A new study suggests that as many as 8.7 million Americans came down with coronavirus in March, but more than 80% of them were never diagnosed.
A team of researchers looked at the number of people who went to doctors or clinics with influenza-like illnesses that were never diagnosed as coronavirus, influenza or any of the other viruses that usually circulate in winter.
There was a giant spike in these cases in March, the researchers reported in the journal Science Translational Medicine.
"The findings support a scenario where more than 8.7 million new SARS-CoV-2 infections appeared in the U.S. during March and estimate that more than 80% of these cases remained unidentified as the outbreak rapidly spread," Justin Silverman of Penn State University, Alex Washburne of Montana State University and colleagues at Cornell University and elsewhere, wrote.
Only 100,000 cases were officially reported during that time period, and the US still reports only 2.3 million cases as of Monday. But there was a shortage of coronavirus testing kits at the time.
With coronavirus infections rising again across the nation, the question of just how lethal the virus is has become more crucial than ever.
Early in the epidemic, public-health experts feared the virus might kill up to 2 percent of those infected, potentially causing millions of deaths in the United States and tens of millions worldwide. Those terrifying estimates prompted the lockdowns that have done incalculable harm to the economy, shattered small businesses and left children traumatized and untold numbers suffering from brutal isolation.
But we now know much more about the virus. And we know its lethality is lower than we originally feared — and highly concentrated in the very elderly and people with serious health problems.
In fact, the Centers for Disease Control and Prevention estimated in May that the coronavirus kills about 0.26 percent of the people it infects, about 1 in 400 people. New estimates from Sweden suggest that only 1 in 10,000 people under 50 will die from the virus, compared to 1 in 14 of people over 80 and 1 in 6 of those over 90.
Estimates for the coronavirus’ lethality have fallen so sharply because calculating the so-called infection fatality rate requires scientists and physicians to know both the total number of deaths and the total number of people infected.
Tracking deaths is relatively easy. But tracking infections can be tough. Many people who are infected with respiratory viruses like influenza or the novel coronavirus have only mild symptoms or none. They may never be tested or even know they are infected.
Thus, in the early stages of an epidemic, scientists must guess at the number of mild and hidden infections.
Probably the best way to discover the real number is through antibody tests, which measure how many people have already been infected and recovered — even if they never had symptoms.
Unlike some other countries, the United States still hasn’t completed a national random antibody study — yet another way in which our public-health establishment has failed to get the data we need to make good decisions about lockdowns. But some counties, states and countries have.O
Those studies consistently show that far more people have been infected with and recovered from the coronavirus than suggested by data from tests that only measure current infections. Tests of municipal sewage systems — measuring the virus’ genetic signature in wastewater — have had similar findings.
Nearly all the studies find between 10 and 100 times the number of total infections as reported infections, with the average somewhere around 20 to 25 times.
In other words, while the CDC reports 2.34 million Americans have been infected with the coronavirus, the actual number of infected and recovered people may be closer to 50 million. (CDC Director Robert Redfield told journalists Thursday that the number of cases may be 10 times higher than the earlier 2.34 million.)
Thus, the death rate, which would be 5.2 percent based on that 2.34 million figure, is actually more like one-20th as high — or 0.26 percent.
To be sure, these estimates still have some uncertainty. The actual figure could be as low as 0.1 percent or as high as 0.4 to 0.5 percent, though treatment advances should mean it will trend lower over time. Even at 0.26 percent, the rate is still significantly higher than influenza most years, more comparable to a bad flu strain like the 1968 Hong Kong flu.
But it is far lower than we initially thought — a fact that should be cause for celebration.
Instead, some media outlets insist on using the out-of-date estimates that are much higher. For example, an ESPN article this week said public discussions about reopening the National Football League were “ignoring a mortality rate that has been estimated at 1.4 percent.” That figure is more than five times the CDC’s best estimate. Even more jarring, it is more than 100 times the actual risk to people in their 20s and 30s — the age range for nearly all NFL players.
