Fifteen years ago, writers schooled in computer science began to imagine various totalitarian schemes for pandemic control. Experienced public health officials in 2006 warned that this would lead to disaster. Donald Henderson, for example, went through the whole list of possible restrictions, shooting them down one by one.
Still, a decade and a half later, governments all over the world tried lockdowns anyway. And sure enough, since April of 2020, scholars have observed that these lockdown policies haven’t worked. The politicians preached, the cops enforced, citizens shamed each other, and businesses and schools did their best to comply with all the strictures. But the virus kept going with seeming disregard for all these antics.
Neither oceans of sanitizer, nor towers of plexiglass, nor covered mouths and noses, nor crowd avoidance, nor the seeming magic of six feet of distance, nor even mandated injections, caused the virus to go away or otherwise be suppressed.
The evidence is in. Restrictions are not associated with any particular set of virus mitigation goals. Forty studies have shown no connection between the policy (egregious violations of human liberty) and the intended outcomes (diminishing the overall disease impact of the pathogen).
You can forget about “causal inference” here because there is an absence of correlation of policy and outcomes at all. You can do a deeper dive and find 400 studies showing that the impositions of basic freedoms did not achieve the intended result but instead produced terrible public-health outcomes.
The two years of the hell into which hundreds of governments simultaneously plunged the globe achieved nothing but economic, social, and cultural destruction. Very obviously, this realization is shocking, and suggests a crying need for a reassessment of the power and influence of the people who did this.
This reassessment is happening now, all over the world.
A major frustration for those of us who have denounced lockdowns (which goes by many names and takes many forms) is that these studies have not exactly rocked the headlines. Indeed, they have been buried for the better part of two years.
Among the ignored studies was a December 2020 examination of light and voluntary measures (discouraging large gatherings, isolating the sick, generally being careful) vs. heavy and forced measures. This piece by Bendavid et al. observes some effects on spread from light measures but nothing statistically significant from heavy measures such as stay-at-home (or shelter-in-place) orders.
We do not question the role of all public health interventions, or of coordinated communications about the epidemic, but we fail to find an additional benefit of stay- at-home orders and business closures. The data cannot fully exclude the possibility of some benefits. However, even if they exist, these benefits may not match the numerous harms of these aggressive measures. More targeted public health interventions that more effectively reduce transmissions may be important for future epidemic control without the harms of highly restrictive measures.
The most recent meta-analysis from Johns Hopkins University (Jonas Herby of the Center for Political Studies in Copenhagen, Denmark, Lars Jonung of Lund University, and Steve Hanke of Johns Hopkins) seems to have achieved some measure of media attention. It focuses in particular on the effects of heavy interventions on mortality, finding little to no relationship between policies and severe disease outcomes.
The attention given to this meta-analysis seems to have annoyed the small cabal of academics who still defend lockdowns. A website called HealthFeedBack blasted the methods of the study while citing biased sources and not seriously grappling with the results. This lame effort has been thoroughly smashed by Phil Magness.
Also seeking to reverse the bad press against lockdowns, the Science Media Centre, a project that appears mostly funded by The Wellcome Trust (Britain’s major funding source for epidemiological studies), published a rebuttal of this paper by top lockdown proponents.
Among the comments were those of Oxford’s Seth Flaxman, a major figure in this realm, who is not trained in biological science or medicine but computer science with a specialization in machine learning. And yet it has been his work that has most often cited in defense of the idea that lockdowns achieved some good.
In opposition to the JHU study, Flaxman writes:
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.
See how this rhetoric works? If you question his claim, you are not a scientist; you are denying the science!
These sentences are surely penned out of frustration. The first time in modern history or perhaps all of history when nearly all governments undertook “ordering people to stay home” (which amounts to a universal quarantine) to “decrease disease transmission” was in 2020.
To say that this is not controversial is ridiculous, since such policies had never before been attempted on this scale. Such a policy is not at all like an established causal claim (smoking increases cancer risk) nor a mere empirical observation (the earth is round). It is subject to verification.
There are plenty of reasons one might expect disease transmission to be higher in enclosed spaces with sustained close contact, such as homes, versus shops or even well-ventilated concert settings. As Henderson himself said, it could result in putting healthy non-infected people in close settings with infected people, worsening disease spread.
Indeed, by December of 2020, the governor’s office of New York found that “contact tracing data shows 70 percent of new COVID-19 cases originate from households and small gatherings.” It was also true with New York hospitalization: two thirds of them had contracted Covid at home.
“They’re not working; they’re not traveling,” Cuomo said of these recently hospitalized coronavirus patients. “We were thinking that maybe we were going to find a higher percent of essential employees who were getting sick because they were going to work — that these may be nurses, doctors, transit workers. That’s not the case. They were predominantly at home.”
That Flaxman would still claim otherwise after all experience shows that he is not observing reality but inventing dogma from his own intuition. Flaxman might say that he is sure that transmission might have been higher had people not been ordered to stay home, and there might be settings in which that is true, but he is in no position to elevate this claim to the status of “the earth is round.”
In addition, even under ideal conditions, reduction in disease transmission might only be short-term, kicking the can down the road. A glance at the wild infection increases of Winter 2021 suggests that. The orders might result in worse outcomes overall, due to all that such an order implies for people’s lives. Turning people’s homes into their own jails, in other words, has a downside for the quality of life. And surely that must factor into any social welfare analysis of pandemic policies.
Finally, it is not possible to order everyone to stay home, not even for a day or two. The groceries have to get to the store or be delivered to homes and apartments. People have to staff the hospitals. The electrical plants still need staff. Cops still have to be on the beat. There is literally no option available to “shut down” society in real life as versus in computer models.
Stay-at-home orders in real life become a class-protection scheme to keep high-end laptop professionals shielded from the virus while imposing the burden of exposure on people who have no option but to be out and about. In other words, the working classes are effectively forced to bear the burden of herd immunity, while the rich and financially secure stay safe and wait for the pandemic to pass.
For example, early in the pandemic, the messaging of the New York Times was to instruct its readers to stay home and get their groceries delivered. The paper knows its reader base well: it did not suggest any of them actually deliver groceries! As Sunetra Gupta says, “Lockdowns are a luxury of the affluent.”
And what, in the end, is the point of the stay-home orders? For a widespread virus such as this one, everyone will eventually meet the virus anyway. Only once the winter wave of 2021 finally swept the Zoom class did we start to see a shift in media messaging that 1) there is no shame in sickness, and 2) perhaps we need to start relaxing these restrictions.
The dogma that ordering people to stay home – for how long? – always reduces the spread comes not from evidence but from Flaxman-style modeling plus a remarkable capacity to ignore reality.
Lockdown policies are easily marketed to political players who might get a power rush from the exercise. But, in the end, Henderson’s prediction was correct: these interventions turned a manageable pandemic into a catastrophe.
It’s a sure bet, however, that lockdown proponents will be in denial at least for another decade.