An NPR report suggests the global response to COVID-19 may have been based on a flawed assumption about the volatility of COVID19. We already know that the model used to initially predict infection and death rates was completely flawed, and now discredited, along with the modeler Neil Ferguson of London’s Imperial College.
Back in 2005, Ferguson claimed up to 200 million might die from the Avian flu, but in reality, only about 100 did. In March 2020, Ferguson was queried by The New York Times with the question: “what the best-case scenario was for the US during the COVID pandemic?”
“About 1.1 million deaths,” he said. So far, as of this writing, 154,471 deaths have been recorded according to the CDC.
Ferguson’s model numbers overreached reality by about a factor of ten.
From the report: (bold mine)
Mounting evidence suggests the coronavirus is more common and less deadly than it first appeared.
The evidence comes from tests that detect antibodies to the coronavirus in a person’s blood rather than the virus itself.
The tests are finding large numbers of people in the US who were infected but never became seriously ill. And when these mild infections are included in coronavirus statistics, the virus appears less dangerous.
“The current best estimates for the infection fatality risk are between 0.5% and 1%,” says Caitlin Rivers, an epidemiologist at the Johns Hopkins Center for Health Security.
That’s in contrast with death rates of 5% or more based on calculations that included only people who got sick enough to be diagnosed with tests that detect the presence of virus in a person’s body.
Basically, the “nanny state” politicians decided to shut down the global economy to protect people from a contagious virus that has resulted in no symptoms or mild symptoms for up to 90 percent of the people who contracted it.
This will eventually go down as one of the biggest, if not the biggest, scientific and political blunders of the 21st century. The so-called “climate emergency” is a close second.