Lockdowns Are Needed, So Let's Make Them Work

With several promising vaccines now in the pipeline, we're moving into the “hanging on” stage of the coronavirus pandemic: until vaccines can be deployed en masse. The U.K. became the first Western country to approve a Covid-19 shot, but the rollout won’t be immediate for everyone. Keeping the epidemic in check until then — most likely in the next few months — will demand more mask wearing, testing and tracing, and, almost certainly, curfews and lockdowns of some variety. Many European nations have returned to those conditions (or finally enacted them), as have a number of cities and states in the U.S.

Even so, we’ve grown increasingly aware of the social and psychological costs of lockdowns. They clearly work to bring cases down yet put stress on almost everyone, crushing small businesses, and depriving children of education and social connection. Perhaps not surprisingly, we’re seeing rising lockdown resistance.

Yet there may be another path that offers the benefits of lockdown while avoiding many of the costs. Some scientists and engineers suggest that the highest costs of lockdowns actually come from their imposition over long periods and the inherent uncertainties behind their planning. Better, they argue, would be repeated, short-term lockdowns coming on a predictable weekly basis. Done correctly, such an approach could keep infection numbers in check while also preserving economic activity and personal freedoms.

It's an idea that deserves attention from governments everywhere, including the incoming Joe Biden administration in the U.S., which faces the most infections of any nation.

One paradoxical weakness of current control measures, these scientists told me in a conference call, is the attempt to fine-tune policy with the latest epidemiologic data, including geographic estimates of R numbers. It's a natural desire, of course, but runs counter to good engineering practice, because such control strategies often lead to unexpected outcomes due to unavoidable data uncertainties and delays in policy implementation.

This is especially true, control engineers Thomas Parisini and Robert Shorten of the Imperial College London explained, given the natural exponential growth of an epidemic. Engineers have learned that better control actually results from using less data and relying on rapid switching — as happens, for example, in modern automobile anti-lock braking systems. Here a computer switches the brakes rapidly on and off, which prevents the brakes from locking and causing skidding. The computer then only gradually adjusts the pattern of switching as the car slows, discarding lots of precise data in favor of a smoother average.

A similar approach to managing the pandemic wouldn't try to devise optimal lockdown timing and duration based on crunching the best data, but would employ brief, repeated lockdowns — two days of mostly unrestricted social and economic activity each week, say, Monday and Tuesday, followed by lockdown for five days. Most people could work outside the home for two days, then, if possible, work from home for three days, before the weekend.

In a series of mathematical analyses, backed by epidemiological simulations, Parisini and colleagues have demonstrated that this policy would enable authorities, by choosing the lockdown and non-lockdown intervals correctly, to ensure infection numbers systematically go down while also giving people and companies the ability to plan in advance, and so be more active economically and socially. This policy could be adjusted slowly in response to long-term trends, such as increasing or decreasing infection levels.

This idea would also eliminate another increasingly despised aspect of pandemic policy: the constant changes in the rules due to recent fluctuations in the data. Predictability would likely make such a strategy easier for people to accept — and therefore more sustainable. Last time lockdown was imposed in London, huge crowds thronged to the pubs just before closing. The move came with little advance notice, and pubs were about to close for four weeks. Would people show the same panic if the lockdown interval was known in advance, was only lasting for five days, and had already been experienced many times before?

This research has been peer-reviewed and accepted for publication in a scientific journal. But the researchers — part of a larger research project — emphasize they aren't epidemiologists; they’re engineers with a knowledge of the advantages but also the limitations of feedback in complex systems. That said, epidemiologists have relied on similar cycling strategies before — for example, in controlling seasonally recurring infectious diseases such as influenza and measles. Moreover, since the research team first proposed this approach in a theoretical paper earlier this year, a number of other research groups have developed similar ideas and explored variations, such as a strategy that keeps half the population active while the other locks down. 

In the U.S., the Biden administration’s plans remain unclear. One Biden Covid adviser has discussed a more aggressive four- to six-week lockdown, perhaps justified by skyrocketing numbers and the lack of systematic Covid policy to this point. But after this period, vaccines may still be months away for the general public, and an intermittent policy may be more effective.

“I think this approach could be valuable,” professor Meagan Fitzpatrick of the University of Maryland School of Medicine told me, “especially prior to vaccine rollout. We know that cases will escalate during ‘reopening,’ and we should plan around it. An enormous part of the mental and economic toll comes from the uncertainty facing families and businesses.”

Of course, the idea needs more testing, especially in the real world. Will people accept the more predictable approach? Could unexpected human reactions somehow spoil the plan? We'll never know until the plan is tested, preferably in slightly different ways in different regions.

Ideas don't normally flow very well between engineering and epidemiology, but we need all the good ideas we can find. “Our intention,” says Shorten, “is simply to help make the community aware of the potential of such policies.”

The average number of further infections that follows from one new infection.

This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.

Mark Buchanan, a physicist and science writer, is the author of the book "Forecast: What Physics, Meteorology and the Natural Sciences Can Teach Us About Economics."

©2020 Bloomberg L.P.

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