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Scientists Inform, Leaders Lead

Author: Alain Catzeflis

In 2009, when governments were showering money on a banking industry that had behaved with almost unbelievable negligence driving the world economy to the brink, the Queen was shown round the London School of Economics. Expressing the view of her most humble subjects like myself she asked: “Why did no one see this coming?”.

This same question is now rising to confront us as the Covid-19 pandemic scythes its way across the globe.

We know two things about how Britain is facing up to this challenge. The first is that, despite clear warnings as early as the beginning of January, unlike some European countries, we’ve been noticeably slow off the mark. And we are likely to pay for it. The death toll in Britain looks like being one of the highest if not the highest in Europe especially now that care homes have become epidemic hot spots.

The second is that, after a decade or more of punitive austerity aimed chiefly at our public services and the less well-off, the NHS described by Boris Johnson, without a hint of irony, as the ‘beating heart of Britain’ is, along with other key services, struggling, only kept from being overwhelmed by the extraordinary devotion of its workers.

What we don’t yet know is quite what the government was thinking and what advice it was being given in those very early weeks. That will come in time. Although both Patrick Vallance, the Chief Scientific Adviser, and Chris Whitty, the chief medic, are belatedly acknowledging that Britain, unlike Ireland and Germany, has not been and is not testing enough. It also raises the suspicion (perhaps unfounded perhaps not) that the absence of testing was – and remains – part of an intellectually seductive ‘herd immunity’ strategy. This possesses a certain, cold logic but is actually a giant game of Russian roulette.

The government repeatedly says that all along it has been ‘led by the science’. This raises two question. 

The first is which science? Our science, the World Health Organisation’s science, whose? 

The second is: does scientific modelling offer more than a useful set of clues when making decisions with such fateful consequences?

The situation we are faced with is unprecedented at least in my lifetime. There are no easy choices. And there are certainly no binary ones: public health or the economy. So as observers we need, as Keir Starmer says, to be constructive and balanced. We need, to park party politics and have good cause to criticise what the Johnson administration is doing. But that doesn’t mean we should be silent.

The deeper we look into the belly of this beast the more horrific the human experience: heart-breaking stories about elderly immensely vulnerable residents in care homes being taken by the virus in their hundreds without their loved ones by their side while poorly equipped but hugely dedicated staff look on helplessly as the end comes; NHS staff performing deeds of mundane heroism by putting themselves in harm’s way every day and every night while scrounging for scarce Personal Protective Equipment, some having to make do with snorkelling masks and bin bags to keep the virus at bay; bus drivers, posties, refuse collectors, shelf stackers and supermarket delivery drivers beating into the gale; food banks running short, domestic abuse spiking, workers wondering if they’ll work again. People who are redefining the meaning of ‘key worker’, citizens we cannot do without.

It is often said that Covid-19 is a great leveller. No more so than when the Prime Minister was rushed into intensive care just hours after he told us he had minor symptoms. But Covid-19 is no more a leveller than, say, cancer. Any of us can get it. But by no means all of us suffer the same social and economic consequences of its fallout. What Covid-19 has shown – apart from the insanity of running down our public services – is that, in sickness and in lockdown, some are more equal than others. It’s all very well telling people to work from home but a family on a very low income or someone entirely dependent on Universal Credit and food banks will find that much harder to do.

The hope is that the socio-economic inequalities exposed by this crisis will lead to greater social justice. It may. But it may equally see a pushback by those who wish to maintain the neo-liberal status quo. We may all be in this together now but it is likely to be business as usual once things get back to normal. This presents the opposition and Keir Starmer in particular with both a challenge and an opportunity.

My purpose here is not recrimination. There will be time and reason enough for that. What interests me is how those who lead us in this continuing crisis make big decisions. What tools do they use? Is it science or is it just predictive modelling because the two are not necessarily the same thing. Try as we might we cannot predict the future. As Helen Ward, Professor of Public Health at Imperial College, London, says “modelling isn’t a value-free process that comes with instructions”. Faced with a set of probabilities Boris Johnson has to exercise his judgement. He has to decide.

In their excellent book Radical Uncertainty: Decision-making for an unknowable future, the economist John Kay and Mervyn King, former governor of the Bank of England examine how good and bad decisions are made based all-too-often on data which is either incomplete or misleading or beguiling because it suits the prevailing narrative.

The book’s main thrust is how an over-reliance on modelling by the financial industry that didn’t really understand ‘what was going on’ led to the 2008 economic crisis. It nails the absurdity that you can reliably control risk - tame it- once you’ve quantified it. And in the case of junk bonds full of dangerously risky mortgages, sell it on seeding a concealed and deadly virus all around the world’s financial system. But it also draws on a much wider canvas including, presciently, public health.

The authors illustrate the crucial importance of not allowing yourself to be overly influenced by what, after all, is no more than sophisticated crystal-ball gazing.

In 1981 the first deaths from an unusual lung disease occurred among men in San Francisco. The authorities were baffled and, as deaths mounted, worried. The World Health Organisation was asked to create a model to guide policymakers. So it designed a bells and whistles model that predicted a relatively benign outcome. They were out by millions. HIV/AIDS became, in effect, a pandemic. It turned out that the WHO model was largely a desk study of susceptible demographic groups . A simpler one by a team at Oxford University which relied on finding out how HIV/AIDS was actually being transmitted on the ground turned out to be much more accurate.

Science is hugely important. But it is not infallible. A scientific ‘fact’ is only a fact until another fact comes along that proves it isn’t. Confronted with growing evidence of disarray the government insists that Covid-19 is an entirely new event implying that it was unforeseeable. That is not the case. It is not an unknown unknown. Covid-19 is the pandemic we have been expecting and rehearsing for. It has merely come out of the blue and we have been caught flat-footed distracted by among others things Brexit. .

There’s something else going on here. It’s the all-too-familiar sound of group think. Having set its course based on the premise that the best – and least controversial - policy was to follow the science the government is finding it hard to reset its approach. This is evident in the baffling some might say stubborn refusal to test, trace and isolate.

John Kay and Mervyn King put it like this: “In the end a model is useful only if the person using it understands that it does not represent ‘the world as it really is’ but is merely one among many tools to base a decision on.” In other words, there’s data and there’s judgement and they’re not the same thing.

We live with uncertainty but we crave certainty. So we tend to believe the numbers that most suit our views. Discourse about how to deal with this uncertainty has, John Kay and Mervyn King argue, “fallen victim to pseudoscience”. The Johnson government took comfort from the early projections by the Imperial College models and took a softly, softly approach which was also what probably suited the PM's own bias to shrug off illness and refrain from anything that smacks of big government or the nanny state. They were wrong.

The parallels with the 2008 financial crisis are striking. Mortgage-backed securities were magically transformed into juicy Triple-A investments that sold like hot cakes across the world until someone took the trouble to knock on a few doors in working class America to discover an epidemic of defaulting borrowers.

I get the sense that this administration is finding it hard to stop campaigning and start governing. The mantra ‘we are being led by the science’ provides a convenient scapegoat when things go wrong. It is both a crutch and an alibi. It may be politically convenient. But it is not leadership.


The publisher is the Centre for Welfare Reform.

Scientists Inform, Leaders Lead © Alain Catzeflis 2020.

All Rights Reserved. No part of this paper may be reproduced in any form without permission from the publisher except for the quotation of brief passages in reviews.