Back in September, Donalid Luskin (CIO, TrendMacro) penned an opinion piece in the WSJ regarding uncontrolled experiments of government lockdowns (https://www.wsj.com/articles/the-failed-experiment-of-covid-lockdowns-11599000890):
The lesson is not that lockdowns made the spread of Covid-19 worse—although the raw evidence might suggest that—but that lockdowns probably didn’t help, and opening up didn’t hurt. This defies common sense. In theory, the spread of an infectious disease ought to be controllable by quarantine. Evidently not in practice, though we are aware of no researcher who understands why not.
We’re not the only researchers to have discovered this statistical relationship. We first published a version of these findings in April, around the same time similar findings appeared in these pages. In July, a publication of the Lancet published research that found similar results looking across countries rather than U.S. states. “A longer time prior to implementation of any lockdown was associated with a lower number of detected cases,” the study concludes. Those findings have now been enhanced by sophisticated measures of actual social distancing, and data from the reopening phase.
There are experimental controls that all this research lacks. There are no observable instances in which there were either total lockdowns or no lockdowns at all. But there’s no escaping the evidence that, at minimum, heavy lockdowns were no more effective than light ones, and that opening up a lot was no more harmful than opening up a little. So where’s the science that would justify the heavy lockdowns many public-health officials are still demanding?
With the evidence we now possess, even the most risk-averse and single-minded public-health officials should hesitate before demanding the next lockdown and causing the next economic recession.
Well, science does eventually catch up on these these.
Bendavid et al. (2021) summarize their investigation as follows: The most restrictive non-pharmaceutical interventions (NPIs) for controlling the spread of COVID-19 are mandatory stay-at-home and business closures. Given the consequences of these policies, it is important to assess their effects. We evaluate the effects on epidemic case growth of more restrictive NPIs (mrNPIs), above and beyond those of less restrictive NPIs (lrNPIs).
Their conclusion: While small benefits cannot be excluded, we do not find significant benefits on case growth of more restrictive NPIs. Similar reductions in case growth may be achievable with less restrictive interventions.
Reference
Bendavid, E., Oh, C., Bhattacharya, J., & Ioannidis, J. P. A. (2021). Assessing mandatory stay-at-home and business closure effects on the spread of COVID-19. European Journal of Clinical Investigation, e13484. https://onlinelibrary.wiley.com/doi/epdf/10.1111/eci.13484
Econophysics2020 