A LinkedIn article by Lynette Nusbacher
I’ve read three pieces in the last few days which critique measures taken to control the spread of infectious disease. These critiques characterise the measures as ‘hysterical’, and suggest that the measures will inappropriately sacrifice economic activity in pursuit of keeping people alive. Two critiques were by legal scholars. None is by a scientist or an economist.
Everything in life is a trade-off. Countries which are currently attempting to keep people alive at the cost of economic activity are making a conscious choice. They are doing so based largely on epidemiological models. In the critiques I read, these models are treated as essentially fictional. That is to say, rather than treating forecasts and scientific modelling as the product of a scientific discipline, they are treated as pure invention.
Because mathematical modelling and associated forecasting are such an important part of the way our financial services industry works, and because none of these people has (so far as I know) criticised investment decisions based on mathematical modelling; I consider this disingenuous. Very serious people in very serious professions make very serious decisions based on modelling and systematic forecasting. High-stakes financial decisions based on modelling are rarely described as ‘hysterical’, even when harshly critiqued, and even those which can create significant market volatility.
These critiques of strict controls over human behaviour point out, rightly, that artificially inducing a recession (which is what we are now doing, globally) will kill people. This is true: many high-stakes decisions, including public health policy decisions, cost lives. Many decisions will cost different people’s lives in surprising ways. This is a practical application of the Trolley Problem: Policy decision A will kill so many people; policy decision B will kill so many different people; what is the right decision?
Some of these critiques have implied that the people who would be killed by the COVID-19 trolley would largely be elderly and therefore of less economic value. They point out — or they could point out — that the Grim Reaper would be coming for many of these people regardless of this coronavirus. They point out that the economic stagnation created by an induced recession will result in morbidity (illness) and mortality (death) as well. Choosing to protect the elderly and vulnerable from COVID-19 at the expense of the young and healthy, is the wrong way to steer the trolley.
They suggest that the elderly and vulnerable should be quarantined, and that otherwise economic activity should continue more or less as normal. Some of the elderly and vulnerable would contract the illness, some of them would die; some of the middle-aged would contract the illness, some of them would die; some of these people would die anyway; but the economy would continue to function and the greatest good would be achieved for the greatest number.
This approach rejects epidemiological modelling as a sort of confabulation. This permits these critics to ignore the hundreds of thousands who would be killed, and larger numbers who would be hospitalised and survive, and larger numbers still who would become ill but not require hospitalisation. By focussing on the idea that the estimates based on, for instance, the Imperial College modelling; are worthless, the number can be minimised. Far more important, however, the economic impact of this illness and death is ignored.
Integral to every one of these critiques is the implicit assumption that the effect on the economy of widespread illness and death would be negligible. Getting everyone off their sofas, off of Zoom and back into their conference rooms would generate sufficient economic growth to far outstrip the economic effects of the deaths and illness of millions.
Death imposes costs on an economy, though. Illness imposes costs on an economy. Treatment of illness has complex effects on an economy. Assuming that costs only come from control measures, and that a marginal increase in deaths of a few hundred thousand people has negligible costs, is driving the trolley without a clear view of who is lying on which track.
A full understanding of this trade-off requires a combination of economic and epidemiological modelling. It requires using structured methods to forecast the future. Doing so requires us to accept that even though there is no accurate foretelling, we still need to forecast. The weather forecast isn’t always exactly right, but it’s still worth having a look before planning a picnic. For someone in a field in which modelling is not part of training and understanding, basing life-and-death decision-making on forecasts known to be imperfect, is strongly counter-inutitive.
This is why I’ve chosen to take a moment to write this. We view problems, including significant problems, through the lenses of our own biases. People of immense intelligence, wisdom and understanding still have biases. Education and intellectual engagement can confirm biases and create new ones. It is those biases which make some people suggest that taking counter-intuitive action like creating an artificially-induced recession with no clear idea how to end such a recession, and doing so based on epidemiologists’ modelling; is madness.
Looking past our biases to understand our potential futures requires us to use intellectual structure. Moving ourselves towards the post-COVID19 future requires simple structures like imposing intellectual diversity on planning and decision-making; and more complex structures like futures technique. Without stripping away those lenses that bias our perception, we aren’t safe to operate complex machinery like a trolley, a business or a government.