Before mid-March, COVID-19 was an overseas problem to most Canadians. The emphasis was on returning Canadians stuck in China, and there was a single COVID-19 death in Canada, a BC man in his eighties with underlying health issues.
Then, suddenly, the world changed. Professor Neil Ferguson of Imperial College London, dubbed “Professor Lockdown,” released a series of models that predicted up to 326,000 Canadians would die of COVID-19 unless we radically shut down person-to-person contact for up to 18 months. Politicians panicked, locking down essentially the entire Canadian economy and shoving over six million Canadians out of their livelihoods and onto emergency benefits.
Now, two months later, experts have uncovered enormous flaws in Ferguson’s predictions. The model gives different results depending on what kind of computer it runs on. The underlying code is largely undocumented, making it unverifiable, and is riddled with amateur errors that could make it completely meaningless.
Moreover, Professor Ferguson has a long history of vastly over-predicting deaths. In 2002, he predicted up to 150,000 deaths from CJD (“Mad cow disease”)—55 times the actual death toll of 2,704. In 2005, he predicted bird flu could kill up to 200 million people. The actual death toll: 455.
Most dramatic is those countries that ignored Professor Lockdown and left even restaurants and bars open and packed into the night. While COVID-19 isn’t over, the difference is staggering. For Sweden, he predicted up to 85,000 deaths; there had been 3,300 by May 12. For South Korea, he predicted up to 381,000 deaths, compared to some 250 by May 12. In Taiwan, he predicted up to 212,000 deaths, compared to just seven.
Even Ferguson’s earliest-lockdown prediction for Canada was 46,000 deaths. We had 5,129 by May 12, compared to 3,500 for a typical flu season. We wouldn’t have dreamed of throwing six million Canadians onto public assistance for a bad flu season.
We can see the results, as hospitals across Canada lay off nurses and close emergency rooms for lack of patients. Even in hard-hit Quebec, hospitals are already showing spare unused capacity. Leaving us to wonder if we’ve made a catastrophic overreaction to, it turns out, a questionable prediction.
Any study used to justify measures that destroy millions of Canadians’ livelihoods and erode their civil liberties must at least be based on the very highest level of scientific rigour. From epidemics to carbon taxes, reliance on shoddy research must end, not only to protect Canadians from half-baked schemes, but so that Canadians can once again trust policy-makers and the experts who advise them.
If this entire lockdown was some tragic mistake based on a single dodgy prediction, we must make sure that it never happens again.
Peter St. Onge is a Senior Fellow at the MEI and the author of “The Flawed COVID-19 Model That Locked Down Canada.” The views reflected in this op-ed are his own.