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Tue 31 March 2020
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Nafeez Ahmed on evidence that Boris Johnson’s Government was more focused on saving money than lives when it came to issues such as school closures.

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A new corpus of documents from the Government’s Science Advisory Group for Emergencies (SAGE), published on 20 March, throws new light on how the Government’s reluctance to take act early on the Coronavirus threat resulted from high-level concerns around the British economy.

The revelations provide new context for reports that Prime Minister Boris Johnson’s chief advisor Dominic Cummings had advocated a policy in February which was described by sources as amounting to “herd immunity, protect the economy and if that means some pensioners die, too bad”. Downing Street has said that the claim is fabricated.

However, adding weight to the claims, economic considerations are explicitly mentioned as a key priority in Government documents weighing up the costs and benefits of early action.

In Part One of this investigation, it became clear that the scientists advising the Government were over-reliant on abstract mathematical models which were insufficiently engaged with the mountains of empirical data coming out of cases around the world from Italy to China. 

That appears to be one reason why it took the Government so long to realise that previous modelling assumptions were so flawed that they were sleepwalking Britain into potentially millions of deaths.

And yet, the main ingredients demonstrating the urgency of early social distancing action, mass contact tracing and other such measures are still clearly identifiable across the medically-focused scientific literature that was being fed to the Government. Somehow, this science did not make it into policy. Why?

Part of the answer can be found from a close analysis of SAGE’s documents and reports to the Government, published by the Government on 20 March. 

The Government has based its response decisions on advice provided by three advisory networks in SAGE: the New and Emerging Respiratory Virus Threats Advisory Group (NERVTAG), the Scientific Pandemic Influenza Group on Modelling (SPI-M), and the Independent Scientific Pandemic Influenza Group on Behaviours (SPI-B).

The Government’s overall strategy was developed by achieving ‘consensus’ within and between these three bodies.

Analysis of the SAGE corpus suggests that inputs from the third group on behavioural science ended up consistently watering down scientific calls for more urgent social distancing action. 

The recommendations that resulted from medical and epidemiological findings being sieved through Government behavioural science showed no explicit concern with saving the maximum number of lives. Instead, they mentioned the need to balance public health goals with the desire to protect “economic” and “business” priorities.


A Confused, Muddled Approach on School Closures

On 19 February, the Government received advice from its modelling advisors on school closures. The SPI-M document’s top-line finding was weak – that the impact of closures would be “very uncertain” because of a lack of knowledge on how the Coronavirus was being transmitted and the potential severity of infection in children. Despite that, its main findings were still clear. But, they were strangely ignored by the Government.

“The consensus view is that a long duration school closures (six weeks or longer) are most effective if started as early as possible,” it said. “They are less sensitive to timing than shorter school closures.”

The document also noted that “the larger impacts are seen when closures take place early in a UK outbreak” and that “up to a certain point, longer school closures are likely to… [be] more effective than shorter ones”.

But, the document was also inconsistent. Its repeated assertion that the effect of school closures would be “limited” contradicted its own figures: “For R0 [reproduction number – the number of people a single infected person goes on to infect] around range 1.9 – 2.3 and school closures of 6 – 12 weeks: the IBMs [individual behavioural models] suggests an effect of the order of 20 – 60% reduction, while the compartmental models suggest 7.5% – 30%.”

In other words, the Government was looking at a range of impacts that could reduce the overall epidemic by anywhere from 7.5 to 60%. 

Given that lives were at stake, and that the upper range would be made more likely by earlier action, why was early action avoided? 

The document does not answer this directly. But, it urged the Government to account for “the large economic and educational costs of school closures, including increased levels of workforce absence in the health and care system”.


Ignoring an Entire Body of Research

Meanwhile, the document made no reference to the very substantial body of independent scientific modelling over decades, demonstrating unequivocally that early school closures dramatically reduce the overall size of an epidemic and reduce peak fatality rates.

According to Professor Nicholas A. Christakis, a sociologist and physician at Yale University, although there are well-known costs to school closures, scientific studies looking at the US, UKJapanItaly and China all show that early school closures successfully slow and reduce the size of epidemics “even if kids are not susceptible”.

School closures, he said, “are one of the most beneficial ‘non-pharmaceutical interventions’ (NPI) that can be employed, more effective even than reactive quarantines or banning of public gatherings. Partly, the reason is that parents also stay home as a result”. 

Pursued early, school closures dramatically reduces the burden on healthcare facilities from the outset and thus saves lives.

Yet, such data is never acknowledged by the SPI-M document, which also makes no reference at all to new data coming out of China, east Asia, or elsewhere on school closures.

Most conspicuously absent from the modelling described in the document is the potential impact on reducing the numbers of deaths. 


Saving Lives – or Money?

It is difficult to avoid the conclusion that the Government’s scientific assessment was poor, inconsistent, disengaged from relevant empirical data, and disengaged from the wider scientific literature. 

Things appeared to worsen when this evidence was interpreted further by the Government’s behavioural science advisors. 

On 4 March, the Independent Scientific Pandemic Influenza Group on Behaviours (SPI-B) produced a consensus document firmly rejecting the idea of school closures on the grounds that they “will be highly disruptive and likely to present an unequal burden to different sections of society”. Its focus was on identifying “the combination of interventions most likely to be socially acceptable” – rather than those most likely to save the most lives. 

On 9 March, a Government document summing up interventions being considered by the Government noted that the recommendations did “not cover economic, operational or policy considerations”. The document therefore urged the Government to ensure that it takes into account economic impacts before ratifying any intervention: “Any decision must consider the impacts these interventions may have on society, on individuals, the workforce and businesses, and the operation of Government and public services.” 

The Government has refused to publish the assessments being conducted on the economic impacts of school closures from its SAGE disclosures. But we do know, thanks to The Guardian, that these assessments were being actively undertaken: “School closures lasting four weeks could cut 3% from the UK’s GDP, costing the economy billions of pounds, according to research being considered by the Government as it weighs up the benefits and risks of shutting down classrooms… The advisors admit that economic considerations are an inevitable part of calculations. They have been attempting to model the impact of school closures on the spread of COVID-19, with mixed results.”

I asked the Cabinet Office whether the Government’s economic assessments of the potential impacts of certain interventions relating to COVID-19 played a role in its decision to avoid early social distancing action for nearly two months. It said “our approach is guided by the best and latest scientific advice, and draws on expertise from across the scientific community and Government”.


A Perfect Storm 

Those assessments have not been released as part of the SAGE corpus, but they clearly inputted into Government thinking and likely fed into the reluctance to take early action.

We cannot tell exactly what went wrong, but we can build up a plausible picture.

Much of the scientific modelling on the Coronavirus was based on flawed assumptions which did not sufficiently account for what was already going on outside of the UK. The modelling showed little awareness of a wider body of scientific literature on the efficacy of early social distancing interventions. 

Even so, the acknowledgement that early action would be helpful does emerge in SAGE’s corpus, but failed to become hard Government advice until 16 March in the wake of the Imperial College study. 

A principal reason for that failure was the input of several Government advisory groups which raised concerns about “social acceptance”, “disruptiveness” to ordinary life, and the need for the Government to balance its approach with assessing impacts on the “economy” and “business”. 

In the midst of an ongoing unprecedented public health crisis with deaths ramping up exponentially every day, the confused preoccupation with economic concerns and social acceptance fatally disrupted the UK Government’s capacity to understand the gravity of the crisis and act fully in the public interest.


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