Diagnostic Test: Predictive Values

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Example: a rapid test has 85% sensitivity and 99% specificity, and is used in a city where 2% of people have the disease. If your result is positive, what is the chance you are ill? Change the values to work out your own case.

Sensitivity S (%) Specificity E (%) Prevalence p (%)

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What each term means

Positive Predictive Value (PPV): The chance of being ill given a positive test. It is what matters to whoever gets the result, and it depends heavily on how common the disease is.
True Positives (S · p): The share of the population that is ill and tests positive: the sensitivity S (how many ill people the test catches) times the prevalence p.
All Positives: The true positives plus the false ones: healthy people, 1 − p, who test positive by mistake, 1 − E, where E is the specificity. When the disease is rare, the false ones can be the majority.