https://www.vox.com/future-perfect/2020/3/31/21199874/coronavirus-spanish-flu-social-distancing
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A study of the 1918 Spanish flu pandemic finds that cities with stricter social distancing reaped economic benefits.
For much of the past month, some commentators have defended the effort to promote social distancing, including the near-shutdown of huge swaths of America’s economy, as the lesser of two evils: Yes, asking or forcing people to remain in their homes for as much of the day as possible will slow economic activity, the argument goes. But it’s worth it for the public health benefits of slowing the coronavirus’s spread.
This argument has, naturally, led to a backlash, explained here by my colleague Ezra Klein. Critics — including the president — have argued that the cure is worse than the disease, and mass death from coronavirus is a price we need to be willing to pay to keep the American economy from cratering.
Both these viewpoints obscure an important possibility: The social distancing regime may well be optimal not just from a public health point of view, but from an economic perspective as well.
Economists Sergio Correia, Stephan Luck, and Emil Verner released a working paper (not yet peer-reviewed) last week that makes this argument extremely persuasively. The three analyzed the 1918-1919 flu pandemic in the United States, as the closest (though still not identical) analogue to the current crisis. They compare cities in 1918-’19 that adopted quarantining and social isolation policies earlier to ones that adopted them later.
Their conclusion? “We find that cities that intervened earlier and more aggressively do not perform worse and, if anything, grow faster after the pandemic is over.”
The researchers refer to such social distancing policies as NPIs, or “non-pharmaceutical interventions,” essentially public health interventions not achieved through medication, like quarantines and school and business closures. The key to the paper is their observation that, in theory, NPIs can both decrease economic activity directly, by keeping people in certain jobs from going to work, and increase it indirectly, because it prevents large-scale deaths that would also have a negative impact on the economy.
“While NPIs lower economic activity, they can solve coordination problems associated with fighting disease transmission and mitigate the pandemic-related economic disruption,” they write. In other words, social distancing measures that save lives can also, in the end, soften the economic disruption of a pandemic.
The data here comes from a 2007 paper in the Journal of the American Medical Association, where a group of researchers chronicled what specific policies were put in place between September 8, 1918, and February 22, 1919, by 43 different cities. The most common NPI the JAMA researchers identified was a combination of school closures and bans on public gatherings; 34 of the 43 cities adopted this rule, for an average of four weeks.
Other cities eschewed these policies in favor of mandatory isolation and quarantine procedures: “Typically, individuals diagnosed with influenza were isolated in hospitals or makeshift facilities, while those suspected to have contact with an ill person (but who were not yet ill themselves) were quarantined in their homes with an official placard declaring that location to be under quarantine,” the JAMA authors write, detailing New York City’s approach.
Another 15 cities did both isolation/quarantines and school closures/public gathering bans.
The 2007 paper found a strong association between the number and duration of NPIs and pandemic deaths, with more and longer-lasting NPIs associated with a smaller death toll. Correia, Luck, and Verner, in their new paper, replicate this finding.
But they take it a step further. They study the impact of changes in mortality due to the 1918 pandemic on economic outcomes.
“The increase in mortality from the 1918 pandemic relative to 1917 mortality levels (416 per 100,000) implies a 23 percent fall in manufacturing employment, 1.5 percentage point reduction in manufacturing employment to population, and an 18 percent fall in output,” they conclude. In other words, a big outbreak spelled economic disaster for affected cities.
Then they combined this analysis with an analysis of the effects of NPI policies. They find that the introduction of social distancing policies is associated with more positive outcomes in terms of manufacturing employment and output. Cities with faster introductions of these policies (one standard deviation faster, to be technical) had 4 percent higher employment after the pandemic had passed; ones with longer durations had 6 percent higher employment after the disaster.
The takeaway is clear: These policies not only led to better health outcomes, they in turn led to better economic outcomes. Pandemics are very bad for the economy, and stopping them is good for the economy.
