Dr Seth Flaxman, Associate Professor in the Department of Computer Science, University of Oxford, said:
“Smoking causes cancer, the earth is round, and ordering people to stay at home (the correct definition of lockdown) decreases disease transmission. None of this is controversial among scientists. A study purporting to prove the opposite is almost certain to be fundamentally flawed.
“In this case, a trio of economists have undertaken a meta-analysis of many previous studies. So far so good. But they systematically excluded from consideration any study based on the science of disease transmission, meaning that the only studies looked at in the analysis are studies using the methods of economics. These do not include key facts about disease transmission such as: later lockdowns are less effective than earlier lockdowns, because many people are already infected; lockdowns do not immediately save lives, because there’s a lag from infection to death, so to see the effect of lockdowns on Covid deaths we need to wait about two or three weeks. (This was all known in March 2020 – we discussed it in a paper released that month, and later published in Nature. Our paper is excluded from consideration in this meta-analysis.)
“It’s as if we wanted to know whether smoking causes cancer and so we asked a bunch of new smokers: did you have cancer the day before you started smoking? And what about the day after? If we did this, obviously we’d incorrectly conclude smoking is unrelated to cancer, but we’d be ignoring basic science. The science of diseases and their causes is complex, and it has a lot of surprises for us, but there are appropriate methods to study it, and inappropriate methods. This study intentionally excludes all studies rooted in epidemiology–the science of disease.”
Prof Samir Bhatt, Professor of Statistics and Public Health, Imperial College London:
“I find this paper has flaws and needs to be interpreted very carefully. Two years in, it seems still to focus on the first wave of SARS-COV2 and in a very limited number of countries. The most inconsistent aspect is the reinterpreting of what a lockdown is. The authors define lockdown as “as the imposition of at least one compulsory, non-pharmaceutical intervention”. This would make a mask wearing policy a lockdown. For a meta-analysis using a definition that is at odds with the dictionary definition (a state of isolation or restricted access instituted as a security measure) is strange. The authors then further confuse matters when in Table 7 they revert to the more common definition of lockdown. Many scientists, including myself, quickly moved on from the word “lockdown” as this isn’t really a policy (Brauner et al 2020, and my work in Sharma et al 2021). It’s an umbrella word for a set of strict policies designed to reduce the reproduction number below one and halt the exponential growth of infections. Lockdown in Denmark and Lockdown in the UK are made up of very different individual policies. Aside from issues of definitions there are other issues such as (a) It’s not easy to compare Low and High income countries in terms of the enforcement and adherence of policies, (b) Many countries locked down before seeing exponential growth and therefore saw no reduction in deaths, (c) There are lags – interventions operate on transmission but mortality is indirect and lagged – comparing mortality a month before and after lockdown is likely to have no effect (e.g Bjørnskov 2021a), (d) As i have mentioned it looks at a tiny slice of the pandemic, there have been many lockdowns since globally with far better data, (e) There are many prominent studies that cover the period in question looking at infections included including Brauner et al 2020, Alfano et al 2020, Dye et al 2020, Lai et al 2020, Hsiang et al 2020, Salje et al 2020 etc. The list of such studies is very long and suggests a highly incomplete meta-analysis. “
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Originally Posted by ZahZoo
