| Yesterday, the world officially recorded its one-millionth Covid-19 case. It's a big, round, scary number. And it's almost certainly wrong. Statistics matter, of course, and yesterday's figure shows us just how far and fast this virus has spread. If anything, it's also a monument to a global failure of disease surveillance. The U.S. has stumbled on rolling out widespread testing to track cases early on, and is only diagnosing patients when they're sick enough to visit the hospital. China, U.S. intelligence services allege, downplayed its outbreak to make it seem less bad. And North Korea either has a public health corps that should be the envy of the world, is incredibly lucky, or is lying. In reality, the world almost certainly passed the one-million case threshold days or weeks ago. A small Chinese study has found that a significant share of cases are asymptomatic, adding to a growing body of research suggesting that there's a population of people without telltale signs of disease who could be causing infections. And with health systems in crisis mode, the focus is on saving the sick, not tallying the virus's spread to people who don't need care. But that also makes it harder to know the things we need to. What's the true fatality rate? How many people are asymptomatic, but infectious? What groups are most at risk? Those are questions that still haven't been answered. We're living in a time of record numbers (stock-market drops, stock-market gains, last week's jobless claims data, this week's jobless claims data) that have a shelf life measured in days.So if the data are so unsatisfying, why measure them at all? It's because we don't have anything better, at least for now. Lacking more widespread testing and fully transparent sharing of data, case counts remain the unsatisfying best that we have for knowing what's to come. —Drew Armstrong | 
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