There's a difference between diagnostic testing of individuals who have symptoms and population level screening. Both involve statistics and probability, and t

There's a difference between diagnostic testing of individuals who have symptoms and population level screening. Both involve statistics and probability, and the public (and a surprising number of health care professionals) really struggle with both. To take your number: a disease exists. There's a test for that disease. The test is good, but not perfect. If you have the disease there is a 99% probability that the test will return "Positive". But if you do not have the disease there is a 10% chance that the test will also return "positive". 4 people in 100,000 people have the disease. Hypothetical Bob takes the test. The test shows "positive". What is the probability that Bob actually has the disease? Most of the public, and lots of healthcare providers, cannot even begin to answer this problem. They simply lack the math skill to start to work out what the answer is. 4 people out of 100,000 people have a disease. There is a test for the disease. If you have the disease the test will, 99 times out of 100, say "positive". If you do not have the disease the test will, 10 times out of 100, (100 out of 1,000, 1,000 out of 10,000 or 10,000 out of 100,000) say "negative". Bob has had the test. It said positive. What's the chances he has the disease? Now people can see that only 4 people in 100,000 have the disease and most of those are going to get a positive result, but also 10,000 people who don't have the disease will also get a positive result. We'd be overwhelming diagnostic services with people who do not have cancer because our test is terrible. Of course, all of this changes if Bob has a mole that has changed shape, because the testing converts from a screening test to a diagnostic test.