Much of the public debate about the coronavirus pandemic has centered on the issue of data — How much data do we have? How reliable are the data? How compatible are competing sets of data? Answering these questions is important not only for grasping the nature and scope of the pandemic but also for assessing our government’s response to it. Put simply, data are vital not only to understand the virus scientifically but also to make informed decisions about how to act.
Yet there lurks a distinct, and much more debatable belief about the role that data can and should play in science-based policy. Some have suggested that the data we have are too uncertain to justify our government’s response, or that our response should be based on risk assessment rather than uncertainty. Such arguments rightly call attention to the challenges and limitations experts face as they endeavor to understand Sars-CoV-2 and to formulate policy recommendations. Beyond this, though, such criticisms also seem to assume that data, if sufficient in volume and quality, can provide us with certainty, thus warranting action — be it imposing wide-spread social distancing measures, banning international travel, or lifting mitigation strategies.
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