After a year of start-and-stop public-health measures, more often guided by intuition than by science, studies are confirming what economists long suspected: the Covid-19 lockdowns were an expensive, unnecessary failure, based on models that overestimated the number of cases and deaths because they failed to account for individual responses to the pandemic.
Epidemiologists viewed lockdowns as the logical response to a new virus to which humans lacked immunity and that could overwhelm hospitals and cause many deaths. Yet health economists, following seminal work by Tomas Philipson, have long understood that people respond to incentives and alter their behaviors to avoid the risks and costs of infectious diseases. Epidemiologists failed to account for these voluntary changes in assessing what would happen without a lockdown.
The influential Imperial College of London model was typical. In March 2020, it predicted exponential growth of Covid cases that would overwhelm ICU bed capacity by early April and cause 2.2 million U.S. deaths by July. The authors recommended prolonged lockdowns until vaccines became available.
The model grossly overpredicted deaths because of critical errors, including an unrealistically high infection-fatality rate. Most important, its predictions were based on the “unlikely” scenario that there would be no changes in individual behaviors. The model used a reproduction number, or Rt—the average number of secondary infections that each infected person produces in a susceptible population—that was too high and, contrary to standard epidemiological practice, did not vary over time. In fact, Rt declines as people voluntarily avoid contact with others and as the number of recovered people no longer susceptible to infection grows.
The Imperial College model also assumed that hospital and ICU capacity was fixed and unchangeable. But hospitals voluntarily adapted to increasing Covid hospitalizations by limiting their elective procedures and redirecting assets to increase capacity even without government direction. Instances of U.S. hospitals reaching, or exceeding, capacity were rare.
Other businesses also made adjustments. Employers had incentives to limit workplace infections in order to reduce absenteeism, lower insurance costs, and enhance their reputation as safe places to work and shop. University of Chicago economist Casey Mulligan found that private companies voluntarily implemented infection-prevention measures that lowered workplace Covid-19 transmission to levels below household rates.
Failing to account for voluntary actions overstated the risks of the pandemic, creating a counterfactual that would never occur. Moreover, it overstated the benefits of a lockdown, attributing entirely to mandates the improvements that were actually a combination of voluntary responses and responses to mandates.
Another widely cited Imperial College paper from June 2020 illustrated this mistake by attributing decreased European Covid-19 deaths entirely to lockdowns. Yet, as the authors acknowledged, “We do not account for changes in behaviour; in reality, even in the absence of government interventions we would expect Rt to decrease and therefore would overestimate deaths in the no-intervention model.”
Indeed, changes in individual behaviors generally precede government actions and can have a more significant impact. An early study of mobility data found that people had already started to reduce time outside their homes before the government implemented restrictions. In another study, the growth rate in Covid deaths across 23 countries and all U.S. states fell from a wide range of initially high levels to nearly zero in 20 to 30 days in each region, regardless of differences in the type or degree of lockdown imposed. Canadian economist Douglas Allen reviewed nearly 20 studies that distinguish between voluntary and mandated lockdown effects. All found that lockdowns had only marginal effects and that voluntary changes in behavior explain most of the changes in cases and deaths.
Read the full article at City Journal.