The pandemic has shown how a lack of solid statistics can be dangerous. But even with the firmest of evidence, we often end up ignoring the facts we don’t like. By Tim Harford
By the spring of 2020, the high stakes involved in rigorous, timely and honest statistics had suddenly become all too clear. A new coronavirus was sweeping the world. Politicians had to make their most consequential decisions in decades, and fast. Many of those decisions depended on data detective work that epidemiologists, medical statisticians and economists were scrambling to conduct. Tens of millions of lives were potentially at risk. So were billions of people’s livelihoods.
In early April, countries around the world were a couple of weeks into lockdown, global deaths passed 60,000, and it was far from clear how the story would unfold. Perhaps the deepest economic depression since the 1930s was on its way, on the back of a mushrooming death toll. Perhaps, thanks to human ingenuity or good fortune, such apocalyptic fears would fade from memory. Many scenarios seemed plausible. And that’s the problem.
