[contravariant]

Your formula has the opposite problem, by looking at cases that have a known outcome you are biasing results towards cases that end quickly (in particular cases that end in death).

For a proper estimate we should look at cases where the infection is known to have begun e.g. a month ago. Then the mortality rate should be somewhere between dead/infected and dead/(dead + recovered).

[swader999]

There's also the possibility of reinfection and false negatives. The best data we have is not even close to perfect.

[nik_s]

> Your formula has the opposite problem, by looking at cases that have a known outcome you are biasing results towards cases that end quickly (in particular case that end in death).

Unless I'm mistaken, that would only be true if cases that end in death are much faster than the cases that end in recovery. I have found it difficult to find detailed statistics on the topic, so I cannot tell you that it's definitely true or not, but I agree that it's an important variable that should be taken into the equation.

[twotwotwo]

With many viral respiratory bugs, symptoms appear a few days after infection, peak a few days after that, and then there's a long tail of sniffling and coughing. Deaths happening in the peak and recovery being declared nearer the end of the tail leads to the intuition that maybe deaths could cluster earlier than recoveries. Of course, I don't know how/when recoveries are being tallied right now and don't want to guess.

Bigger picture: lots of factors go into a good estimate, and epidemiologists are not new to mathematical modeling. When back-of-the-envelope math doesn't get the same prediction as the consensus models of what's going on, we shouldn't assume the epidemiologists are wrong.