'Either we can use models, trying to stay cautious about how much they’re really telling us, or we can rely on conjecture, gut reactions and expert opinion alone. Only the first path is a transparent one with a built-in mechanism for self-correction.'
For the past few months, we’ve heard a lot about statistical models and their predictions of what might happen as the COVID-19 pandemic rages on. Their estimates have varied widely — in part because almost every piece of data that goes into the models is imperfect.
, like characters in a computer game, and then let the game play out according to some algorithm to see what happens. In either case, the scientist has posed what we call aThere’s a challenge with mechanistic models, however. To fully specify a mechanistic model, we have to give actual values tosingle feature of the model.
There is no single way that infectious disease modelers arrive at reliable numbers for these values. Some of these things we can measure. For instance, we can measure the speed at which people isolate by asking people who are hospitalized when they first began to feel symptoms and when they were first isolated . If the delay is five days on average, in some population or other, then the isolation rate for that population is ⅕.
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