In case you’ve missed previously my expressed feelings about computer modeling, they’ll be inflicted on you all yet again! They are only as good as the data employed/deployed. And can very easily be manipulated.
Deaths could hit 6,000 a day,’ reported the newspapers on 19 December. A day later documents for the 99th meeting of Sage were released which said that, without restrictions over and above ‘Plan B’, deaths would range from 600 to 6,000 a day. A summary of Sage advice, prepared for the Cabinet, gave three models of what could happen next:
-Do nothing (ie, stick with ‘Plan B’) and face “a minimum peak” of 3,000 hospitalisations a day and 600 to 6,000 deaths a day
-Implement ‘Stage 2’ restrictions (household bubbles, etc) and cut daily deaths to a lower range: 500 to 3,000.
-Implement ‘Stage 1’ restrictions (stay-at-home mandates) and cut deaths even further: to a range of 200 to 2,000 a day
After a long and cabinet debate, the decision was to do nothing and wait for more data. ‘Government ignores scientists’ advice,’ fumed the BMJ. ‘Staggering and deeply frustrating,’ said Jeremy Farrar, chairman of the Wellcome Trust. ( Accurately Wellcome -Sanger vested interest in agenda pushing- eugenics ) But the decision not to act meant that the quality of Sage advice can now be tested, its ‘scenarios’ compared to actual.
Last year, whistleblowers privately accused Sanger of commercializing a gene chip without proper legal agreements with partner institutions and the consent of the hundreds of African people whose donated DNA was used to develop the chip. “What happened at Sanger was clearly unethical. Full stop,” says Jantina de Vries, a bioethicist at the University of Cape Town in South Africa, who has followed the dispute.
Back to the Spectator:
Let’s start with the Warwick model. It published various Covid scenarios depending on Omicron’s possible ‘severity’: 100 per cent as severe as Delta, 50 per cent, 20 per cent and 10 per cent. A UK Health Security Agency (UKHSA) document released on New Year’s Eve said: ‘the risk of presentation to emergency care or hospital admission with Omicron was approximately half of that for Delta’. That’s still its best estimate. So we open with the 50 per cent severity scenario. Here’s how Warwick’s model is performing for hospital
So: pretty far out. The Warwick scenario which closest matches actual hospitalisations in England is the one that assumes Omicron is 10 per cent as severe as Delta. But no one has ever claimed the new variant is as mild as that.
Let’s look at the Warwick Model that shows 10 percent severity
So why were the Sage “scenarios” so wide of the mark?
An annex in the Sage documents points to some of these revisions. It suggests that the LSHTM changed their models to show that Omicron was between three to eight times more transmissible than Delta – but did not appear to make any adjustments in the models for severity. They assumed the virus was as deadly as Delta but by then real-world South African data was clearly showing the variant had far less severe outcomes.
It’s not the first time Sage’s modelling has been overly pessimistic. Before the summer reopening Sage modelled bed occupancy and in no fewer than nine scenarios the actual figure was lower than modelled. We’re often told that models look wrong in retrospect because people adjust their behaviour – or because restrictions are implemented, thereby preventing predicted calamity. But when Sage gloom is ignored and reopening has gone ahead, its scenarios have proved to be wide of the mark. Let’s look at last year’s summer reopening in the face of a Delta wave: Sage offered nine ‘scenarios’, each one too pessimistic.
Then again last September, when schools were reopening, Sage modelled hospital admissions. Too pessimistic again. Some have since claimed these scenarios were never intended to be forecasts or predictions, but let’s remember how they were described at the time: ‘The two scenarios of R = 1.1 and R = 1.5 attempt to provide an envelope which contains the likely epidemic trajectory over the next couple of months,’ (our emphasis). As so often, hospitalisations ended up below the lowest range of the lower Sage scenario.
The defences of Sage modelling (including those published in The Spectator) leave many questions unanswered. If the modelling is only ‘illustrative’ and does not predict or forecast, then why are they summarised (and presented to ministers) this way: “Without intervention beyond those measures already in place (“Plan B”), modelling indicates a peak of at least 3,000 hospital admissions per day in England.
And why are scenarios described as being ‘likely’?
Modelling matters. It has consequences. If the Sage summer reopening scenarios had been believed (as they were by Keir Starmer) lockdown could have been extended – with all the social and economic damage that would entail. If the Sage autumn scenarios had been believed, schools might have remained shut. If just one December cabinet meeting had gone differently there would have been sweeping restrictions that the real world data now tells us would have been completely unnecessary.
“Modelling matters” Indeed, it does. It’s very influential. In covid and in climate science. One wonders why it is then that modelling is so out of touch with reality? Repeatedly. It can’t be happenstance! Since it occurs so very often. One can only conclude in both instances (covid and climate) this is intentional misrepresentation of reality to push other ideas and goals.
There is additional information at the Spectator link