“the truth is that lockdown is a luxury, and it’s a luxury that the middle classes are enjoying and higher income countries are enjoying at the expense of the poor, the vulnerable and less developed countries” Sunetra Gupta @FreddieSayers @unherd


Loads of great points

  • COVID on the way out in UK
  • Antibody tests unreliable, don’t show prevalence
  • Infections rates shouldn’t even be reported; dependent on testing
  • R number depends on immunity and thus a red herring
  • Everywhere same curve: up, then gently down (resonant of Michael Levitt’s interview in the same place). Immunity explains better than a load of different explanations for all the countries with different measures.
  • And lockdown is retrogressive, not progressive; it’s dumb to bundle up the anti-lockdown people as on the right (or left I guess). It’s a luxury that the rich can afford and the poor can’t.

“…regardless of government interventions [, after] around a two week exponential growth of cases (and, subsequently, deaths) some kind of break kicks in, and growth starts slowing down. The curve quickly becomes “sub-exponential”.


Freddie Sayers of Unherd interviews Michael Levitt (a Nobel-prize-winning non-epidemiologist) on a purely statistical observations of the pattern of the epidemic. Given that the only way we have of measuring effectiveness of government interventions is statistical, that’s interesting. The fun stuff (epidemiological and statistical) comes in deciding whether the correlation is causal. But there’s been no progress with that, in my opinion; in fact for me it is here that the epidemiological profession has disappointed me – it is at if epidemiology has forgotten everything it ever taught itself about causal inference. Against that background, this is ought to give pause for thought.