A few notes of caution
It’s important to always approach this kind of study with a degree of skepticism. The 1918 pandemic was not a planned experiment, so researchers’ ability to determine the degree to which the pandemic, or the policies adopted in response to it, affected economic outcomes is always going to be somewhat limited.
The researchers acknowledge that their biggest limitation is the non-randomness of policy adoption by cities. Presumably cities with strict responses to the pandemic were different from cities with laxer responses in ways that went beyond this one incident. Maybe the stricter cities had better public health infrastructure to begin with, for instance, which could exaggerate the estimated effect of social distancing interventions.
The authors argue that because the second and most fatal wave of the 1918 pandemic spread mostly from east to west, geographically, these kinds of dynamics weren’t at play. “Given the timing of the influenza wave, cities that were affected later appeared to have implemented NPIs sooner as they were able to learn from cities that were affected in the early stages of the pandemic,” they note.
The best explanation of differences in policies, then, is how far a city is from the East Coast of the US. They control for a big factor that might affect Western states more (the boom and bust of the agricultural industry as World War I drew to a close) and find few other observable differences between Western cities with strong policies and Eastern policies with weak ones. But the notion that these cities are comparable is a key part of the paper’s research design, and one worth digging into as the paper goes through peer review and revisions.
The economy isn’t everything
The message that there isn’t a trade-off between saving lives and saving the economy is reassuring. If there were such a trade-off, the debate over coronavirus response would be in the realm of pure values: How much money should we be willing to forsake to save a human life? That’s a thorny choice, and finding that we don’t actually have to make it — as this paper suggests — is comforting.
It’s worth emphasizing, though, that if we did have to make that choice, it would still be an easy decision. The lives saved would be worth more.
In another recent white paper, UChicago’s Michael Greenstone and Vishan Nigam estimate the social value of social distancing policies, relative to a baseline where we endure an untrammeled pandemic. To simulate the two scenarios, they rely on the influential Imperial College London model of the coronavirus pandemic — a paper that found that an uncontrolled spread of coronavirus would kill 2.2 million Americans.
Then they throw in an oft-used tool of cost-benefit economic analysis: the value of a statistical life (VSL). Popularized by Vanderbilt economist Kip Viscusi, VSL involves putting a dollar value on a human life by estimating the implicit value that people in a given society place on continuing to live based on their willingness to pay for services that reduce their risk of dying.
Usually, this involves a “revealed preferences” approach. A 2018 paper by Viscusi, for example, used, among other data sources, Bureau of Labor Statistics Census of Fatal Occupational Injuries to measure how much more, in practice, US workers demand to be paid to take jobs that carry a higher risk of death.
Greenstone and Nigam allow VSL to vary with age — understandably, older people are less willing to pay to reduce their odds of death than younger people — but set the average VSL for an American age 18 and over to $11.5 million.
Based on the Imperial College projection that social distancing would save about 1.76 million lives over the next six months, Greenstone and Nigam estimate that the economic value of the policy is $7.9 trillion, larger than the entire US federal budget and greater than a third of GDP. The value is about $60,000 per US household. Even if the Imperial College model is off by 60 percent and the no-social-distancing scenario is less deadly than anticipated, the aggregate benefits are still $3.6 trillion. And this is likely an underestimate that ignores other costs of a large-scale outbreak to society; it focuses solely on mortality benefits.
VSL is sometimes attacked from the left as craven, a reductio ad absurdum of economistic reasoning trampling over everything, including the value of human life itself. But coronavirus helps illustrate how VSL can work in the opposite direction. Human life is so valuable in these terms that social distancing would have to force a 33 percent drop in US GDP before you could start to plausibly argue that the cure is worse than the disease.
That social distancing likely won’t cause a reduction in GDP relative to a scenario where there’s a multimillion-person death toll, as indicated by the 1918 flu paper, makes the case for distancing policies that much stronger.
