“This would translate to about 10,000 deaths”
Two years ago, Dr. John Ioannidis wrote an essay in STAT titled “A Fiasco in The Making? As The Coronavirus Pandemic Takes Hold, We Are Making Decisions Without Reliable Data.” It contained the following paragraph:
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.
This all seems pretty straightforward. Dr. Ioannidis calculated a case fatality rate with the limited information that was available at that time, and assumed 1% of the US would get infected. Combining these metrics, he calculated about 10,000 people would die. He thought we if we didn’t test for it, we might not notice the virus at all. He felt that “at most we might have casually noted” its impact, and that overall it would be as significant as a dull basketball game.
This clearly reflected his thinking at the time. In a paper, published two days later, March 19th, 2020, he wrote about “exaggerated pandemic estimates,” “exaggerated case fatality rate,” and “exaggerated exponential community spread.” He said a claim that 20%-60% of adults would be infected, was “substantially exaggerated.” He said, “China data are more compatible with close contact rather than wide community spread being the main mode of transmission,” He said that, “Even if COVID-19 is not a 1918-recap in infection-related deaths, some coronavirus may match the 1918 pandemic in future seasons. Thus, we should learn and be better prepared.” He felt this coronavirus was a false alarm. He wrote that,
If only part of resources mobilized to implement extreme measures for COVID-19 had been invested towards enhancing influenza vaccination uptake, tens of thousands of influenza deaths might have been averted.
But there were some problems. Dr. Hilda Bastian, noticed flaws in his estimation that 0.3% of people who contract COVID will die, writing “the 0.3% CFR seems likely to be too low, too.” Two years later, 0.3% Americans have died of COVID, proving Dr. Bastian’s criticism was correct.
Dr. Bastian also said that “The 1% rate of people infected, however, is likely to be very wide off the mark. It’s far lower than the infection rate on the Diamond Princess (which was more like 20%).” Others noticed this as well. One commentator on STAT news wrote,
In the same article that you use the Diamond Princess cruise ship as a case study for fatality rates, you estimate that 1% of the U.S population might be infected. The Diamond Princess cruise ship saw nearly 25% of the ship’s passengers infected. Perhaps multiply your “lost in the noise” 10,000 influenza-like deaths by 20+.
Another prescient commentator wrote,
The contagion factor of this virus is far greater than influenza- so if you don’t take measures to slow the spread you get a higher death rate because you can’t treat all the sick at once.
The tip of the iceberg
Indeed, a few weeks later, Dr. Ioannidis would partially adopt this position and completely reverse his his assumption that 1% of the US would contract COVID. Based on a controversial antibody study, he estimated the virus was 50-85 times more common than he previously thought. He now felt the virus was “very common” and that the number of known COVID cases was merely the “tip of the iceberg“.
Paradoxically, this was a comforting thought. If large numbers of people had been infected without even knowing about it, it meant COVID’s impact would be much less severe than feared. As he said in an interview, it would mean the “probability of dying if you are infected diminishes by 50-85 fold.” Dr. Ioannidis felt that most people had no or mild symptoms and that this was a cause for “optimism” about reopening society. He called COVID a “common and mild infection” for most people. He said “the infection fatality rate for this new coronavirus was likely to be in the same ballpark as the seasonal influenza.” He said that “For someone who is less than 65 and has no underlying diseases, the risk (of death) is completely negligible…these deaths are extremely exceptional.” He would later say “For people younger than 45, the infection fatality rate is almost 0%.”
This was exactly what we all wanted to hear! If the virus was already widespread, it meant that we were closer to the middle, or even the end of the pandemic than to its start. Indeed, Dr. Ioannidis felt there was a good chance the pandemic was close to over, saying on April 17, 2020:
Acknowledging for the fact that the epidemic is still evolving, and we cannot be sure whether we will hit even higher peaks in the future, although this doesn’t seem to be the case, at least for the European countries, and it seems to be that even in the US, in most states we’re very close to the peak, if not past the peak, the risk is something that should be manageable as opposed to the panic and horror stories that are circulating about.
