Born in USA and raised in Greece, John Ioannidis is a physician-scientist, writer and professor of epidemiology at Stanford University. He is one of the world’s most cited and respected scientist in public health. Ioannidis is a member of the USA National Academy of Medicine, of the European Academy of Sciences and Arts and an Einstein Fellow. In 2019, Ioannidis was awarded the NIH’s Robert S. Gordon, Jr. Lecture in Epidemiology.
He practically invented “Meta Research”, which is research on research. This new field has its roots in traditional meta-analysis and systematic reviews, which aim to examine and combine all research on a scientific question. His work has aimed to identify solutions to problems in research, and on how to perform research more optimally.
John Ioannidis has a legendary track record in calling out the bad practices that lead to a truth deficit in bio-medicine. His 2005 paper “Why Most Published Research Findings Are False” is the most downloaded paper in the Public Library of Science.
He wrote numerous articles, papers, bulletins, reviews and studies and he is now one of the top cited scientist in the world averaging >6,000 new citations per month, and he is co-director of Meta-Research Innovation Center at Stanford (METRICS):
Almost literally overnight Ioannidis has himself become a case study in how to screw up a medical study. And not just any study: This study concluded that Covid-19 isn’t all that dangerous; that the current lockdowns to prevent its spread are a bigger threat to public health than the actual disease.
Since then, Mr Ioannidis has been a leading opponent of prolonged lockdowns during the COVID-19 pandemic. He said that as the coronavirus pandemic took hold, we were making decisions without reliable data. He called the global response to the COVID-19 pandemic a “once-in-a-century evidence fiasco” and wrote that lockdowns were likely an overreaction to unreliable data.
“There is a worrying lack of reliable data. The lockdowns in place in many parts of the world may not be justified. COVID-19 infections could be more widespread, and less lethal, than many experts feared.”
He even wrote to President Trump of his concerns about the lack of evidence regarding the efficacy of lockdowns, and questioned the lockdown and wondered if we might cause more harm than good in trying to control coronavirus.
He cited certain research teams (Johns Hopkins, Imperial College London, etc.) to denounce their conclusions about Covid Infection fatality rate, which he described as “astronomically false” and “constantly revised downwards to correspond to reality”. He noted problems in the way subjects were recruited, potential defects in the antibody test, and apparent mistakes in the statistical analysis.
He explained that infection fatality rate is not a constant. It’s affected both by how you count the numerator and how you count the denominator, and who are the people in the numerator and who are the people in the denominator. So, the case mix is very different in different locations. And the way that the serious cases were managed, or could be managed, is very different in different locations.”
“So, depending on the setting and the population, the infection fatality rate may be from far less than influenza to far more — from the mild infection all the way to ‘this is disaster’.”
One of his study shows a drastically reduced infection fatality rate and concluded that reported case fatality rates, like the official 3.4% rate from the World Health Organization, were wrong. In fact, since the study came out, more researchers and physicians have been citing likely fatality rates of around 0.5 percent, which is closer to Ioannidis’ estimate than it is to the 1-percent-and-way-up numbers that were once bandied about. Recent antibody testing results in New York support the 0.5 figure.
“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.”
Maybe Ioannidis’ results look to be an outlier—but they may be an outlier in the right direction, suggesting a need to revise the infection fatality rate downwards,.
He explains that a 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.
In the absence of data, prepare-for-the-worst reasoning leads to extreme measures of social distancing and lockdowns. Unfortunately, we do not know if these measures work. School closures, for example, may reduce transmission rates. But they may also backfire if children socialize anyhow, if school closure leads children to spend more time with susceptible elderly family members, if children at home disrupt their parents ability to work, and more. School closures may also diminish the chances of developing herd immunity in an age group that is spared serious disease.
But the real essence of Ioannidis’ claims is about the need to shift the conversation from how to avoid infection to reckoning how many people would ultimately die from the virus depending on how long and tightly the stay-at-home policies are maintained.
“I worry that many people in public health are very weak in research methodology. Many of them have very strong beliefs. And this means that often they go into war without really knowing what they’re doing.”
Ioannidis has been censored by YouTube, and has received death threats. At one point the severity of which left him fearing for the life of his elderly mother.
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Some of John Ioannidis’ Studies about Covid-19:
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