Open by Pentecost? By fall? Whenever a vaccine is ready? Who can tell us? Only the scientists, we are told. But although the pandemic itself is a natural and therefore amoral phenomenon, our response to it is, and has to be, a moral one. For that reason, science isn’t enough. We also need practical wisdom, otherwise known as prudence.
Both science and prudence tell us that a pandemic requires a collective response. We can’t do this job individually, or in competing teams. (The board game Pandemic teaches this lesson well, by the way.) Once most of us grasped “exponential function” and “flattening the curve” and saw the example of Italy’s outbreak, we witnessed collective action far beyond anything in my lifetime. That’s great. Solidarity was imperative. When we needed it, it was there.
But now what? A while back, President Trump grabbed the headlines and played to his base by claiming the country would be “open by Easter,” relishing the far-fetched prospect of packed churches. This led journalists to ask other politicians what they thought of this claim. Here’s how Virginia Governor Ralph Northam responded: “It would be nice to say that this will be behind us in two weeks…. That’s really not what the data tells us. What the data tells us is this will be with us for at least two to three months and perhaps even longer.” He added: “I think we have to use science, we have to use data…and really do what’s in the best interest—in our case—of Virginians.” More recently, New Jersey’s governor, Phil Murphy, announced that “the data shows us we are ready” for a phased reopening, while down the road in Montgomery County, Maryland, Marc Elrich said stay-at-home orders would remain in place: “We will change the rules as soon as the science says that we can change the rules.” These responses all suggest that science or “the data” can tell us exactly what to do. But “What should we do?” is never just a scientific question; it’s also a moral one. The misleading identification of prudent public policy with attention to empirical data is deeply problematic in our present situation, for two reasons.
First, it obscures the uncertainty and provisionality of the data itself. Scientific research is a long, messy process of conjecture and refutation. Researchers propose interpretations of evidence and these either stand the test of time or are rejected as new evidence comes in. At such an early stage of a public-health crisis, we are confronted by many incomplete and conflicting reports. But even when we have clearer findings, a second problem is that the kind of prudence politicians need in order to make wise decisions about the common good is a matter of judgment rather than measurement or calculation—even though measurement and calculation must inform it.
Let’s talk about the science first. As with many other issues, the outsized effect of the Trump presidency on this discussion has been dismal. President Trump’s imprudence is an obvious one: he believes (insofar as he has any settled beliefs) that moral language does not even need to take account of empirical data. Matters such as accuracy and consistency are subordinated to gut-level impulses. There are obvious and grave dangers when one substitutes bluster and magical thinking for basic scientific literacy. We’re all witnessing that now.
Yet an imprudent use of data can happen in other ways, too. Northam and other politicians who claim they are going to “follow the science” make that sound simpler than it really is. Research is moving quickly, with over 13,000 papers published on the virus since it was discovered. That may seem like good news, but it actually raises a host of difficulties for public officials. Good science tends to move slowly, requiring great care. In the current environment, labs are rushing publications out, journals are rushing peer review, and journalists report on not-yet-peer-reviewed preprints. Some theories and expert opinions will turn out to be wrong. We’ve already seen the recommendations of public-health officials dramatically change tack as new information becomes available: Are masks helpful? They weren’t but now they are. Is Ibuprofen dangerous? First the answer was maybe yes, then it was probably no.
Just as importantly, given the failures of widespread testing, we still lack knowledge of many of the basic characteristics of the pandemic, like when it began, how many people have been infected, or the infection mortality rate. Recent studies indicate that daily public-health numbers suffer from erratic and inconsistent reporting, and that national data on even the simplest measure—the number of deaths—is murky. Moreover, without clear data, predictive modeling is even more uncertain. Much of this is what one would expect at the early stage of a pandemic: epidemiology is an incredibly complicated area of research. Since much of the science isn’t settled—and since we can’t always afford to wait until it is—governing officials must exercise prudence in their use of the available information. They cannot ignore it or wish it away, but they also cannot expect it to answer all their questions.