The Bearer of Good Coronavirus News
Stanford scientist John Ioannidis finds himself under attack for questioning the prevailing wisdom about lockdowns
Defenders of coronavirus lockdown mandates keep talking about science. “We are going to do the right thing, not judge by politics, not judge by protests, but by science,” California’s Gov. Gavin Newsom said this week. Michigan Gov. Gretchen Whitmer defended an order that, among other things, banned the sale of paint and vegetable seeds but not liquor or lottery tickets. “Each action has been informed by the best science and epidemiology counsel there is,” she wrote in an op-ed.
But scientists are almost never unanimous, and many appeals to “science” are transparently political or ideological. Consider the story of John Ioannidis, a professor at Stanford’s School of Medicine. His expertise is wide-ranging—he juggles appointments in statistics, biomedical data, prevention research and health research and policy. Google Scholar ranks him among the world’s 100 most-cited scientists. He has published more than 1,000 papers, many of them meta-analyses—reviews of other studies. Yet he’s now found himself pilloried because he dissents from the theories behind the lockdowns—because he’s looked at the data and found good news.
In a March article for Stat News, Dr. Ioannidis argued that Covid-19 is far less deadly than modelers were assuming. He considered the experience of the Diamond Princess cruise ship, which was quarantined Feb. 4 in Japan. Nine of 700 infected passengers and crew died. Based on the demographics of the ship’s population, Dr. Ioannidis estimated that the U.S. fatality rate could be as low as 0.025% to 0.625% and put the upper bound at 0.05% to 1%—comparable to that of seasonal flu.
“If that is the true rate,” he wrote, “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.”
...Early in his career, he (Dr. Ioannidis,) realized that “the common denominator for everything that I was doing was that I was very interested in the methods—not necessarily the results but how exactly you do that, how exactly you try to avoid bias, how you avoid error.” When he began examining studies, he discovered that few headline-grabbing findings could be replicated, and many were later contradicted by new evidence.
Scientific studies are often infected by biases. “Several years ago, along with one of my colleagues, we had mapped 235 biases across science. And maybe the biggest cluster is biases that are trying to generate significant, spectacular, fascinating, extraordinary results,” he says. “Early results tend to be inflated. Claims for significance tend to be exaggerated.”
An example is a 2012 meta-analysis on nutritional research, in which he randomly selected 50 common cooking ingredients, such as sugar, flour and milk. Eighty percent of them had been studied for links to cancer, and 72% of the studies linked an ingredient to a higher or lower risk. Yet three-quarters of the findings were weak or statistically insignificant.
Dr. Ioannidis calls the coronavirus pandemic “the perfect storm of that quest for very urgent, spectacular, exciting, apocalyptic results. And as you see, apparently our early estimates seem to have been tremendously exaggerated in many fronts.”
Chief among them was a study by modelers at Imperial College London, which predicted more than 2.2 million coronavirus deaths in the U.S. absent “any control measures or spontaneous changes in individual behaviour.” The study was published March 16—the same day the Trump administration released its “15 Days to Slow the Spread” initiative, which included strict social-distancing guidelines.
Dr. Ioannidis says the Imperial projection now appears to be a gross overestimate. “They used inputs that were completely off in some of their calculation,” he says. “If data are limited or flawed, their errors are being propagated through the model. . . . So if you have a small error, and you exponentiate that error, the magnitude of the final error in the prediction or whatever can be astronomical.”
“I love models,” he adds. “I do a lot of mathematical modeling myself. But I think we need to recognize that they’re very, very low in terms of how much weight we can place on them and how much we can trust them....They can give you a very first kind of mathematical justification to a gut feeling, but beyond that point, depending on models for evidence, I think it’s a very bad recipe.”
Modelers sometimes refuse to disclose their assumptions or data, so their errors go undetected. Los Angeles County predicted last week that 95.6% of its population would be infected by August if social distancing orders were relaxed. (Confirmed cases were 0.17% of the population as of Thursday.) But the basis for this projection is unclear. “At a minimum, we need openness and transparency in order to be able to say anything,” Dr. Ioannidis says.
Most important, “what we need is data. We need real data. We need data on how many people are infected so far, how many people are actively infected, what is really the death rate, how many beds do we have to spare, how has this changed.”
