Embracing uncertainty is the only path out of the pandemic
A few days ago, Sajid Javid made one of the most thoughtful and encouraging statements by a government minister during the whole Covid crisis.
Early In July, he seemed to be falling under the control of the modellers. The number of daily infections, he stated confidently, would soon reach 100,000, bowing to the so-called experts.
We now know that the peak in daily infections in the middle of last month was only just over half that number.
There is a well-documented litany of pessimistic forecasts of cases, hospitalisations and deaths which have proved to be wrong within a few weeks of them being made.
One of these cited by Patrick Vallance, the government’s chief scientist, last October was so wildly flawed that it earned Vallance a rebuke from the official statistics watchdog, the UK Statistics Authority
Javid has absorbed these failures and has learned from them. Now he says “no-one really knows” how many Covid cases there might be during the rest of the summer. He refused to be drawn into making another prediction.
This is a crucial step in liberating the government from the python-like grip – no, make that a giant anaconda grip – which the epidemiological modellers have so far exerted upon its leading members.
Javid’s statement is truly scientific, far more so than the rather straightforward bits of applied maths which constitute the epidemiological models. As the Health Secretary has understood, there is a very large amount of inherent uncertainty about the future trajectory of any pandemic, not just Covid.
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To the layperson, the maths of the epidemic models appears very intimidating. But it is well within the grasp of graduate students even in economics, for example, where the level of maths required is less than that needed by physicists, let alone by real mathematicians.
Such models are easy to set up and solve using well-tested open-source software.
In early April 2020, for example, Professor Ferguson and the team at Imperial College were already famous for their prediction that without lockdown there would be 500,000 deaths in the UK.
I did an experiment. I asked a young UCL researcher, Rickard Nyman, to set up a standard epidemiological model in a free, downloadable package and to set the relevant parameters so that the initial reproduction number – the infamous ‘R’ – was 2.5. This is what it was believed to be with the initial Covid variant.
Within half an hour, the work was complete and the forecast produced. The answer was the same as that of the Imperial team, supported by large amounts of taxpayer funded research money.
Michael Gove got into trouble four years ago for trashing experts. Gove’s view must have been shaped by the spectacular failures of the experts and their forecasts of immediate disaster if Leave won in 2016.
Javid does not dismiss models and experts outright. But he appreciates there is a great deal of uncertainty in this so-called science.
The assumptions which are fed in, such as how human behaviour adapts during a pandemic, are crucial. It is these which are both the legitimate and the essential focus of democratic scrutiny.