Let’s discuss the efficacy of lockdowns.
Almost immediately after COVID-19 first rooted and spread in America, debates over whether locking down local and state economies began splitting along partisan lines. The left generally supported business closures and stay-at-home orders to protect lives at all cost; the right was slower to adopt such severe restrictions in favor of balancing economic and health outcomes.
Initially, experts and modelers suggested the death toll would be catastrophic if areas didn’t lock down. Too rapid an increase in cases could overwhelm hospital systems, and so the initial strategy was not to stop the virus but to slow the spread.
This seems like common sense: Separate people so they don’t infect one another.
Researchers later followed up with additional articles “proving” that they were right using further projections, though they acknowledge the difficulty in distinguishing between variables that impacted virus spread.
A June study in the National Center for Biotechnical Information explains, “This study offers initial evidence that the COVID-19 pandemic can be suppressed by a lockdown. In addition, other parameters such as demographic of population, density of populations, the parameters of weather, economy, infrastructure of health care systems may be considered in the studies considering that it may be effective on COVID-19 pandemic.”
Liberal politicians and the media, bracing for every worst-case scenario, leaned into the shutdowns, following the science and the best advice of health experts. Multiple peer-reviewed studies and articles have supported this position.
But now, seven months into the pandemic, the landscape has changed.
Where most of the simulations and studies supporting lockdown efforts relied on the best available testimony by infectious disease experts, tracking the daily spread of COVID-19 through various lockdown and reopening measures has provided empirical data.
Despite modelers’ predictions and protestations, such data indicates surprisingly little correlation between lockdowns and flattening the COVID-19 curve, according to a variety of researchers.
In many cases, states that began instituting shutdown measures in the spring were either already experiencing a slowdown in spread or there was no significant drop in the rate of transmission. Some states that did not institute lockdown orders also saw slowdowns in spread. This is likely due to individuals deciding to socially distance and mask up as the public learned more about the virus.
At least one study posted to the open access journal EClinicalMedicine argued that a country’s level of obesity and GDP was a far better predictor of COVID-19 spread than whether an area locked down.
Still, the lockdowns weren’t ill-advised. State leaders were acting on the best available evidence and advice, and more than 210,000 Americans have died due to the coronavirus to date.
But at this point in the battle against the pandemic, it’s time to rely more heavily on actual data than statistical models, both of which predict escalating fatalities by the end of the year if the public fails to maintain vigilance.
Were there no cost to locking down, it would be an obvious choice should the virus spike in a second wave. However, the economic fallout from initial shutdowns demands careful scrutiny of whether the lockdowns impacted the virus in a statistically significant way.
There is a difference between estimations and hard data.
If lockdowns had been effective, then the data would show that the projections were correct at this point, and they do not. It’s time to acknowledge that fact.