That will require more testing. Dr. Ioannidis and colleagues at Stanford last week published a study on the prevalence of coronavirus antibodies in Santa Clara County. Based on blood tests of 3,300 volunteers in the county—which includes San Jose, California’s third-largest city—during the first week of April, they estimated that between 2.49% and 4.16% of the county population had been infected. That’s 50 to 85 times the number of confirmed cases and implies a fatality rate between 0.12% and 0.2%, consistent with that of the Diamond Princess.
The study immediately came under attack. Some statisticians questioned its methods. Critics noted the study sample was not randomly selected, and white women under 64 were disproportionately represented. The Stanford team adjusted for the sampling bias by weighting the results by sex, race and ZIP Code, but the study acknowledges that “other biases, such as bias favoring individuals in good health capable of attending our testing sites, or bias favoring those with prior Covid-like illnesses seeking antibody confirmation are also possible. The overall effect of such biases is hard to ascertain.”
Dr. Ioannidis admits his study isn’t “bulletproof” and says he welcomes scrutiny. But he’s confident the findings will hold up, and he says antibody studies from around the world will yield more data. A study published this week by the University of Southern California and the Los Angeles County Department of Public Health estimated that the virus is 28 to 55 times as prevalent in that county as confirmed cases are. A New York study released Thursday estimated that 13.9% of the state and 21.2% of the city had been infected, more than 10 times the confirmed cases.
Yet most criticism of the Stanford study has been aimed at defending the lockdown mandates against the implication that they’re an overreaction. “There’s some sort of mob mentality here operating that they just insist that this has to be the end of the world, and it has to be that the sky is falling. It’s attacking studies with data based on speculation and science fiction,” he says. “But dismissing real data in favor of mathematical speculation is mind-boggling.”
In part he blames the media: “We have some evidence that bad news, negative news [stories], are more attractive than positive news—they lead to more clicks, they lead to people being more engaged. And of course we know that fake news travels faster than true news. So in the current environment, unfortunately, we have generated a very heavily panic-driven, horror-driven, death-reality-show type of situation.”
The news is filled with stories of healthy young people who die of coronavirus. But Dr. Ioannidis recently published a paper with his wife, Despina Contopoulos-Ioannidis, an infectious-disease specialist at Stanford, that showed this to be a classic man-bites-dog story. The couple found that people under 65 without underlying conditions accounted for only 0.7% of coronavirus deaths in Italy and 1.8% in New York City.
“Compared to almost any other cause of disease that I can think of, it’s really sparing young people. I’m not saying that the lives of 80-year-olds do not have value—they do,” he says. “But there’s far, far, far more . . . young people who commit suicide.” If the panic and attendant disruption continue, he says, “we will see many young people committing suicide . . . just because we are spreading horror stories with Covid-19. There’s far, far more young people who get cancer and will not be treated, because again, they will not go to the hospital to get treated because of Covid-19. There’s far, far more people whose mental health will collapse.”
He argues that public officials need to weigh these factors when making public-health decisions, and more hard data from antibody and other studies will help. “I think that we should just take everything that we know, put it on the table, and try to see, OK, what’s the next step, and see what happens when we take the next step. I think this sort of data-driven feedback will be the best. So you start opening, you start opening your schools. You can see what happens,” he says. “We need to be open minded, we need to just be calm, allow for some error, it’s unavoidable. We started knowing nothing. We know a lot now, but we still don’t know everything.”
He cautions against drawing broad conclusions about the efficacy of lockdowns based on national infection and fatality rates. “It’s not that we have randomized 10 countries to go into lockdown and another 10 countries to remain relatively open and see what happens, and do that randomly. Different prime ministers, different presidents, different task forces make decisions, they implement them in different sequences, at different times, in different phases of the epidemic. And then people start looking at this data and they say, ‘Oh look at that, this place did very well. Why? Oh, because of this measure.’ This is completely, completely opinion-based.”
People are making “big statements about ‘lockdowns save the world.’ I think that they’re immature. They’re tremendously immature. They may have worked in some cases, they may have had no effect in others, and they may have been damaging still in others.”
Most disagreements among scientists, he notes, reflect differences in perspective, not facts. Some find the Stanford study worrisome because it suggests the virus is more easily transmitted, while others are hopeful because it suggests the virus is far less lethal. “It’s basically an issue of whether you’re an optimist or a pessimist. Even scientists can be optimists and pessimists. Probably usually I’m a pessimist, but in this case, I’m probably an optimist.”
