Unfortunately, it turned out that the model had far deeper problems than incomplete information. One was that, when fitting those curves, it operated under an assumption that states’ curves would generally be symmetrical — that deaths would fall as quickly as they had risen. There is no reason this has to be the case, and indeed, imposing a specific shape like this undermines the entire point of drawing on other places’ experiences to see where we could end up.

Another problem was that the damn thing simply didn’t work. It wasn’t and isn’t some conspiracy to over- or under-predict the toll of COVID-19; it just has not been very accurate. Last month, a group of researchers pointed out that the model was failing to make even the shortest-term predictions accurately. Its guesses were so far off that even its “95 percent” intervals didn’t include the correct value 70 percent of the time. The group updated its paper a few weeks later, finding that the predictions were no better in later versions of the model (though the accompanying intervals had widened, so they included the correct number far more often).

The IHME model’s national-level predictions weren’t quite that bad, but at one point they ticked down to about 60,000. We’re already at 70,000 today.