Yes, I found out that later, but while we were in the low hundreds fitting to an exponential didn't seem to work very well in comparison to a polynomial (it was

Yes, I found out that later, but while we were in the low hundreds fitting to an exponential didn't seem to work very well in comparison to a polynomial (it was overestimating). It wasn't a quadratic either. There it jumped and I remembered I should try population growth models. I started with Gompertz, which is pretty much indistinguishable from logistic at this stage. Then I found out that logistic was more stable and parameters seemed to converge for a few days, so I learned about SIR/SIS. And then I figured I had some idea about what to expect in the following few days. I stopped trusting any of my rudimentary models by Sunday+incubation, because conditions changed then. Which data, why I trusted them and the set of assumptions taken to consider them representative for the shape of the time series/distribution, that's something I don't think I should share here at this point. In any case I'm used to extract some information from imperfect data, you approximate and estimate. I mean there was by then 12, then 16, then 30 positives in a nursery home next to my door, and no lockdown measures, now there's 100, an improvised hospital there and I'm not allowed go out except for buying groceries. Two weeks ago I needed some picture which I wasn't getting anywhere, the alternative was freaking out after comparing what the authorities were saying with what I knew about the situation. Now they are making sense and the measures in place too, so I expect it getting much better soon. I don't want to go into epidemiology and I want to respect and trust blindly the epidemiologists, but in any field you expect the professionals having predictive skills working before your eyes, that's their job. Hearing that we should wait for the post-mortem to know where we are now, I mean, come on... And now I'll just shut up.