2. Their model predicts that the peak of the epidemic in Italy should have been before March 5th (first death on February 22nd + 14 days, at which point easily more than half the population is infected). There should have been a sharp drop in new cases about a week later, as the virus burnt itself down. But here we are three weeks later, and it's still not entirely clear that the peak has been found.
Italy did not institute significant nation-wide measures until March 9th, so the "slowdown from measures" explanation makes no sense.
3. Agreed. But their entire model is predicated on treating the entire country as a single unit. That's probably a part of the reason why the results are so absurd. I don't think it's fair to excuse the model for regional differences, but require any criticism of the model to take them into account.
4. The difference between the model's prediction and apparent reality is likely to be about a factor of 200. Even assuming everybody on the ship was actually infected, that only cuts it to a factor of 40 difference.
And it's really not just that single case. Consider that infamous Washington state nursing home. 120 residents, 35 dead from Covid to date. Even if we assume that every single one of the 120 was infected despite not testing positive, that still an IFR of 30%. Sure, it's a high-risk segment. But it's also a large enough segment a 30% IFT for them makes it quite impossible for the population-wide IFR to be 0.01%.
(Re: your last point, they had two parameters. One for being at risk of becoming a serious case, and another of dying if serious. The two need to be multiplied to get their predicted IFR. They assumed that 0.1% of population were at risk to become severe cases, and 15% of the severe cases died. So about 0.01%).
