There’s a video going viral of two doctors from Bakersfield, CA — Dan Erickson and Artin Massihi — who argue the testing results they’re seeing at the urgent care businesses they own makes COVID-19 more like the flu and is evidence that isolating the healthy doesn’t make sense and social distancing restrictions can be safely eased, leading to the opening of the economy. It’s a powerful message in these times, but, unfortunately there is a “solid counter argument to be made from the other side” that’s not getting shared:

First up, here’s the video, which was shared by Elon Musk:

Now, the counterpoint from the article: The two are being called out on their use of the testing data:

Kern County Public Health Services Spokeswoman Michelle Corson and an epidemiologist contacted by The Californian said they didn’t agree with the doctors’ recommendation to end social distancing and immediately start reopening society.

“This is a many-headed hydra. It’s really unfortunate to boil this all down to it’s just flu,” said Andrew Noymer, associate professor of public health at UC Irvine. “There’s no flu season that looks anything like New York does right now.”


Noymer of UC Irvine disagreed with the doctors’ premise that COVID-19 is as widespread as Erickson and Massihi think, saying the idea that nearly 5 million Californians have had the virus is a gross overestimate. The people tested in California were not a random sample; they were mostly people who were symptomatic, Noymer said. Therefore, extrapolating the positive test rate across the entire population of the state is not an accurate way to arrive at how widespread the virus is.

And even if 12 percent of the state has had the virus, that still leaves 88 percent vulnerable to it, Noymer said.

“They’re advancing factual inaccuracies and playing off the esoteric nature of the mortality stats to make a case that the economy should be reopened,” Noymer said. “I agree it should be reopened, but it should be opened deliberately, bit by bit, and informed by science. Not informed by a misreading of the mortality.”

More from the University of Washington ‘s Carl Bergstrom where he explains how the sample they’re using as the base for all their calculations is not random at all, which is throwing off the entire estimate: