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Stay-at-home orders can reduce COVID-19 deaths, though the effectiveness of these measures can vary greatly from one location to another due to many factors. Jose Sarmento Matos/Bloomberg/Getty Images
  • A number of studies have shown that stay-at-home orders have helped slow the spread of coronavirus during the pandemic.
  • However, the effectiveness can vary greatly from one area to another due to many factors such as compliance.
  • Some studies have found that while local stay-at-home orders can be effective, their effectiveness diminishes over time as people begin to feel “lockdown fatigue.”

A recent preprint that combines data from several other studies suggests that lockdowns early in the pandemic didn’t reduce COVID-19 deaths.

However, experts say this nonpeer-reviewed paper has serious flaws that limit the conclusions being made by the authors.

“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,” Neil Ferguson, PhD, an epidemiologist and professor of mathematical biology at Imperial College London, said in a statement.

The preprint was published on the website of the Johns Hopkins Krieger School of Arts and Sciences.

All three of the paper’s authors are economists — not medical doctors, epidemiologists, or public health experts — and only one is from Johns Hopkins University.

The paper is a meta-analysis, which combines the results of independent studies to get a better sense of the overall effect of an intervention such as a medication, other treatment, or a public health response.

This type of analysis involves more than just combining data from separate studies. Researchers use statistical methods to merge the findings while considering differences in how those studies were carried out.

In addition, a well-designed meta-analysis has to use the best statistical methods and needs to include all of the appropriate studies in the analysis.

Seth Flaxman, PhD, a statistician also at Imperial College London, said in the same statement that the authors of the preprint did not do the latter.

“They systematically excluded from consideration any study based on the science of disease transmission,” he said, “meaning that the only studies looked at in the analysis are studies using the methods of economics.”

Gideon Meyerowitz-Katz, an epidemiologist from the University of Wollongong in New South Wales, Australia, agreed.

“The included studies certainly aren’t representative of research as a whole on lockdowns — not even close,” he wrote on Twitter. “Many of the most robust papers on the impact of lockdowns are, by definition, excluded.”

In addition to excluding several important studies, the authors use a definition of “lockdown” that some experts find a little too broad.

“The most inconsistent aspect [of the preprint] is the reinterpreting of what a lockdown is,” Samir Bhatt, DPhil, a professor of statistics and public health at Imperial College London, said in the statement.

The preprint authors define a lockdown as “the imposition of at least one compulsory, non-pharmaceutical intervention,” which includes stay-at-home orders as well as physical distancing, handwashing, and others.

“This would make a mask-wearing policy a lockdown,” said Bhatt.

Many scientists have stopped using “lockdown” because it isn’t a policy, said Bhatt. It is an “umbrella word” for a set of policies designed to slow the community spread of the coronavirus.

So a lockdown in the United States and a lockdown in the United Kingdom would look very different. In fact, a lockdown in one U.S. state would look very different from one in another state.

“All of this adds up to a very weird review paper,” wrote Meyerowitz-Katz on Twitter.

Bhatt also found the preprint concerning because it focused on the early part of the pandemic, even though countries and local governments have been using nonpharmaceutical interventions — including stay-at-home orders — throughout the pandemic.

“[The study] looks at a tiny slice of the pandemic,” he said. “There have been many lockdowns since globally with far better data.”

Other studies — including this one and this one — have looked at later periods during the pandemic. These studies also found that stronger government measures reduced COVID-19 deaths more.

One challenge with estimating the impact of mitigation strategies on COVID-19 deaths is that these measures are intended to slow transmission of the virus. The impact on hospitalizations and deaths comes later.

“Because there’s a lag from infection to death, to see the effect of lockdowns on COVID deaths, we need to wait about two or three weeks,” said Flaxman in the statement.

Ferguson said in the statement that “many studies of the effects of [nonpharmaceutical interventions] fail to recognize this important issue.”

Another thing that researchers have to take into account is that stay-at-home orders are rarely imposed in isolation. They may follow — or occur at the same time as — less restrictive interventions, such as mask policies, capacity restrictions, and school closures.

In an earlier study, Flaxman and Bhatt wrote that it is difficult to “disentangle the individual effect sizes of each intervention” because countries implemented these in “rapid succession.”

“Analysis has been further complicated by the accumulation of immunity — from infection and vaccination — in populations, together with the emergence of new COVID-19 variants,” Ferguson said in the statement.

Other factors that can impact COVID-19 death rates include hospital capacity and the availability of COVID-19 vaccines and treatments, all of which vary widely across countries.

Olga Yakusheva, PhD, an economist in the School of Nursing at the University of Michigan, and her colleagues took some of these issues into account during their study on the benefits and costs of mitigation measures early in the pandemic in the United States.

Their analysis looked at the impact of the “full set of public health measures,” said Yakusheva, which included stay-at-home orders and other measures such as mask policies, physical distancing, and school closures.

However, they didn’t just focus on the impact these measures had on COVID-19 deaths. They also looked at the adverse impact of the economic downturn that occurred as a result of these measures.

Similar research done before has focused on the financial impact of COVID-19 mitigation measures, but Yakusheva and her colleagues estimated the number of deaths that might occur as a result of this economic disruption.

These deaths might result from the loss of a job or income that leads to diminished access to health insurance or the inability to buy essentials such as food or medication — all of which can impact a person’s health.

“The impetus for this paper was to humanize the economic damage,” said Yakusheva, “so we can more effectively use the same language to talk about the costs and the benefits of the lockdown.”

The researchers estimate that during the first 6 months of the pandemic, between 800,000 and 1.7 million lives were saved as a result of these health measures.

“These are the people who would have potentially died from COVID had they not been protected by the strong public health response,” said Yakusheva.

In contrast, they estimate that between 57,000 and 245,000 deaths potentially occurred due to the economic downturn during the first part of 2020.

“When you look at it in terms of lives saved versus lives lost, it does seem that the lockdowns were more protective of human lives in comparison to the economic damage they caused,” said Yakusheva.

In this study, the researchers attempt to address one of the many nuances in the debate over stay-at-home orders — how do you balance the benefits and costs of these kinds of measures?

It’s never as easy as saying lockdowns are “good” or “bad.”

In making public health decisions, scientists and health officials look at the entire body of research to figure out what types of mitigation strategies work best and in what circumstances.

And also, how long these measures should be put in place.

Yogesh Joshi, PhD, an associate professor in the Robert H. Smith School of Business at the University of Maryland, and his colleagues looked at the impact of stay-at-home orders on mobility.

These types of mitigation strategies are intended to slow the spread of the virus by encouraging people to stay home, which reduces their interactions with others.

In Joshi’s study, he and his colleagues found that stay-at-home orders reduced mobility in most countries they looked at.

But after a while, people began moving around more in the community, even though the stay-at-home order continued. One of their analyses showed that on average, by 7 or 8 weeks after the start of the lockdown, mobility was essentially back where it started.

“When lockdowns extend for long periods of time, then the past data shows us that mobility levels start rebounding,” said Joshi.

While they didn’t look specifically at the effectiveness of shorter stay-at-home orders — sometimes called “circuit breakers” — Joshi “speculates that shorter lockdowns should yield higher compliance, in terms of [people] staying at home.”

Health officials can use mobility data to help make decisions about stay-at-home orders.

For example, said Joshi, if people in a community have already voluntarily restricted their movement in response to the high spread of the coronavirus, imposing a stay-at-home order may not have much of an effect.

Officials might also want to emphasize less restrictive mitigation measures first — such as mask policies and business capacity limits — which can be effective when put in place early during a surge.

“Our research finds that lockdowns have an effect, but that effect wears out over time,” said Joshi.

“Further research may be needed to investigate whether countries where lockdowns were repeatedly imposed continue to exhibit the same type of response to lockdowns each time around, or whether there is a wear-out across lockdowns as well,” he added.

Yakusheva emphasized that her paper is just one of many that helps to clarify the benefits and costs of COVID-19 mitigation measures.

“My paper, just as much as anybody else’s paper, is never a final answer to this question,” she said. “It’s a piece of the puzzle, and it should be taken into consideration in the context of all of the other research.”