He expressed a similar sentiment in August 2020 in an article ironically titled “Forecasting for COVID-19 has Failed” saying,
However, very few hospitals were eventually stressed and only for a couple of weeks. Most hospitals maintained largely empty wards, expecting tsunamis that never came… Tragically, many health systems faced major adverse consequences, not by COVID-19 cases overload, but for very different reasons.
Whether he was assuming that only 1% of the population would get COVID-19 or that it was already widespread, Dr. Ioannidis’s message was clear: though COVID-19 can devastate older, ill people, for almost everyone else, it’s as dangerous as driving to work and back, to borrow his analogy. Its overall impact would be as seismic as a February contest between the Orlando Magic and Sacramento Kings.
COVID-19: Bigger than an NBA game
Unfortunately, COVID-19 turned out to be bigger than a basketball game. When asked about his “10,000 deaths” statement four months later, Dr. Ioannidis said the following:
I never said that I knew that the death toll was going to be “10,000 deaths in the US”. How could I, in a piece where the message was “we don’t know”! The 10,000 deaths in the US projection was meant to be in the most optimistic range of the spectrum and in the same piece I also described the most pessimistic end of the spectrum, 40 million deaths. The point I wanted to emphasize was the huge uncertainty.
Another gross distortion propagated in social media is that the op-ed had supposedly predicted that only 10,000 deaths will happen in the USA as a result of the pandemic. The key message of the op-ed was that we lack reliable data, that is, we do not know. The self-contradicting misinterpretation as “we don’t know, but actually we do know that 10,000 deaths will happen” is impossible. The op-ed discussed two extreme scenarios to highlight the tremendous uncertainty absent reliable data: an overtly optimistic scenario of only 10,000 deaths in the US and an overtly pessimistic scenario of 40,000,000 deaths.
How accurate is all this? I agree Dr. Ioannidis never said he “knew” the death toll was going to be 10,000. However, any fair reading of his article in STAT, as well as everything else he said at the time, shows that he felt the danger of COVID was greatly exaggerated.
For example, he wrote “This year’s coronavirus outbreak is clearly unprecedented in amount of attention received,” not in the threat it posed. He said that other coronaviruses receive scant attention and it is “only this year that every single case and every single death gets red alert broadcasting in the news.” In contrast, he felt measures to control the virus were much more likely to harm than help, saying they were 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.” He warned of “financial crisis, unrest, civil strife, war, and a meltdown of the social fabric” as a result of lockdowns. He lamented that children might avoid the virus saying, “school closures may also diminish the chances of developing herd immunity in an age group that is spared serious disease”. Over 1,000 children have died since, a number that would have been much higher had the virus been allowed to rip through schools..
The notion that the virus might shutter schools and businesses didn’t occur to him. The refrigerated trucks outside my hospital weren’t very good for business, I imagine. They were there because the morgue couldn’t store all the dead bodies.
Despite this, Dr. Ioannidis would have us believe his STAT article presented two equally plausible scenarios, one overtly optimistic and one overtly pessimistic, and that he merely said we need to collect more data to determine which of these is more likely. It’s possible that Dr. Ioannidis meant for his “10,000 deaths” statement to be “the most optimistic range of the spectrum”, but that’s not what he wrote. It seems Dr. Ioannidis feels it’s a “strawman” or a “gross distortion” to quote the paragraph that opened this article and believe he was sincere when he wrote it.
“The most pessimistic scenario, which I do not espouse”
It’s worthwhile to further examine his claim that “In the STAT article, I discussed two hypothetical extremes for illustrative purposes, one with just 10,000 deaths in the USA and another with 50 million deaths worldwide.” In his STAT article, he said,
In the most pessimistic scenario, which I do not espouse, if the new coronavirus infects 60% of the global population and 1% of the infected people die, that will translate into more than 40 million deaths globally, matching the 1918 influenza pandemic.
Elsewhere he wrote “Some fear an analogy to the 1918 influenza pandemic that killed 20-40 million people.”
