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So if 5% of the population have had it then using 98.5% and 99.5% figures we get:-
-ve result would be 99.973% accurate
+ve result would be 91.284% accurateIf 1% of the population have had it then:-
-ve would be 99.995% accurate
+ve would be 66.779% accurateIf 10% of the population have had it then:-
-ve would be 99.944% accurate
+ve would be 95.673% accurateWhat are you doing to get a shift in sensitivity/specificity based on an outside factor?
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The sensitivity and specificity aren't changing. The derived accuracy of a result changes depending on how prevalent the condition is amongst the tested population as the relative
The less prevalent the condition is in the population the more false positives you'll get.
The more prevalent the condition is in the population the more false negatives you'll get.
Both of these factors affect the eventual accuracy. See: https://www.lfgss.com/comments/15296147/
That's what they claim, it later says:-
So if 5% of the population have had it then using 98.5% and 99.5% figures we get:-
-ve result would be 99.973% accurate
+ve result would be 91.284% accurate
If 1% of the population have had it then:-
-ve would be 99.995% accurate
+ve would be 66.779% accurate
If 10% of the population have had it then:-
-ve would be 99.944% accurate
+ve would be 95.673% accurate
(Caveat my fat fingers mistyping something into a spreadsheet.)