Ms. Finley is a member of the Journal’s editorial board.
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COMMENTS FROM READERS
Counter-intuitively, locking down America could make a pathogen worse. In the 1918 breakout of the a Spanish flu, many large U.S. cities legislated strict lock-down regulations. In 1919 when the pathogen re-surged into communities, it came back even more lethal than when the pathogen first caused chaotic concern. People died within a day of becoming ill. Did the isolation strategy actually cause the pathogen to become stronger? — Like an antibiotic killing all of a bacterial infection except that which has mutated a resistance to the antibiotic, resulting in antibiotic resistant strains re-populating the host. Did the 1918-1919 lock-downs, which separated both the healthy from the ill, cause the pathogen to actually strengthen? Could we, by dramatically changing the environment, actually be creating an environment which strengthens what we fear? - Dennis O'Neil
In many politicians' minds the worst thing that could happen is to relax all the restrictions and...nothing happen. No massive death count or overwhelmed hospitals. When all this is over and people are bankrupt or businesses failed remember, it wasn’t the virus that shut down the economy and forced people to stay at home, It was the politicians. Rodney Hall
The lockdowns have done a great job at only one thing. Delaying heard immunity for at least a year. That’s the main reason the virus may return. The virus won’t be defeated until the non-vulnerable population is widely exposed. The vulnerable can stay in shelter, but they may have to do so for the rest of their lives, or until there’s a vaccine. In some immuno-compromised people, a vaccine may not work. That’s the tough truth of the matter. Joseph Breton
..we have taken steps based on the advice of “experts” who don’t know very much about this virus at all, steps that have no evidence of efficacy, such as “social distancing,” wearing masks too ineffective to filter out the 0.3 micron size of the virus, and telling people to stay home. We can’t all stay home until no one dies. Protect the 80+ year olds, that’s fine. But even for those folks, we have no evidence that socially isolating them will actually protect them and cause no other harm. The pandemic will stop when enough people get it and develop immunity to it; then the virus will not be able to spread. Eventually, there may be a vaccine or a medication to combat this, but we don’t know if that will ever happen, let alone in the near future. Meanwhile, normal life needs to resume, the sooner the better. Jay Sigel
Please, someone cite something to refute the following: “For virus and disease, never before in the history of humankind that we know of, have we made the decision to quarantine the healthy.” Yes, during a time of war, with bombs reigning down, those that are healthy and not hurling the bombs will quarantine themselves (shelter) and heed the warnings and edicts from those in authority to shelter in place. But not for medical pandemics. While there is a history of quarantining large groups that may be infected or using infection as an excuse to quarantine groups like during the bubonic plague and yellow fever, we have never totally locked down free people to stop spreading a virus. It is ludicrous. This is a failed experiment and it must end now. - Ed Garwinter
The thought of hiding out in our houses until this thing passes is insane. Currently there is no cure, no vaccine and it may never happen. Herd immunity can be achieved and we should focus on that strategy now; rather than cowering in fear and hoping this bug will somehow go away and we will somehow avoid casualties. ...We don’t live in a risk free society. Nature will take its course whether we hide in our homes or get back to work. - William Fris
Policy should never be dictated by scientists. They are as biased and blind as members of the general public. Dr. Fauchi has never answered the question of how many unnecessary deaths are being caused by this quarantine. By the way, I am a retired Chemical Engineer. - Erick Matzke
Solve the problem? That’s hubris. We can’t even “solve” the common cold. Despite billions poured into R&D, there is still no vaccine for HIV. Flu shots kind of, sort of work, but not all the time, and have to be reinvented every year. We have to adapt. Wash your hands. Stop shaking hands. Wear a mask if you’re sick. But the lockdown is pure insanity. -Felix McAllister
With a vaccine at least a year away - some vaccines take decades - the quickest path through this is to build herd immunity, which requires social interaction. Here in Ohio, hospitals are very underwhelmed, and the problem - if you can call it that - is limited to the large cities. We can afford less social distancing to build herd immunity and get the economy going again and still not overwhelm hospitals. - Jason Bowman
Coronavirus is not killing 2,500 people daily. 2,500 people are dying daily, and some (not all) of whom also happen to have coronavirus, which is not necessarily their cause of death.
- Joseph Breton