John Ioannidis is a respected epidemiologist at Stanford. He specialises in something called “metascience”, which is essentially calling out shoddy medical research. He points out that we don’t yet have enough data to feel confident about how dangerous Coronavirus (COVID-19) is. Why does that matter? Well, governments across the globe are implementing policies with massive social and economic repercussions.
Writing for STAT, he says:
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%). 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 huge range markedly affects how severe the pandemic is and what should be done. A population-wide case fatality rate of 0.05% is lower than seasonal influenza. If that is the true rate, locking down the world with potentially tremendous social and financial consequences may be totally irrational. It’s like an elephant being attacked by a house cat. Frustrated and trying to avoid the cat, the elephant accidentally jumps off a cliff and dies.John Ioannidis, STAT
Let’s take a look at the death rates for the worst hit European countries:
|Country||Total Cases||Total Deaths||Death Rate|
What could explain the incredible difference between Italy’s near 8 percent case death rate and Germany’s 0.23%? It’s likely due to the limited testing to date, some deaths and the vast majority of cases are being missed.
Media reporting of case fatality rates, like the official 3.4% from World Health Organisation, are utterly meaningless. Patients tested for COVID-19 are disproportionately those with severe symptoms and bad outcomes.
Some point to the high death rate in elderly people. However, some mild coronaviruses that cause the common cold have been know for decades to have case fatality rates as high as 8%. As John Ioannidis points out:
Such “mild” coronaviruses infect tens of millions of people every year, and account for 3% to 11% of those hospitalised in the U.S. with lower respiratory infections each winter.
If we assume that case fatality rate among individuals infected by SARS-CoV-2 is 0.3% in the general population — a mid-range guess from my Diamond Princess analysis — and that 1% of the U.S. population gets infected (about 3.3 million people), this would translate to about 10,000 deaths. This sounds like a huge number, but it is buried within the noise of the estimate of deaths from “influenza-like illness.” If we had not known about a new virus out there, and had not checked individuals with PCR tests, the number of total deaths due to “influenza-like illness” would not seem unusual this year. At most, we might have casually noted that flu this season seems to be a bit worse than average. The media coverage would have been less than for an NBA game between the two most indifferent teams.
Given the current lack of clear data, it is unreasonable for governments to be causing such panic.
If we decide to jump off the cliff, we need some data to inform us about the rationale of such an action and the chances of landing somewhere safe.