Models based on assumptions in the absence of data can be over-speculative and ‘open to gross over-interpretation’

PERSPECTIVES ON THE PANDEMIC I (pt 1 & 2) A Conversation with Dr. John Ioannidis, Stanford University (Originally published March 23rd, 2020) PART ONE PART TWO JOHN KIRBY: So, professor, if you could just begin by telling us your name and a little bit about your background? DR. IOANNIDIS: I'm John Ioanniddis. I'm a professor of medicine and of epidemiology and population health at Stanford University. I'm one of the two directors, co-directors, of the Meta-research Innovation Center at Stanford

John Ioannidis - coronavirus interventions vastly lacked scientific credability, and 2020 has been a year of government "dictatorship"

The statistical jiggery-pokery employed since 2020 is so outrageous it is perhaps best viewed through the lens of (dark) comedy, so we forewarn you in advance that — in a change from our usual (possibly over-sober) tone — the following article has been written in a somewhat jocular manner, despite covering a topic that is very much not a laughing matter.

4 January 2022 - Norman Fenton is Professor of Risk Information Management at Queen Mary University of London and a Director of Agena, a company that specialises in risk management for critical system

Throughout the pandemic, the government and its scientific advisers have made constant predictions, projections and illustrations regarding the behaviour of Covid-19. Their figures are never revisited as the Covid narrative unfolds, which means we are not given an idea of the error margin. A look back at the figures issued shows that the track record,