During the Brexit referendum campaign, Michael Gove, who at
the time went by the Orwellian job title of Secretary of State for Justice,
said in a TV interview with Sky News that “I
think the people in this country have had enough of experts.” When quizzed
on this, he went further and suggested that “these people are the same ones who got consistently wrong what was
happening.” It was a somewhat off the cuff remark but it instantly caught
the mood of the times. Recall the summer of 2016 was the time when British
politicians exaggerated the benefits of Brexit. It was also the first time that
the world became aware of just how little regard Donald Trump has for the truth
– those inconvenient pieces of evidence that suggest that one’s prejudices may
not always be right. But this attitude has had a hugely damaging effect on the
quality of policy debate, and nowhere is this more important than in the debate
over Covid-19.
As an economist who does not always get every forecast
right, this argument is sometimes thrown in my direction. After all, what use
are experts if they are not infallible? I have explained on numerous occasions
that economics is not a predictive discipline – economists cannot foretell the
future – but in the public mind that is what we do. When it comes to matters
scientific, the public holds the view that there is a single body of evidence
which represents the truth and anything that is not inside this envelope of
perceived wisdom must be false. But just as with economics, the public
perception of science is not wholly true. Scientific conclusions on issues such
as epidemiology depend on a host of input assumptions, which if changed can
result in very different outcomes.
There has been much debate in recent weeks about the size of
the R (or reproductive) number associated with Covid-19. As we are all now
aware, an R number in excess of one implies the rate of infection is rising. It
is extremely difficult to measure R in real time and estimates for the UK in
the range 0.7 to 0.9 imply a margin for error that puts it dangerously close to
one. It also varies by geography so if it is higher than one in some places,
this runs the risk of a second wave of Covid-19 cases. The R value is
calculated using data such as hospital admissions, intensive care unit
admissions and deaths. However if the cause of death is wrongly attributed,
this will impact on estimates of R. Since age is also a factor in deaths from
Covid-19, the overall R value may be biased upwards if we do not take
sufficient account of this.
Those responsible for making these calculations are
acknowledged experts in their field, and are aware that their estimates are
subject to a margin of uncertainty. The problem then becomes one of deciding
whether the estimates form a sufficiently strong basis for the decisions made
by policymakers, who ultimately have to carry the can. Or to put it another
way, is the science sufficiently robust to support some of the recent policy actions?
With the UK having suffered the second highest recorded
death rate from Covid-19, questions are increasingly being asked of the
policies adopted over recent months. Quite how an island has significantly more
deaths than other European countries which share land borders suggests that
there have been policy mistakes. The government has consistently stated that it
is “following the science,” therefore either the advice was flawed or the
policy implementation was.
The most obvious question is why the UK did not
impose some form of border controls – after all, they were employed by nearly
all other European countries? As it happens, the minutes of the Scientific Advisory Group for Emergencies (SAGE) for 23 March suggested that “closing borders would have a negligible impact on spread.” Yet on
Monday the UK introduced a quarantine regime in which people entering from
overseas are now expected to self-isolate for 14 days. This appears to be
somewhat self-defeating since the rates of infection are now lower in other
European countries than the UK, and it would have made more sense to implement
these restrictions in March. Nor is it clear how the policy is enforceable
since there is no guarantee that the address people give on the form which they
are legally required to fill in is necessarily where they intend to stay.
The policy on schools closure has been similarly muddled.
The SAGE view on 16 March was that “school closures constitutes one
of the less effective single measure to reduce the epidemic peak.” Two days later,
“SAGE reviewed available evidence and
modelling on the potential impact of school closures. The evidence indicates
that school closures, combined with other measures, could help to bring the R0
number below 1.” On the basis that the government believed the epidemic to
be under control, it announced that primary school pupils would return to
school at the start of June. But many local authorities, and indeed parents,
questioned whether the policy was safe and many children simply did not show up
at school. With attendance rates last week running at just 7% the government
this week conceded that its plan was not workable and backtracked on its school
reopening policy.
Then there is the vexed question of the lockdown. On 18 March, SAGE concluded that there was a case for a lockdown in London but “measures such as restricting public transport … would have minimal
impact.” Five days later, there was
a stronger case for “reducing contact
with friends and family outside the household, and contact in shops and other
areas.” One of the attendees at this meeting was the epidemiologist
Professor Neil Ferguson, who yesterday told a committee of MPs that “had we introduced lockdown measures a week
earlier, we would have reduced the final death toll by at least a half.” Yet
the SAGE minutes do not suggest that
the scientific consensus was pushing for an earlier lockdown. Nor is there much
evidence during the early stages of the debate that they paid much attention to
the problem of shielding the older, more vulnerable members of society despite
the fact that some estimates suggest “more than half of England’s coronavirus-related deaths will be people from care homes.”
It is easy to be critical of a government which has presided
over the highest number of Covid-19 deaths in Europe, and its communication
strategy has been muddled and inconsistent (viz. the Dominic Cummings affair).
However, its claim to be following the science does appear to stand up to
scrutiny – at least to some degree – as a cursory glance of the SAGE minutes suggests.
The government has made errors and will ultimately be held accountable for them
(we hope). But the scientific advice has also flip-flopped. This is not to say
that the SAGE committee was wrong – it was acting on the best information
available at the time, and like all good scientists members changed their views
in the face of new evidence.
Whilst the experts may not get everything right, they do get
more right than they do wrong. Deductive failures do not mean that we can do without
experts – Michael Gove was wrong about that. But next time you hear the media calls suggesting that economists’ forecasts are always wrong remember that the so-called hard science disciplines do not always get it right
either
