> If the top scientists from well-funded teams came up with estimates that were so wildly off, I'm not sure why we have any hope of getting these things right.

I think there's a lot of confusion from the general public about how to evaluate models. A modeling being "correct" is sometimes not possible, and useful, sometimes a model has to be used instead to reduce uncertainty, not to exactly predict X amount of cases in Y amount of time. There's just so much randomness in systems that prevent accuracy in predictions.