at death rates is looking at death rates is looking at the wrong statistic. The alarming statistics concern hospitalization rates. Those have held constant across the world at 15-20%. You cannot have a functioning hospital system or economy if 20% of your population needs to be hospitalized at the same time. That is why you need to "flatten the curve." If you slow the rate of growth, people will enter the hospitals at different times allowing them to continue operation.

We have plenty of data & statistically competent consumers can grasp the implications of the numbers we are provided daily. The math is clear. You just have to understand how to use it.

Dr. Larry W, Chappell, Professor of Political Science

Mississippi Valley State University

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