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Scientists criticize flaws in study that found lockdowns do little to reduce COVID deaths
The new paper, drafted by three economists, does not come from Johns Hopkins’ Coronavirus Resource Center
Author of the article:
Publishing date:
Feb 04, 2022 • Last Updated 23 hours ago • 4 minute read
Following a Johns Hopkins University study showing that lockdowns only curbed COVID deaths by 0.2 per cent, some scientists are criticizing the report as fundamentally flawed.
“Smoking causes cancer, the earth is round, and ordering people to stay at home … decreases disease transmission. A study purporting to prove the opposite is almost certain to be fundamentally flawed,” reads a critique by the University of Oxford’s Seth Flaxman, the lead author on a 2020 study which estimated that lockdowns had likely saved up to three million lives across Europe.
The Johns Hopkins paper in question is a pre-print meta-analysis of 34 prior studies examining the link between lockdowns and COVID mortality. Its authors ultimately conclude that lockdowns have “little to no public health effects” and should be “rejected out of hand as a pandemic policy instrument.”
Flaxman was among four prominent public health researchers who criticized the study in a Thursday post published by the Science Media Centre, a U.K. non-profit that works as a conduit between scientists and the media.
One of the other critiques was drafted by Neil Ferguson, an epidemiologist at the U.K.’s Imperial College London whose early modelling on COVID-19 was influential in driving the first major waves of pandemic lockdowns.
The U.K. had initially intended minor interventions on COVID-19, until persuaded otherwise by research from Ferguson’s COVID-19 Response Team, which claimed that a hands-off strategy could yield “hundreds of thousands of deaths.”
“Suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members,” said the March 2020 paper.
Throughout the pandemic, most COVID research out of Johns Hopkins University has typically come from its Coronavirus Resource Center, an initiative run out the university’s world-renowned medical school.
But the new paper, which was drafted by three economists, comes out of the university’s unaffiliated Krieger School of Arts and Sciences.
The economists — who were led by Denmark’s Jonas Herby — only sought data on COVID mortality, and ignored the effects of pandemic strictures on other factors such as hospitalizations or overall case rates. They also excluded any study whose accounting of lives saved was based on forecasts.
Most notably, this included the aforementioned Flaxman study which calculated that lockdowns saved three million European lives (that study also counted Ferguson as a co-author).
As the Johns Hopkins authors wrote, the Flaxman study assumed the “pandemic would follow an epidemiological curve unless countries locked down.” In doing so, they argue, the study took the view that “lockdowns are the only thing that matters” and ignored peripheral factors such as seasonal changes.
One of Ferguson’s primary criticisms of the Johns Hopkins study was that it painted the term “lockdown” with too broad a brush.
The Johns Hopkins study defined a lockdown as “the imposition of at least one compulsory, non-pharmaceutical intervention.” Under this metric, a country whose only COVID stricture is a five-day mandatory quarantine is treated exactly the same as a country experiencing curfews and blanket closures on public venues.
A theme taken up by all the critics in the Science Media Centre post was that the Johns Hopkins meta-analysis failed to account for instances in which a lockdown may have arrested the growth rate of deaths, if not the raw number of deaths themselves. “Many countries locked down before seeing exponential growth and therefore saw no reduction in deaths,” wrote Samir Bhatt, an Imperial College London statistician who was directly involved with the COVID-19 response in New York State.
A report in Forbes wrote that all three authors of the Johns Hopkins paper are definitively of the “free market” bent. Herby works for the libertarian-leaning Center for Political Studies in Copenhagen.
Easily the most famous author is Steve Hanke, a renowned currency researcher who has certainly made no secret of his opinion on lockdowns. Just last week, he posted a cartoon to Twitter showing a semi-truck about to crush an effigy of Prime Minister Justin Trudeau dressed up as Adolf Hitler.
“Trudeau’s political overreach and endless lockdowns have pushed the Canadian public to the boiling point,” he wrote.
The Johns Hopkins paper has thus far received minimal mainstream media attention, and has been cited mostly by right-leaning outlets such as the Daily Mail, Fox News and the National Review.
Lockdowns, school closures and limiting gatherings only reduced COVID mortality by 0.2% at ‘enormous economic and social costs’, study finds
- Meta-analysis of 24 studies found Covid lockdown restrictions caused just 0.2% reduction in virus deaths
- Economists who carried out review said border closures had virtually zero effect on Covid mortality (-0.1%)
- However, researchers found closing nonessential shops was most effective intervention, causing 10.6% fall
By Connor Boyd Deputy Health Editor For Mailonline and Gina Martinez For Dailymail.Com
Published: 07:15 GMT, 2 February 2022 | Updated: 17:12 GMT, 2 February 2022
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A preprint, an unpublished non peer reviewed study posted on the John Hopkins Krieger School of Arts and Sciences website, has looked at the impact of lockdowns.
Prof Neil Ferguson, Director of the MRC Centre for Global Infectious Disease Analysis, Jameel Institute, Imperial College London, said:
“This report on the effect of “lockdowns” does not significantly advance our understanding of the relative effectiveness of the plethora of public health measures adopted by different countries to limit COVID-19 transmission. First, the policies which comprised “lockdown” varied dramatically between countries, meaning defining the term is problematic. In their new report, Herby et al appear to define lockdown as imposition of one or more mandatory non-pharmaceutical interventions (NPIs); by that definition, the UK has been in permanent lockdown since 16th of March 2021, and remains in lockdown – given it remain compulsory for people with diagnosed COVID-19 to self-isolate for at least 5 days.
“A second and more important issue is that the statistical methods used to estimate the impact of NPIs using observational data need to be appropriate. Such interventions are intended to reduce contact rates between individuals in a population, so their primary impact, if effective, is on transmission rates. Impacts on hospitalisation and mortality are delayed, in some cases by several weeks. In addition, such measures were generally introduced (or intensified) during periods where governments saw rapidly growing hospitalisations and deaths. Hence mortality immediately following the introduction of lockdowns is generally substantially higher than before. Neither is lockdown a single event as some of the studies feeding into this meta-analysis assume; the duration of the intervention needs to be accounted for when assessing its impact.
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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 considerationin 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. “
Prof David Paton, Chair of Industrial Economics, Nottingham University Business School, said:
“First the paper is not yet peer-reviewed. It looks to be of good quality so I suspect it will end up in a peer-reviewed journal but obviously results need to be interpreted with that caveat.
“Meta analysis is becoming a bit more common in social sciences. There is a whole literature on pros & cons of that approach, e.g. can be difficult to combine studies with quite different measures & methodologies. This is a bit tricker in the social sciences than when dealing with RCTs in the medical field. However, the authors do start with a more standard systematic literature review before going on to the MA.
“Both parts of the paper (systematic review and the meta analysis) make a significant contribution to our understanding of lockdown effects.
“Key to a systematic review like this are the sets of search & exclusion criteria. The paper is very transparent about this which is good. They focus on difference-in-difference empirical studies. i.e. they look at papers which compare the impact of an intervention on mortality by looking before & after, but relative to other areas which did not have the intervention. As a result, modelling studies (like the well-known Flaxman Nature paper) are excluded. That is not controversial. More marginal in my view is their exclusion of synthetic control method (SCM) papers. Some of these paper find a significant impact of NPIs on mortality so including them might have led to somewhat higher average mortality effects. The paper gives a robust defence of their exclusion, but I think you would get people on both sides of that debate.
https://www.sciencemediacentre.org/expert-reaction-to-a-preprint-looking-at-the-impact-of-lockdowns-as-posted-on-the-john-hopkins-krieger-school-of-arts-and-sciences-website/
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