I have a piece up at Science Based Medicine responding to criticism of New Zealand’s zero COVID policy by Jay Bhattacharya, an author of the Great Barrington Declaration and an uncompromising critic of COVID restrictions. Here’s the intro:
Bhattacharya’s most compelling argument is that the zero COVID policy led to an increase in non-COVID mortality that substantially offset the COVID deaths the policy averted. If this were true, it would indeed be a powerful criticism of New Zealand’s policy. However, the best available estimates suggest that excess non-COVID mortality in New Zealand was negative during the pandemic – fewer people died than we would have expected based on historical data. New Zealand’s COVID policy appears to have prevented thousands of COVID deaths, with no offsetting increase in non-COVID mortality.
Bhattacharya got this wrong for a simple reason: he did not attempt to compare COVID deaths averted to estimates of excess non-COVID mortality. Instead, he used statistical innuendo to create the impression that the policy backfired. He also seems to have been misled by a chart of excess deaths based on a biased methodology, a mistake that would have become apparent to him if he had bothered to compare excess non-COVID mortality to COVID deaths avoided.
I was puzzled by this claim when I read it. It was immediately clear to me that Bhattacharya erred by not comparing COVID deaths averted to excess non-COVID mortality caused by the zero COVID policy. But things got confusing when I looked at the excess death data; eventually I figured out what was going on.
Worth a read if you’re interested in how empirical claims about policy can go awry; it’s not just garden-of-forking-paths, p-hacking, and file drawer problems that we have all (rightly) become much more aware of.