Which Epidemiologist Do You Believe?

[Drareg]

https://unherd.com/2020/04/which-epidemiologist-do-you-believe/
Good article, good points made, my only issue is he shy’s away from addressing Ferguson’s past predictions which are failures, he does allude however to Ferguson’s ego in a matter of words, I don’t think he wants to be too critical just yet as he would want Ferguson back on again.

The author forgets as pointed out in the video interview by Johan Giesecke is that many of Ferguson’s ideas have never been tested in the field.

"Whether you’re more Giesecke or Ferguson, it’s time to stop pretending that our response to this threat is simply a scientific question, or even an easy moral choice between right and wrong. It’s a question of what sort of world we want to live in, and at what cost."

I don’t agree with the above statement entirely ,it presupposes that Ferguson’s science is legit, it’s more human written algorithms proven wrong in the past, even thinking about what they are doing now if the data for covid infections is been tampered with it means the future models will be even more incoherent with reality.
The last line is a gem, it’s biological personas at war here, all colors of that biological spectrum in the "peaty" sense, the defeated personas,depressed,psychotic,low thyroid,high estrogen etc


Now if we can just get an interviewer to ask bill gates why the public should trust him with medical treatments for their kids when Bill was friends with Jeffrey Epstein the child sex trafficker, this is a legitimate question that needs to be asked.


Which epidemiologist do you believe? - UnHerd

 

[Giraffe]

"Whether you’re more Giesecke or Ferguson, it’s time to stop pretending that our response to this threat is simply a scientific question, or even an easy moral choice between right and wrong. It’s a question of what sort of world we want to live in, and at what cost."

I don’t agree with the above statement entirely ,it presupposes that Ferguson’s science is legit, it’s more human written algorithms proven wrong in the past, even thinking about what they are doing now if the data for covid infections is been tampered with it means the future models will be even more incoherent with reality.

To put it more bluntly... Stop discussing model predictions and stuff and ask, "What sort of world do we want to live in?" Everything else is distraction.

 

[Drareg]

To put it more bluntly... Stop discussing model predictions and stuff and ask, "What sort of world do we want to live in?" Everything else is distraction.

Link to the written story-Nobel prize-winning scientist: the Covid-19 epidemic was never exponential - The Post

The below quote about scaring people into doing something seems to be a genuine belief the WHO and epidemiologists have, this won’t go down well with the public if this story catches on.

"More generally, he complains that epidemiologists only seem to be called wrong if they underestimate deaths, and so there is an intrinsic bias towards caution. “They see their role as scaring people into doing something, and I understand that… but in my work, if I say a number is too small and I’m wrong, or too big and I’m wrong, both of those errors are the same.”

Take him with a grain of salt IMO,I detect an angle with his views ,he starts blaming the boomers for this, this isn’t a generational issue imo, the younger generation have lapped this up, he also alludes to cashless society, smart lockdowns which I think is using tech more for lockdowns and is critical of the boomers allowing population growth to get out of control.

Would be interesting to look more into what he mentions about Ferguson’s paper being relative only to exponential process being present,I get the impression the "experts"have realized this including Ferguson so now they are playing politics on how to back out of it.

"His observation is a simple one: that in outbreak after outbreak of this disease, a similar mathematical pattern is observable regardless of government interventions. After around a two week exponential growth of cases (and, subsequently, deaths) some kind of break kicks in, and growth starts slowing down. The curve quickly becomes “sub-exponential”.

This may seem like a technical distinction, but its implications are profound. The ‘unmitigated’ scenarios modelled by (among others) Imperial College, and which tilted governments across the world into drastic action, relied on a presumption of continued exponential growth — that with a consistent R number of significantly above 1 and a consistent death rate, very quickly the majority of the population would be infected and huge numbers of deaths would be recorded. But Professor Levitt’s point is that that hasn’t actually happened anywhere, even in countries that have been relatively lax in their responses.

He takes specific issue with the Neil Ferguson paper. “In a footnote to a table it said, assuming exponential growth of 15% for six days. Now I had looked at China and had never seen exponential growth that wasn’t decaying rapidly.”