How should we interpret the "with covid" numbers when trying to estimate the chance of being asymptomatic? My intuition is people admitted to the hospital are generally less healthy than the rest of the population. Is it fair to assume that the 12% asymptomatic rate from UCSF should be a strict lower bound on the probability that a boostered and healthy 20 something (asking for a friend) person would be asymptomatic if they caught covid?
Any good estimates on the asymptomatic rate by demographic? Maybe workplaces or schools that test regularly, or from surveillance testing?
At the end of 2020, the CDC estimated ~85 million infections. There were however only 32 million cases at that time. A large fraction of the difference would be asymptomatic.
2tslarm
I think 12% is the positive rate among patients without symptoms at the time of the test, so if you want to extrapolate from there to an estimate of your chance of experiencing no symptoms, you'll first need to estimate how many of those people were in fact presymptomatic.
edit: also, if I'm reading your comment right, I think you're interpreting 12% as the proportion of positive cases that had no symptoms, whereas it's actually the proportion of people without symptoms who tested positive:
How should we interpret the "with covid" numbers when trying to estimate the chance of being asymptomatic? My intuition is people admitted to the hospital are generally less healthy than the rest of the population. Is it fair to assume that the 12% asymptomatic rate from UCSF should be a strict lower bound on the probability that a boostered and healthy 20 something (asking for a friend) person would be asymptomatic if they caught covid?
Any good estimates on the asymptomatic rate by demographic? Maybe workplaces or schools that test regularly, or from surveillance testing?