Earlier quoted context omitted.
Let me give it a try. Suppose we have 100,000 people in a statistically representative town. If 1% of people have had COVID-19, then that's 1000 people who have had it, and 99,000 people who haven't. The test has a sensitivity of 100%, which means all 1000 people who've had it will test positive. The test has a specificity of 99.9%, which means 98,901 of the 99,000 people who haven't had it will test negative; but th…
So if I'm understanding this correctly, with this test. If you test negative, you are clear, guaranteed, no false negatives. If you test positive, there is a 10% chance it's a false positive. I guess my follow up question, does a retest of the positive population make that false positive rate drop to 0.1%, or is the reason for false positive significant to an individual and not random chance?
This percentage is based on both the test and the real infection rate.