The catastrophe of the Covid models

Link:https://www.spiked-online.com/2022/01/21/the-catastrophe-of-the-covid-models/

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Having taken all the modelling into account, SAGE produced a table that showed in stark terms what the future held if the government stuck to ‘Plan B’. With the usual risible caveat that ‘these are not forecasts or predictions’, they showed a peak in hospitalisations of between 3,000 and 10,000 per day and a peak in deaths of between 600 and 6,000 a day. In previous waves, without any vaccines, deaths had never exceeded 1,250 a day.

The government was effectively given an ultimatum. SAGE offered Johnson a choice between the disaster that would surely unfold and a ‘Step 1’ or ‘Step 2’ lockdown, both of which had been helpfully modelled to give him a steer. ‘Step 1’ was a full lockdown as implemented last January. ‘Step 2’ allowed limited contact with other households but only outdoors.

In the event, as we all know, Boris Johnson ignored the warnings and declined to implement any new restrictions on liberty. A few days later, Robert West, a nicotine-addiction specialist who is on SAGE for some reason, tweeted: ‘It is now a near certainty that the UK will be seeing a hospitalisation rate that massively exceeds the capacity of the NHS. Many thousands of people have been condemned to death by the Conservative government.’

It did not quite turn out that way. Covid-related hospitalisations in England peaked at 2,370 on 29 December and it looks like the number of deaths will peak well below 300. This is not just less than was projected under ‘Plan B’, it is less than was projected under a ‘Step 2’ lockdown. The modelling for ‘Step 2’ showed a peak of at least 3,000 hospitalisations and 500 deaths a day. SAGE had given itself an enormous margin of error. There is an order of magnitude between 600 deaths a day and 6,000 deaths a day and yet it still managed to miss the mark.

Author(s): Christopher Snowdon

Publication Date: 22 Jan 2022

Publication Site: Spiked Online

12 strategies to uncover any wrongs inside

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Look for nonlinearities

Not all 10% increases are created equal. And by that we mean, assumption effects are often more impactful in one direction than in the other. Especially when it comes to truncation models or those which use a CTE measure (conditional tail expectation).

Principles-based reserves, for example, use a CTE70 measure. [Take the average of the (100% – 70% = 30%) of the scenarios.] If your model increases expense 3% across the board, sure, on average, your asset funding need might increase by exactly that amount. However, because your final measurement isn’t the average across all the scenarios, but only the worst ones, it’s likely that your reserve amounts are going to increase by significantly more than the average. You might need to run a few different tests, at various magnitudes of change, to determine how your various outputs change as a function of the volatility of your inputs.

Publication Date: 14 July 2021

Publication Site: SLOPE – Actuarial Modeling Software