Who Is This Guy?

John P. Ioannidis has a remarkable resume. Professor here, director there, author, researcher, physician, and generally a capable human.

From Wikipedia, he is currently “Professor of Medicine, Health Research and Policy, and of Biomedical Data Science at Stanford University School of Medicine and a professor, by courtesy, of Statistics at Stanford University School of Humanities and Sciences. [13][14] He is director of the Stanford Prevention Research Center, and co-director, along with Steven N. Goodman, of the Meta-Research Innovation Center at Stanford (METRICS). [15][16]” 

You can see even more of his resume here.

The thing that intrigued me was his Google H score. It relates to how often a paper for an author is cited by others. His H number is 211. I know from previous reading that 40 is outstanding and 60 exceptional. So we have a capable person who others in his field respect.

The H-number is not very good for comparison to those in different fields. Some fields, like medicine, have many more scholarly participants than would poetry or geology. There are more people who might cite the paper. Fame and notoriety don’t matter a lot either. Jordan Peterson, by comparison, has an h-score of 55. Exceptional, Lee Smolin – a world-class theoretical physicist at the Perimeter Institute in Waterloo is at 67.

Do you think Dr. Ioannidis’ research and thoughts tend to be credible?

It might not matter for long.

Dr. Ioannidis is on the wrong side of the media and political narrative regarding COVID-19.

For example

  1. From Medscape, “John Ioannidis, professor of epidemiology at Stanford University and one of the most cited physician-scientists who practically invented “meta-research,” questioned the lockdown and wondered if we might cause more harm than good in trying to control coronavirus. What would normally pass for skepticism in the midst of the uncertainty of a novel virus became tinder in the social media outrage fire.
  2. From BMJ, “Professor John Ioannidis of Stanford University quotes an infection fatality rate (IFR) for Covid of 0.00-0.57% (0.05% for under 70s), far lower than originally feared and no different to severe flu [3]. This paper is published on WHO’s own Bulletin but ignored by UK mainstream media.” The reference is to his paper “Infection fatality rate of COVID-1937 inferred from seroprevalence data. Publication: Bulletin of the World Health Organization; Type: Research Article ID: BLT.20.265892 Page 1. 14 October 2020 https://www.who.int/bulletin/online_first/BLT.20.265892.pdf
  3. There is no significant effect arising from nonpharmaceutical Interventions. Lockdowns and the like. European Journal of Clinical Investigation.
  4. In a paper submitted in July but not yet peer-reviewed, Infection Mortality Rate, his research shows that the mortality rate is vastly lower than people have been telling us. It could be a fog of war problem, or it could be manipulative. You decide. The numbers he and an associate have found are these:
AGE INFECTION SURVIVAL RATE
0-19 99.997%
20-29 99.986%
30-39 99.969%
40-49 99.918%
50-59 99.730%
60-69 99.410%
70+ 97.6% (non institutionalized, not in a care home)
70+ 94.5% (all)

What we can expect

  1. No media coverage whatever
  2. If there is any comment at all, loud and complete denial of the study’s validity.
  3. Fat checker commentary all over it. Just as a point of interest, why would a 22-year-old fact-checker, newly graduated from some journalism school, be competent to evaluate this study?

What we should do and ask

  1. As part of our #Showyourwork campaign, ask for the fact checker’s resume.
  2. Think about what we are seeing and be critical
    1. Are meta-studies valid in general?
    2. Is this one in particular?
    3. There was a study published in late 2020 that has different numbers. Age-specific mortality and immunity patterns of SARS-CoV-2 It has assumptions and very early reported data. Up to 1 September 2020. It shows much higher numbers. It could be right too. Different circumstances.
    4. Does a Covid death mean a) died with Covid or b) died because of Covid?
  3. Would someone or some group gain an advantage by having the study belittled? Who?
  4. What policy changes should occur if it is right? Will policies change?
  5. Can the media, the government, and the government’s various agencies back away from their previously promoted fear program?

The takeaway

As always the science is not settled. Be open-minded about what you can learn.

Trust scientists who show their work. Trust no one who interprets it for you. Are you hearing science or biased interpretation?

Science guides, it does not command.

Use common sense. If you are at risk or think you might be, do something about it.

Support scientists who publish well-formed and opposing views.


I help people have more retirement income and larger, more liquid estates.

Call in Canada 705-927-4770, or email don@moneyfyi.com

 

 

 

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