Using those overstated estimates is a recipe for panic, bad public policy — and continued lockdowns that may delay to return to normality.
Let’s hope that isn’t the reason people in the media are using them.
It is tempting to present more facts to those who don’t see the world the way you do. Yet, we have all experienced the truth of John Kenneth Galbraith’s famous observation: “Faced with a choice between changing one’s mind and proving there is no need to do so, almost everyone gets busy with the proof.”
Due to confirmation bias, “we embrace information that confirms [our] view while ignoring, or rejecting, information that casts doubt on it.” Those who believe that experts and politicians should lead the way will not question their belief no matter what alternative COVID-19 data is presented.
In his article “Confirmation Bias: A Ubiquitous Phenomenon in Many Guises,” psychology professor Raymond Nickerson observes that a “significant fraction of the disputes, altercations, and misunderstandings that occur among individuals, groups, and nations,” is due to confirmation bias.
In short, to get through to your friend, you must overcome the human tendency to filter and ignore evidence.
The school closures, stay home orders, shuttering of businesses, banning of elective surgeries, closure of physical entertainment events, blocked flights, and sudden imposition of a central plan – it all happened suddenly from mid-March in the course of only a few days, and to enormous shock on the part of people who had previously taken their freedom and rights for granted.
Despite enormous pressure from Washington, eight states did not lock down or used a very light touch: South Dakota, North Dakota, South Carolina, Wyoming, Utah, Arkansas, Iowa, and Nebraska.
After 100 days, we are in a position for some preliminary analysis of the performance of locked down states versus those that did not lock down. AIER has already published the evidence that lockdown states had higher rates of unemployment.
The Sentinel, a nonprofit news source of the Kansas Policy Institute, confirms our research by reporting the following data: locked down states have overall a 13.2% unemployment rate, while open states have a 7.8% unemployment rate.
As new coronavirus cases surge across a large swath of the country, with real spikes occurring in certain states, what are we to make of what's happening? It's undoubtedly true that increased testing is leading to increasing raw numbers of people testing positive, which helps explain a significant portion of this effect.
But that's not the whole story, as infection rates are also up in places like Florida (though they're roughly stable nationally). Gov. Ron DeSantis has conceded this point, which was echoed by one of the state's GOP Senators, himself a former governor. That said, there are less worrisome statistics that mitigate the serious jumps in cases we're seeing. What's going on? Let's start here:
A dozen states have seen record highs in new coronavirus cases, blares the news media, accompanied by dire warnings of a “second wave” of the disease because those awful Republican states reopened too soon. Once again, however, the mainstream press is needlessly scaring the public by hiding the relevant context.
One news outlet put it this way: “The U.S. reported more than 33,000 new coronavirus cases on Saturday – the highest total since May 1 – while the surge of infections in several states is outpacing growth in coronavirus testing.”
The same trend is happening nationally, which has seen the growth rate in the total number of cases steadily outstrip the growth in COVID-19 deaths for many weeks now.
So far this month, in fact, the number of new cases on June 21 was 16% higher than on June 1, but the daily number of deaths was 63% lower.
Still, won’t the current spike in cases lead to a subsequent spike in deaths?
That’s unlikely. As Michael Fumento has repeatedly pointed out in these pages and elsewhere, death rates are higher at the start of an outbreak for the simple reason that the disease claims the low-hanging fruit first. This, he says, is known as Farr’s Law.
In the case of COVID-19, this reality is glaringly apparent, as the disease strictly targets the old and infirm.
The latest CDC data show that those aged 65 and older account for 80% of all COVID-19 deaths in the U.S. But that age group makes up only 16% of the population. At the other end of the spectrum, those under age 35 comprise 45% of the population but account for a tiny 0.8% of COVID-19 deaths.
Not only has the disease already claimed many of the most vulnerable in this country, there are also millions who now have antibodies.
The combination means that even if there are lots of new cases going forward, the death toll is likely to be far less severe than it has been.
Just don’t expect anyone in the mainstream press to explain this, because they’re too busy looking for ways to blame a scary “second wave” on President Donald Trump.