HENRY KOTULA 
CAMBRIDGE – Aristotle was right. Humans have never been atomized individuals, but rather social beings whose every decision affects other people. And now the COVID-19 pandemic is driving home this fundamental point: each of us is morally responsible for the infection risks we pose to others through our own behavior.
In fact, this pandemic is just one of many collective-action problems facing humankind, including climate change, catastrophic biodiversity loss, antimicrobial resistance, nuclear tensions fueled by escalating geopolitical uncertainty, and even potential threats such as a collision with an asteroid.
As the pandemic has demonstrated, however, it is not these existential dangers, but rather everyday economic activities, that reveal the collective, connected character of modern life beneath the individualist façade of rights and contracts.
Those of us in white-collar jobs who are able to work from home and swap sourdough tips are more dependent than we perhaps realized on previously invisible essential workers, such as hospital cleaners and medics, supermarket staff, parcel couriers, and telecoms technicians who maintain our connectivity.
Similarly, manufacturers of new essentials such as face masks and chemical reagents depend on imports from the other side of the world. And many people who are ill, self-isolating, or suddenly unemployed depend on the kindness of neighbors, friends, and strangers to get by.
The sudden stop to economic activity underscores a truth about the modern, interconnected economy: what affects some parts substantially affects the whole. This web of linkages is therefore a vulnerability when disrupted. But it is also a strength, because it shows once again how the division of labor makes everyone better off, exactly as Adam Smith pointed out over two centuries ago.
Today’s transformative digital technologies are dramatically increasing such social spillovers, and not only because they underpin sophisticated logistics networks and just-in-time supply chains. The very nature of the digital economy means that each of our individual choices will affect many other people.
Consider the question of data, which has become even more salient today because of the policy debate about whether digital contact-tracing apps can help the economy to emerge from lockdown faster.
This approach will be effective only if a high enough proportion of the population uses the same app and shares the data it gathers. And, as the Ada Lovelace Institute points out in a thoughtful report, that will depend on whether people regard the app as trustworthy and are sure that using it will help them. No app will be effective if people are unwilling to provide “their” data to governments rolling out the system. If I decide to withhold information about my movements and contacts, this would adversely affect everyone.
Yet, while much information certainly should remain private, data about individuals is only rarely “personal,” in the sense that it is only about them. Indeed, very little data with useful information content concerns a single individual; it is the context – whether population data, location, or the activities of others – that gives it value.
Most commentators recognize that privacy and trust must be balanced with the need to fill the huge gaps in our knowledge about COVID-19. But the balance is tipping toward the latter. In the current circumstances, the collective goal outweighs individual preferences.
But the current emergency is only an acute symptom of increasing interdependence. Underlying it is the steady shift from an economy in which the classical assumptions of diminishing or constant returns to scale hold true to one in which there are increasing returns to scale almost everywhere.
In the conventional framework, adding a unit of input (capital and labor) produces a smaller or (at best) the same increment to output. For an economy based on agriculture and manufacturing, this was a reasonable assumption.
But much of today’s economy is characterized by increasing returns, with bigger firms doing ever better. The network effects that drive the growth of digital platforms are one example of this. And because most sectors of the economy have high upfront costs, bigger producers face lower unit costs.
One important source of increasing returns is the extensive experience-based know-how needed in high-value activities such as software design, architecture, and advanced manufacturing. Such returns not only favor incumbents, but also mean that choices by individual producers and consumers have spillover effects on others.
The pervasiveness of increasing returns to scale, and spillovers more generally, has been surprisingly slow to influence policy choices, even though economists have been focusing on the phenomenon for many years now. The COVID-19 pandemic may make it harder to ignore.
Just as a spider’s web crumples when a few strands are broken, so the pandemic has highlighted the risks arising from our economic interdependence. And now California and Georgia, Germany and Italy, and China and the United States need each other to recover and rebuild. No one should waste time yearning for an unsustainable fantasy.