So yes, Dr. Ioannidis did discuss pessimistic scenarios, but only to say that he did not believe them, though other people did. If I said “I don’t think aliens are real, though some people do” I would not use my statement that “aliens are real” to claim I accepted the possibility of aliens existence if they landed tomorrow. Yet, this is exactly what Dr. Ioannidis is doing. He discussed the overtly pessimistic scenario only as a foil for his own belief that the threat from COVID was greatly exaggerated.
While he expanded on the most “optimistic scenario”, saying it would matter as much as an “NBA game between the two most indifferent teams,” he never elaborated on the potential consequences of the pessimistic scenario. Why would he? He thought these pessimistic scenarios were “completely off, just an astronomical error,” as he told a Fox News interviewer in April 2020.
“There were additional contributing reasons.”
Importantly, Dr. Ioannidis has acknowledged error, and it’s worth examining this too. In his article in the International Journal of Forecasting Dr. Ioannidis revisited another prediction he made, this one during an interview on April 9th 2020 where he said, “If I were to make an informed estimate based on the limited testing data we have, I would say that COVID-19 will result in fewer than 40,000 deaths this season in the USA.” Dr. Ioannidis admitted this prediction was “so wrong” and he called himself a “fool” for having made it.
However, Dr. Ioannidis’s explanation as to why he was so wrong is telling. The problem, as he sees it, wasn’t that he underestimated COVID. Rather, he lists these “additional contributing reasons”:
When I made that tentative quote, I had not considered the impact of the new case definition of COVID-19 and of COVID-19 becoming a notifiable disease, despite being aware of the Italian experience where almost all counted “COVID-19 deaths” also had other concomitant causes of death/comorbidities. “COVID-19 death” now includes not only “deaths by COVID-19” and “deaths with COVID-19”, but even deaths “without COVID-19 documented”. Moreover, I had not taken seriously into account weekend reporting delays in death counts. Worse, COVID-19 had already started devastating nursing homes in the USA by then, but the nursing home data were mostly unavailable. I could not imagine that despite the Italian and Washington state experience, nursing homes were still unprotected. Had I known that nursing homes were even having COVID-19 patients massively transferred to them, I would have escalated my foolish quote several fold.
The notion that COVID deaths were significantly inflated is a dangerous falsehood, and in fact, deaths due to COVID are more likely to be undercounted. Later, Dr. Ioannidis would blame doctors for the high death toll, falsely claiming that “a lot of lives” were lost early in the pandemic due to premature intubations and because “financial incentives may promote coding for COVID-19.”
It’s certainly true that nursing homes were poorly managed early in the pandemic. Most notoriously, New York Governor Andrew Cuomo issued a disastrous order on March 25, 2020 that no “resident shall be denied re-admission or admission to the NH [nursing home] solely based on a confirmed or suspected diagnosis of COVID-19.” However, Dr. Ioannidis apparently expected that every nursing home and care facility would both recognize the danger posed by COVID and implement measures to hermetically seal off vulnerable residents in a few weeks’ time. Sadly, but predictably, many were unable to do that.
“Make a complete ass of yourself”
Very few predictions from the start of the pandemic aged well. Other smart people also underestimated COVID. Dr. Paul Offit, one of the world’s foremost authorities on vaccines and viruses, said in an interview on March 2nd 2020, “I can’t imagine, frankly, that it would cause even one-tenth of the damage that influenza causes every year in the United States.” Reflecting back on his erroneous prediction Dr. Offit joked, “If you’re going to be wrong, be wrong in front of millions of people. Make a complete ass of yourself.”
We need people who are willing to buck the scientific consensus and think outside-the-box. There is no shame in being wrong, only in refusing to admit error. Dr. Offit underestimated COVID and he admitted this. His initial flawed prediction is worth remembering only because it stands as a model of how scientists should behave when they are wrong in a public forum. He didn’t later claim his erroneous prediction was his most “optimistic” one. He didn’t blame nursing home directors. He didn’t claim COVID deaths were inflated. He didn’t claim doctors killed their patients and then filled out death certificates inappropriately.
Dr. Offit remains a widely-respected scientist. There’s a lesson there.