The trouble is that pretty much all of the data is garbage quality, and if you feed garbage into a computer you of course just get garbage out. The figures from Wuhan are particularly bad, probably just a function of their testing ramp-up until well after the peak, and the ones from Italy might not be much better. (The other problem is that China has taken the position that their numbers are an exact description of reality and their approach is a model for the rest of the world to follow, basically for domestic political reasons, and the WHO seems to be eagerly regurgitating this to the many people who'll listen.)
I wouldn't necessarily call the data "garbage" but the numbers are definitely _soft_.
But soft numbers are a common issue with many areas of public health. In particular, analysis of the current pandemic suffers from both a "numerator" and "denominator" problem (http://conflict.lshtm.ac.uk/page_83.htm)
I think many of us are accustomed to getting high-quality stats when studying a process. But that's often not possible with a fast-moving public health issue.
I think you have to acknowledge the limitations of the data, but it can still be helpful.
The thing I _don't_ like about the JHU dashboard is that it doesn't really let you slice the data in interesting ways. For example, I'd like to be able to click on a country or state/province and see temporal data. This doesn't seem like it would be that difficult, but maybe I'm naive.
I've tried doing some stuff with the Italian data but got a similar roadblock. For example, I'd be interested in knowing, among the ICU cases, if these cases were new (people arrived in the ICU with a diagnosis) or a worsening of the already existing patients (perhaps in sub-intensive care earlier).
It would help forming an idea on how the current situation (in addition to the new cases) is going.
Is there an open data portal for emergency room visit stats? That would probably paint a better picture of the real case count, by showing us whether there's a spike in visits for acute respiratory illness.
