Imperial College’s death estimates over the years have some things in common: flawed modeling, hair-raising predictions of disaster that missed the mark, and no lessons learned.
The defining event in the history of Western Covid lockdowns occurred on March 16, 2020, with the publication of the now infamous Imperial College London Covid report, which predicted that in the “absence of any control measures or spontaneous changes in individual behaviour,” there would be 510,000 Covid deaths in Great Britain and 2.2 million in the United States. This prediction sent shock waves around the world. The next day, the U.K. media announced that the country was going into lockdown.
The impact of the report was amplified by the U.K’s soft-power machine, the BBC. Its reach has no equal: broadcasting in 42 languages, reaching 468 million people worldwide each week, and efficiently disseminating its message. With the BBC in full cry and the public genuinely alarmed, there was no room for dissent.
A copycat cascade then took hold, with the U.S. and other countries embracing London’s message and policies. The result was a policy based on a defective model that originated at Imperial College under the leadership of Neil Ferguson.
The model’s major flaw is its assumption that people would be unresponsive to the dangers that accompany a pandemic. That behavioral assumption is unrealistic. If people are told they are in danger of catching a potentially lethal disease, most will take action to reduce their exposure. The Imperial team turned the world on its head with fantasy numbers about a scenario that could never materialize.
Before hurrying into panicked policy decisions, U.K. policy-makers should have been aware that Neil Ferguson’s Imperial College team had a history of defective modeling. With minimal effort, policy-makers would have quickly discovered that that team had a track record that makes astrology look respectable.
That dreadful record started with the U.K. foot-and-mouth disease epidemic in 2001, during which the Imperial College modelers persuaded the government to adopt a policy of mass animal slaughter. Their model predicted that daily case incidences would peak at about 420. At the time, the number of incidences had already peaked at just over 50 and was falling. The prediction missed its mark, and as many as 10 million animals, most of which could have been vaccinated, were needlessly killed.
Shortly thereafter, in January 2002, the Imperial team suggested that up to 150,000 people in the U.K. could die from mad cow disease. As it turned out, the total number of U.K. deaths was 178 — another miss for the Imperial team.
Then, in 2005, Neil Ferguson suggested that “up to around 200 million” could die from bird flu globally. He justified this claim by comparing the lethality of bird flu to that of the 1918 Spanish flu outbreak, which killed 40 million. By 2021, bird flu had killed 456 people worldwide, making it Imperial’s biggest miss yet.
Neil Ferguson and his team were back at it again in 2009 when they claimed that 65,000 people could die of swine flu in the U.K. By the end of March 2010, the outbreak had killed fewer than 500 people before petering out. Neil Ferguson’s “reasonable worst case” scenario was over 130 times too high — yet another big miss.
In each case there was the same pattern: flawed modeling, hair-raising predictions of disaster that missed the mark, and no lessons learned. The same mistakes were repeated over and over again and were never challenged by those in authority. Why? Maybe the Imperial College models are ideal fear-generating machines for politicians and governments craving more power. H. L. Mencken put his finger on this phenomenon when he wrote that “the whole aim of practical politics is to keep the populace alarmed (and hence clamorous to be led to safety) by an endless series of hobgoblins, most of them imaginary.”
The Imperial College modeling team should have faced an audit of its models and practices after the foot-and-mouth disease debacle more than 20 years ago. Had that been done, later fiascos might have been avoided. Be that as it may, Imperial should certainly face an audit now, and it should focus on the inadequacies of the team’s models and on how faulty policy recommendations were derived from them.
Governments across the world should also initiate their own public inquiries to draw lessons and address the measures needed to protect their citizens from reckless public-health modeling. Never again should “scientists” armed with flawed models get away with shouting, “Pandemic!” in a theater filled with politicians and bureaucrats eager to grab yet more power.
Steve H. Hanke is a professor of applied economics at the Johns Hopkins University in Baltimore. He is a senior fellow and the director of the Troubled Currencies Project at the Cato Institute in Washington, D.C. Kevin Dowd is professor of finance and economics at Durham University Business School in Durham, England.