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by chedca21 1284 days ago
https://www.bmj.com/content/371/bmj.m4425/rr-31

Covid-19: politicisation, “corruption,” and suppression of science

"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" -March 2020

The bigger scandal is how covid case:fatality rate was so much higher in some places than the global average. https://www.nbcnews.com/health/health-news/why-some-doctors-...

2 comments

The fatality rate for a disease that is very often asymptomatic highly depends on testing. The rate will go way down in places where lots of people are required to or just do get treated frequently.

Most asymptomatic cases will go unnoticed in places with less testing so the fatality rate will go way up.

Also how you count whether or not a death gets tagged with covid matters. Lots of people had Covid and plenty of deaths will just coincidentally happen while a person has a minor infection which didn’t affect the outcome. How or when do you count that?

Professor ioannidis forecasted 10,000 deaths in the US as a mid range guess of what to expect. He’s not exactly a good appeal to authority.
Ioannidis did a antigen survey and found the vast majority of cases were mild; https://apps.who.int/iris/handle/10665/340124

A survey by the most cited epidemiologist alive is not a forecast for one. It is the best appeal to authority one can make. I've seen it shown that h1n1 in england in 2009 had a IFR of 0.05% which is greater than the revised figure for covid.

Amazing how all the proof in the world makes such little difference to the average Luddite who will just defer to authority regardless. Stanley Milgram was clearly right about everything he said.

The vast majority of cases are mild, yes. This doesn’t change the fact that Ionnadis’ predictions of the severity of the pandemic were off by a factor of x100.

Here is a pretty good recap of his blundering walk through covid

https://sciencebasedmedicine.org/10000-deaths/