This post is a companion to Where Does the Misinformation Come From? on DH.org, which gives the slides and text of a lecture on Monday evening. Norman Fenton asked me to give the talk to a group that is neither pro nor anti vaccines or drugs but were all interested in how we go about collecting evidence .
The talk is dedicated, in my mind anyway, to Bri Dressen and all who have been harmed by vaccines – as RxISK is dedicated to people harmed by medical treatments more generally.
The lecture was recorded, and later edited and polished, by Bill James and is HERE and HERE but no longer HERE – Where Does the Misinformation. The sound catches at one or two points so you might need to check the text and slides on DH to clarify points.
There was for me a very helpful set of questions afterwards, one in particular which challenged me. Are you not asking us to forget Evidence Based Medicine and go back to the (unstated – bad) old days of Expert Based Medicine?
Caught on the hop, I gave the least satisfactory answer of the Q and A and for that reason was left mulling it over all night until the answer came to me.
The opening picture of this post is the last slide in the Misinformation Lecture. Albert (Bourla) greets Ursula (von der Leyen). The CEO of Pfizer meets the President of the European Commission. Vet greets Doc. Greek meets German. Does Yanis Varoufakis relish the moment when one of his countrymen fleeces those who have been fleecing his country?
Albert is being presented with a Distinguished Business Leadership Award by the Atlantic Foundation.
A few weeks afterwards the BBC interviewed Albert and one of the questions he was asked was what to do about all these people who have not had the vaccine.
Albert talked about the fear they have and said in a very emollient fashion that the one thing that can overcome Fear is Love – they need to love their fellow-men and friends and family.
But can Love overcome Greed? Can Albert find it within himself to make the data from the I-con trials freely available for general scrutiny?