As he is careful to point out, Professor Michael Levitt is not an epidemiologist. He’s Professor of Structural Biology at the Stanford School of Medicine, and winner of the 2013 Nobel Prize for Chemistry for “the development of multiscale models for complex chemical systems.” With a purely statistical perspective, he has been playing close attention to the Covid-19 pandemic since January, when most of us were not even aware of it. He first spoke out in early February, when through analysing the numbers of cases and deaths in Hubei province he predicted with remarkable accuracy that the epidemic in that province would top out at around 3,250 deaths. In this interview with Freddie Sayers, Executive Editor of UnHerd, Professor Levitt explains why he thinks indiscriminate lockdown measures as “a huge mistake,” and advocates a “smart lockdown” policy, focused on more effective measures, focused on protecting elderly people.

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