A pair of public health experts from Stanford, Drs. Eran Bendavid and Jay Bhattacharya, warn Americans in a Wall Street Journal editorial that the current estimates about the coronavirus' fatality rate may be too high by "orders of magnitude."

According to Bendavid and Bhattacharya, both of whom are medical doctors, while they are supportive of social distancing guidelines and efforts to contain the disease, they fear that orders to shut down the entire economy may be based on shoddy research data.

Death toll projects may be 'orders of magnitude too high'

"If it's true that the novel coronavirus would kill millions without shelter-in-place orders and quarantines, then the extraordinary measures being carried out in cities and states around the country are surely justified," they wrote. "But," and what a big one it is, they add, "there's little evidence to confirm that premise — and projections of the death toll could plausibly be orders of magnitude too high."

The two submit that because the United States and other countries largely focus their testing on symptomatic patients, the number of people who are infected with COVID-19 is likely much larger than the number of confirmed cases being reported by public health agencies throughout the country, which means the virus' mortality rate is likely significantly lower.

"Fear of Covid-19 is based on its high estimated case fatality rate — 2% to 4% of people with confirmed Covid-19 have died, according to the World Health Organization and others," wrote Bendavid and Bhattacharya. "So if 100 million Americans ultimately get the disease, 2 million to 4 million could die. We believe that estimate is deeply flawed. The true fatality rate is the portion of those infected who die, not the deaths from identified positive cases."

How did they predict this?

The two professors argue that the best evidence of the coronavirus death rate being significantly lower than what is being reported may lie in the Italian town of Vò. On March 6, the town's 3,300 residents were tested. Of these, 90 tests came back positive, indicating a prevalence of 2.7% of the population having the virus.

If one were to apply this to the entire province where the town is located, which has a population of 955,000, it would mean there were actually 26,000 infections at the time, and not just the 198 that were officially confirmed. This would be 130 times greater than the number of reported cases. Since Italy's case fatality rate of 8% is estimated using the confirmed cases, Bendavid and Bhattacharya write, "the real fatality rate [of the virus] could in fact be closer to 0.06%."

A 'cause for optimism'?

The two Stanford Health Policy experts even said the virus' mortality rate might be on par with that of the seasonal flu:

Existing evidence suggests that the virus is highly transmissible and that the number of infections doubles roughly every three days. An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that's a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism.

A universal lockdown 'may not be worth the costs'

Bendavid and Bhattacharya say that if they are right about the lower lethality of the epidemic, public policy experts should focus their measures on protecting the elderly and expanding medical capacity.



"Hospital resources will need to be reallocated to care for the critically ill patients. Triage will need to improve. And policy makers will need to focus on reducing risks for older adults and people with underlying medical conditions."

The pair conclude that if their estimates are right, then the universal quarantine measures "may not be worth the costs it imposes on the economy, community, and individual mental and physical health."

"We should undertake immediate steps to evaluate the empirical basis of the current lockdowns," they added.