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The asymptomatic rate being that high and that many people being infected implies three things.

1) that the asymptomatic rate for this Coronavirus is much higher than other Coronaviruses.

2) but at the same time, it's more deadly than most Coronaviruses.

3) and it's also the R0 is much higher than other Coronaviruses.

Isn't it more likely there's a testing issue? This seems a lot like a person that runs a SQL query that overturns all established data at a business, and instead of first assuming that their query is wrong, they instead assume everyone at the business is wrong.

I'm not saying the tests are inaccurate. I'm saying when you get highly conflicting data that has critical implications, you shouldn't jump to conclusions. And you should prepare for the worst case, not assume the best.



> the R0 is much higher than other Coronaviruses

R0 depends on the population you measure. In a high contact, crowded place, the R0 could be very high. In a population staying at home, the R0 could be very low.


> instead of first assuming that their query is wrong, they instead assume everyone at the business is wrong

All those 3 numbers you cite are taken from the same small set of models where the rate of asymptomatic cases is an input. So, no, that's not right.


If the asymptomatic rate is higher, then it is less dealt, no?




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