John P.A. Ioannidis, who is a professor at Stanford University’s School of Medicine, understands that experts, authorities, and scientists have not come to a consensus on the exact fatality rate of COVID-19. It remains unknown.
In addition to medicine, Ioannidis is also a professor with expertise in epidemiology and population health. In an article published in STAT and reviewed in The Wall Street Journal, Ioannidis argued that data collected from the Diamond Princess cruise ship could mean the World Health Organization’s predicted COVID-19 fatality rate is wrong.
Ioannidis writes, “The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco.”
“The data collected so far on how many people are infected and how the epidemic is evolving are utterly unreliable. Given the limited testing to date, some deaths and probably the vast majority of infections due to SARS-CoV-2 are being missed,” he added.
“We don’t know if we are failing to capture infections by a factor of three or 300. Three months after the outbreak emerged, most countries, including the U.S., lack the ability to test a large number of people and no countries have reliable data on the prevalence of the virus in a representative random sample of the general population.”
“This evidence fiasco creates tremendous uncertainty about the risk of dying from Covid-19. Reported case fatality rates, like the official 3.4% rate from the World Health Organization, cause horror — and are meaningless. Patients who have been tested for SARS-CoV-2 are disproportionately those with severe symptoms and bad outcomes. As most health systems have limited testing capacity, selection bias may even worsen in the near future.”
WHO’s director-general Tedros Adhanom Ghebreyesus said on March 3rd that coronavirus “causes more severe disease than seasonal influenza. “Globally, about 3.4 percent of reported COVID-19 cases have died. By comparison, seasonal flu generally kills far fewer than 1 percent of those infected,” he added.
This is where the figure 3.4 percent figure comes from.
“While many people globally have built up immunity to seasonal flu strains, COVID-19 is a new virus to which no one has immunity. That means more people are susceptible to infection, and some will suffer severe disease,” Ghebreyesus continued.
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However, Ioannidis pointed out that “[t]he one situation where an entire, closed population was tested was the Diamond Princess cruise ship and its quarantine passengers.
“The case fatality rate there was 1.0%, but this was a largely elderly population, in which the death rate from Covid-19 is much higher,” he added.
“Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%. But since this estimate is based on extremely thin data — there were just seven deaths among the 700 infected passengers and crew — the real death rate could stretch from five times lower (0.025%) to five times higher (0.625%),” Ioannidis continued.
“It is also possible that some of the passengers who were infected might die later, and that tourists may have different frequencies of chronic diseases — a risk factor for worse outcomes with SARS-CoV-2 infection — than the general population. Adding these extra sources of uncertainty, reasonable estimates for the case fatality ratio in the general U.S. population vary from 0.05% to 1%.”
That’s obviously a huge range — and it’s not close to 3.4 percent.
Now, granted, the Diamond Princess was a unique situation. It’s impossible to extrapolate that to an entire population.
However, given how unreliable much of the data is when it comes to COVID-19, the Diamond Princess data is not something we should ignore.