Is it a Scenario or a Prediction?
Interpreting modelling speak
In December 2021, the former Chief Scientific Advisor Patrick Vallance publicly defended modellers and their modelling in The Times and on the government’s official website.
He considered monitoring clinical data as ‘trying to get a good fix on the severity of disease caused by Omicron.’ But Vallance was already at odds with the data. Nine days earlier, in the Telegraph, TTE geezers had written that ‘We're almost certainly overreacting to the Omicron variant:’ South African data reported fewer intensive care patients, less severe disease, and shorter hospital stays.
Sir (now Lord) Patrick was at pains to impress on the populace that “epidemiological modellers have an unenviable task.’ He confirmed what we all know: ‘Modellers always have to make assumptions.’
‘They will make assumptions about vaccine effectiveness, they will model different levels of viral transmission, mixing patterns and different levels of disease severity. The range of assumptions modelled can be very broad,’ he said.
Sir (now Lord) Patrick Vallance went further in evidence to the Science and Technology Committee, stating on record that modelling estimates were scenarios, not predictions.
Old geezer note: the “200” Sir Patrick, now Lord Vallance, meant 200 deaths daily. In a 21 September 2020 press conference, he published a graph showing Covid cases hitting 50,000 a day by 13th October without further action - cases peaked at 19,452.
Chart: The Spectator - Source: Carl Heneghan / coronavirus.data.gov.ukGet the data
Rhetorically, however, he answered his question - the information models report is “not real.”
But it doesn't end there.
In December 2021, Fraser Nelson, former chief editor of the Spectator, tackled a Sage Covid modeller on Twitter, reporting it was quite the revelation. We were now heading for up to 6,000 deaths a day.
The modeller in question was Professor Graham Medley, chair of the SPI-M-O modelling subgroup of SAGE, which provided evidence to the UK’s COVID-19 response.
‘Prof Medley suggests the scientists are doing what they are “asked” during a “dialogue” with a pre-existing "policy"’ note.
“We model the scenarios that are useful to decisions,” wrote Medley. Nelson rightly noted models were being used for ‘policy-based evidence-making’.
When we wrote that the estimated number of deaths averted by vaccines based on modelling is implausible, we also checked the RCT data: The published paper reports that 15 participants in the vaccine group died and 14 in the placebo group.
Taking aside the point that we usually only use clinical study reports, as published papers under-report harms, a difference of millions saved would be as clear as day in the publication. Yet, it reports no difference. If the UKHSA has data on mortality by the number of vaccine doses and will not disclose the data, they aren't sitting on millions of lives saved.
So, to recap: Sir/Lord Vallance has told us models are full of assumptions, the data they report are unreal, and modellers revealed their modelling is done to fit the policy narrative of the time.
At TTE headquarters, we are finally piecing together how the terminology is deliberately used to confuse, terrify, or reassure the populace. It is predictions for events that no one checks; it is scenarios when someone checks.
This post was written by two old geezers who model scenarios and do scenarios when they need models to create scenarios instead of models. Clear?
Presumably the same applies to CO2 Global Warming on steroids?!
Every time reference is made to mr vallance and his advice during the plandemic, or to the advice of sage, I find myself feeling physically sick. To think none of these people are serving time right now in one of hms jails for crimes against humanity. Quite the contrary, they were catapulted to higher levels of incompetence. Whatever happened to integrity, honesty, morality in the UK? We are witnessing its demise one day at a time. As Tess Lawrie asked one other scientist she worked with and wrote a paper with, how he slept at night, after he made an abrupt turn and refused to sign off on their research.