Will anyone with disease be missed with your strategy and if so why Suggested

Will anyone with disease be missed with your strategy

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NOT cause disease). Will anyone with disease be missed with your strategy, and if so, why? Suggested strategy: Screen first with the inexpensive rapid test. This has an 82% likelihood of finding people with either the A80 or A81 mutation (i.e. 82% sensitivity for A80 or A81). The problem with this test is that out of all the positives obtained, some will be people who have the A81 mutation, which does NOT cause the disease. To find these people, all the positives will need to be tested again using the more expensive definitive test to identify only those people with the A80 mutation (i.e. distinguish between those with the A80 and A81 mutation). However, it is much more cost effective to be using the expensive definitive test on the small group of people with positive rapid tests, rather than testing everyone with the more expensive test. The main shortcoming of this approach is that it will still miss ~18% of true positives since the rapid test is only 82% sensitive. Those who had false negative tests will not be identified using the definitive test, since that will only be used on people with positive tests to identify false positives. Thus, the proposed strategy will not identify true positives that were missed by the first test. Sensitivity and Specificity Question B: You are working at a public health department that is choosing between two new HIV tests. HIV test 1 has 99.5% sensitivity and 80% specificity for diagnosing HIV. HIV test 2 has 85% sensitivity and 99.9% specificity for diagnosing HIV. Question 1: Out of 1000 people with true HIV infection, how many will have false negative results with test 1? Sensitivity is the true positive rate, meaning the number meaning the number of people with disease who test positive. Sensitivity is also the inverse of the false negative rate. Thus, a test with 99.5% sensitivity has an 0.5% false negative rate (100% - 99.5% = 0.5%). Thus, 5 out of 1000 people with true HIV infection will test negative with test 1. Question 2: Out of 1000 people with true HIV infection, how many will have false negative results with test 2?
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Jaisri Lingappa, MD PhD Science in Public Health, SPH381 3 Sensitivity is the true positive rate, meaning the number meaning the number of people with disease who test positive. Sensitivity is also the inverse of the false negative rate. Thus, a test with 85% sensitivity has a 15% false negative rate. Thus, 150 out of 1000 people with true HIV infection will test negative with test 2.
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