The Neil Ferguson case shows the limits of science in COVID-19
CoinDesk expert Nic Carter is a partner at Castle Island Ventures, a venture capital fund based in Cambridge, Mass. Focus on public blockchains. He is also the co-founder of Coin Metrics, a blockchain analysis startup.
A dramatic storyline in the COVID-19 saga is the sad story of Neil Ferguson.
The English epidemiologist (unrelated to historians, lovely people) emerged in March with his landmark model for Imperial College London, predicting 250,000 deaths in the UK and affecting Lockout policy in the United States and abroad.
Very quickly, he became a typical figure for a professional scientific base. His star grew once it emerged that he was infected by the virus. The locked-in public saw him as a form similar to Bruce Banner, a sick scientist suffering from his truth.
But it wasn't long until we failed, the glasses-wearing hero fell into turmoil.
First, he revealed that his favorite model was a mess of undocumented spaghetti code, raising eyebrows among several people in the scientific community who were trying to copy and test the results of brother. Later, it became clear that his prognosis was too pessimistic, even for the UK that was heavily affected. The public began to sour over his model and the strict locking rules of it. The criticism began to pile up. And then, the worst of all: he committed an unforgivable violation by breaking the door lock for a rendezvous with a married woman.
This turned him into a perfect scapegoat. An uncountable member of the policy-making elite, making rules from above, bold enough to violate his own lock policy - for an equally tryst? You can hardly think of a better story to satisfy the locked community's desire for catharsis.
On its side, his sacrifice has been devalued, as tens of thousands of people march through London in areas close to only a mask in sight. But Ferguson's dismissal was never a public defense. It's about extracting a pound of meat from policy elites, as a revenge of sorts to lock down the public. We lost our jobs: what about you? That skin in the game.
Now in the postscript of his career, the National Journal asked, Why has anyone ever heard of this guy? This is a more interesting question than it may appear. Indeed, if you look at it, his track record is decided to mix. According to the Telegraph, he warned in 2001 that up to 150,000 people could die from mad cow disease, a claim that resulted in the destruction of 6 million cattle. In the end, only 200 British died. His logical worst case scenario is prevention of swine flu in 2009, which left 65,000 people dead in the UK. The number of deaths is 457. In 2005, he predicts that the number of deaths from influenza will be 200 million globally. Last death: 282.
Now, all these predictions are obviously very broad by some degree of magnitude. In this context, his rise to the echo on the grounds of British public health policy beggars of faith. How to explain this clear puzzle? I have confirmed that there is another explanation. Perhaps the professor who taught the pessimistic predictions is really the problem.
Imagine for a moment that science really is not exactly as it seems. Now entertain yourself with the idea that the role of epidemiologists may not really make accurate predictions about diseases as they progress through society. That seems to be largely impossible to know anyway. Instead, they act as a kind of social immune response, reminding policymakers that we must act now, even if the numbers themselves are faint. You might even argue that societies informed by overly pessimistic public health experts tend to do better, in the long run, because disproportionate paranoia about the pathogen is more suited to the village. their obesity.
With that in mind, a different way of reading history appears. Anointed Fraud Society, whose task is to ring an alarm about a pandemic, wailing for decades. He stands out because the cost of complying with his prescriptions is relatively low, and is not borne by the public. And far from being punished for his predictions, he has rewarded. In the end, Mr. Elephant took on the personal burden of taking risks and acting as a kind of policy white blood cell.
And then one day, a big event happened, the 100 year pandemic that he was waiting for. His prediction, as usual, is pessimistic: we must act now or many will die. This is the indifference of his career; His opportunity to help society fight a real public health disaster. But this time, things were different. The enormous cost that his model demands of society causes revenge. His unreadable code became a public concern. Suddenly, his quiet, comfortable life against the plague was broadcast in the newspaper. He was exterminated professionally and personally. A great pandemic means that his vindication ultimately becomes his disjointed object.
This raises some nasty questions. Could it be any different? Can we really expect inaccurate predictions related to epidemiology to accurately model the trajectory of a virus in an information-poor environment? Or do we instead choose pessimists, because that's their role in society?
Why was his pessimistic forecasts being forgiven, when he paid the final price for this? Are reprimands directed at Professor Ferguson as a response proportional to a poor prediction, or rather they stem from more evil requests to repent from a fed up public with deterrence ?
In the final analysis, the depth of wrath shows how scandalous the public may become when trusted organizations are revealed to be less reliable than expected. Combining humility of his earlier predictions with the fact that epidemiologists in general cannot predict the trajectory of the disease with any credibility, and can put forth that epidemiology, As it is done today, it is possible that a pseudo-scientific organization seems to have more in common with augury than biology.
In this context, Ferguson's legacy may perhaps be restored somewhat. Instead of being a case of an uncountable scientist running amok, instead, what happened might have been socially reprimanded for a theory of excessive precision - with the Professor Ferguson's career.