Olen nyt pannut merkille sinun tuoneen useammassa viestissä esiin tuota Ioannidiksen tutkimusta. Valitettavasti kyseessä on menetelmiltään todella kyseenalainen tutkimus, ja on surullista nähdä Ioannidiksen vajonneen nykyiseen rooliinsa. Suosittelen kaikkia tieteeseen perustuvan kannan muodostamiseen pyrkiviä huomioimaan esim. seuraavat jutut:
Ioannidis ollut mukana julkaisemassa viime vuonna 99 tutkimusta ja tänä vuonna niitä on kertynyt jo 37. Kukaan ei voi vakavissaan kuvitella hänen käyttäneen aikaansa näihin juurikaan. Professori Balloux nosti tämän esille ja hän muuten kannattaa talouden avaamista:
Ballouxn jutussa koottu hyvin kritiikkiä Ioannidiksen ryhmän tutkimusta kohtaan:
For his Covid-19 work, the respected Stanford physician and scientist John Ioannidis is being accused of the same bad science he has criticized.
undark.org
'“My quick take is that something really odd is going on with Ioannidis,” wrote Alexander Rubinsteyn, a geneticist and computational biologist at the University of North Carolina at Chapel Hill, in an email to Undark. Rubinsteyn suggested that Ioannidis may simply be “so attached to being the iconoclast that defies conventional wisdom that he’s unintentionally doing horrible science.”
He added: “Pretty much no one with statistical acumen believes these studies.”'
'In an essay published by STAT in mid-March, Ioannidis himself bemoaned the lack of testing and data for Covid-19. But he also argued that it was possible that, if we had not discovered the new virus, the additional deaths it has caused may have gone largely unnoticed. And in the absence of clear information about the fatality rate of Covid-19, he suggested, long-term lockdowns could be too hasty. “If we decide to jump off the cliff, we need some data to inform us about the rationale of such an action,” he wrote.
Not all epidemiologists agreed. “Ioannidis doing his schtick about standards of evidence is not helpful. Everyone knows we’re acting with little or partial information,” wrote Yale epidemiologist Gregg Gonsalves in a Twitter thread. “We all want better data. But if you don’t have it. Do you sit and wait for it in a pandemic?” Marc Lipsitch, director of Harvard’s Center for Communicable Disease Dynamics, suggested that dwelling on the ambiguities of data collection might be missing the point at a time when, amid a surge in Covid-19 deaths, corpses were piling up in churches in Italy.'
Onkin todella vastenmielistä että Ioannidiksen nimi, kuten voi hyvin esim.
@Toxic Enema :n hehkutuksista lukea, tuo tälle huonolle tutkimukselle niin valtavaa julkituutta että rajoitusten purkajat käyttävät sitä päälyömäaseenaan. Jatkuu...
'The study was released, like many other Covid-19 studies, as a preprint, meaning it had not yet received peer review vetting from other scientists. And it quickly came under criticism from other researchers, who eviscerated its methods on Twitter and in an online forum. (Two senior authors on the paper, Eran Bendavid and Jay Bhattacharya, did not respond to requests for comment.)
“The Stanford study was not a true random sample,” said Prabhat Jha, an epidemiologist at the University of Toronto, in an email to Undark. In addition, he said, “their testing was flawed, so they might have many false positives.”'
'The Stanford data also do not seem to match up with observations in other, more hard-hit parts of the country. In New York City, for example, an estimated 15,400 people have died from Covid-19, according to figures from the city’s health department. While death rates may vary from place to place, if the fatality rate of Covid-19 is as low as 0.12 percent, as the Stanford study authors claim, this would suggest that more than 12.5 million people in New York City have already been infected with Covid-19, even though only 8.3 million people live there.
A. Marm Kilpatrick, an infectious disease ecologist at UC-Santa Cruz and a vocal critic of the study, summed up his thoughts in an email: “They completely ignore the data from N.Y.”'
'“Most of the population has minimal risk,” he (Ioannidis) added, “in the range of dying while you’re driving from home to work and back.”
When Undark ran that statement by several public health experts, all of them expressed skepticism. That “claim might well be true,” Jha said, “but their data are not sufficiently definitive to make their claim.”'
'In a telephone interview, Cecília Tomori, director of global public health and community health at the Johns Hopkins School of Nursing, echoed that sentiment. “The question of making sure we have the best evidence to make decisions is a valid one,” she said. “But I think that there’s something else when we question some of the empirical reality of how awful this disease has been. And I think that’s really what’s going on.
Along with Ioannidis’ piece in STAT, Bendavid and Bhattacharya had published their own op-ed in The Wall Street Journal, before conducting the study, questioning whether the Covid-19 quarantines were overreactions. This has led some critics to question the authors’ motives. “The fact that Ioannidis and another author had published two articles … arguing that the threat of Covid-19 was overblown, and then published a study that was done in a way that was likely to produce a spuriously high estimate of seroprevalence (and thus a low [infection fatality rate]) was worrisome,” wrote Kilpatrick.
Accusations of biased sampling and sloppy methods have also disappointed some Stanford students who volunteered to collect samples for the study. Maria Filsinger Interrante, an MD/Ph.D. student at Stanford, is currently working long hours in the lab helping develop potential vaccines for the virus. But she spent 10 hours on a Saturday in early April helping to draw blood for the Stanford study. “If you want to prove to the world that the seroprevalence rate is higher, those are things that you would do in designing your study,” she said. “Were they done intentionally? I have no idea, and I would hope not, because I think the people who ran the studies are probably great people and good scientists. But it seems to fit with getting them the answer that they wanted, and that just makes me sad.”'
Onko Ioannidis tosiaan rakastunut liikaa vastarannan kiisken rooliin vai onko hän todella tullut omalta kohdaltaan sokeaksi niille vioille, joista itse on tutkimuksia kritisoinut kuuluisalla tavalla?
'In the meantime, critics of Ioannidis say the evidence remains murky, leaving them to wonder whether a venerated scientist known for his learned and very often justified skepticism of others’ scientific work has become blind to his own methodological flaws. Travis Gerke, an epidemiologist at the Moffitt Cancer Center and a visiting scientist at the Harvard T.H. Chan School of Public Health, said that he read Ioannidis’ work while a graduate student. Recently he has wondered if Ioannidis should consider re-reading his own most famous paper, “Why Most Published Research Findings are False.”
“His current study fits most of the high-risk criteria for falsehood that he outlines, such as publishing in a really hot scientific field with few corroborating studies, using a small bias sample, [and] reporting provocative findings in a politically charged arena,” Gerke said.
“If you just go through his own work,” Gerke added, “he seems to be breaking all his own rules.”'
PS: Andrew Gelmanin (jos et tiedä kuka hän on, älä keuli Ioannidiksen maineella) teknisempi kritiikki löytyy täältä:
Concerns with that Stanford study of coronavirus prevalence « Statistical Modeling, Causal Inference, and Social Science
Yhteenvedosta pieni pätkä:
"I think the authors of the above-linked paper owe us all an apology. We wasted time and effort discussing this paper whose main selling point was some numbers that were essentially the product of a statistical error."
Pitkä viesti mutta sen sijaan kannattaa lukea alkuperäiset linkit. Aihe on kuitenkin todella vakava kun näin kyseenalaisella tutkimuksella myydään ihmisten henkiä vaarantavia poliittisia toimia. Ja tämä vieläpä suurelta osin koska Ioannidis on kuuluisa alallaan.
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