That's exactly what I don't understand. Logically, wouldn't deaths typically lag diagnosis by some amount? If so, we would expect the death rate to be higher than current deaths/cases because we need to use the confirmed cases from some number of days ago. That number of days being the average time between someone being diagnosed and dying.
Another stat is that there are roughly 700 deaths and 2400 recoveries, which would indicate a mortality rate of 23%. Of course, this suffers from the same delay issue as the 2% calculation (T_death < T_recovery). But the possible range is 2% < M_rate < 23%
There's a standard paper on this topic the authors I forget atm but all estimates will be biased. The best estimates are sort of unintuitive and account for estimated time-to-death and the time since diagnosis.
Another stat is that there are roughly 700 deaths and 2400 recoveries, which would indicate a mortality rate of 23%. Of course, this suffers from the same delay issue as the 2% calculation (T_death < T_recovery). But the possible range is 2% < M_rate < 23%
https://www.worldometers.info/coronavirus/#repro