And that's assuming that the 99% accurate really means 99% sensitive, 99% specific.
To amplify your point,
99% sensitive from 100000 people with an incidence of 60 means 1 false negative, assuming you can't detect .4 of a person and floor to integer.
99% specific from the same pool means 999 false positives, same assumption.
You mentioned that re: 1000 total, but the kicker:
Total population, 59 true positives + 999 false positives.
So, if I test positive, absent any more knowledge that means it's a 59/(999 + 59) chance of being true, or around a 6% chance of being true.
Probably enough for followup testing, but an interesting demo of why the statistical accuracy is meaningless unless you also know the actual incidence. 99% becomes not many % right quick.
Comments
And that's assuming that the 99% accurate really means 99% sensitive, 99% specific.
To amplify your point,
99% sensitive from 100000 people with an incidence of 60 means 1 false negative, assuming you can't detect .4 of a person and floor to integer.
99% specific from the same pool means 999 false positives, same assumption.
You mentioned that re: 1000 total, but the kicker:
Total population, 59 true positives + 999 false positives.
So, if I test positive, absent any more knowledge that means it's a 59/(999 + 59) chance of being true, or around a 6% chance of being true.
Probably enough for followup testing, but an interesting demo of why the statistical accuracy is meaningless unless you also know the actual incidence. 99% becomes not many % right quick.