Chapter 2, Unit E Screening Tests.

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Presentation transcript:

Chapter 2, Unit E Screening Tests

Essential Question: How accurate are the tests claiming to be REALLY?

Screening Tests: Used to test a large population for a disease Must be cheap and easy to apply to a large number of people Not usually very precise If a screening test comes back positive, the person is tested again, using a more accurate confirmatory test

Screening Test Questions: Does the person actually have the disease? Will the person test positive or negative?

Screen Test Results= Could be in 4 Groups: False negative: Have the disease but test negative True positive: Have the disease and test positive True negative: Don’t have the disease and test negative False positive: Don’t have the disease but test positive

Example 1: HIV Screening United States Tests Positive Tests Negative Total Has HIV 5,982 18 6,000 Doesn’t have HIV 14,910 979,090 994,000 20,982 979,108 1,000,000

Example 1: HIV Screening What percentage of people in the US have HIV? This is the PREVELANCE of the disease. What percentage of the people with HIV actually test positive? (round your percentage to one decimal place) What percentage of people without HIV test positive? This is called the FALSE POSITIVE rate. What percentage of people with HIV test negative? This is called the FALSE NEGATIVE rate. What percentage of people who test positive actually have HIV? This is the PREDICTIVE VALUE OF A POSITIVE TEST and answers the question, “If someone tests positive, what is the probability that they actually have HIV?”

Example 1: HIV Screening What percentage of people in the US have HIV? This is the PREVELANCE of the disease. 0.6% What percentage of the people with HIV actually test positive? (round your percentage to one decimal place) 99.7% What percentage of people without HIV test positive? This is called the FALSE POSITIVE rate. 1.5% What percentage of people with HIV test negative? This is called the FALSE NEGATIVE rate. 0.3% What percentage of people who test positive actually have HIV? This is the PREDICTIVE VALUE OF A POSITIVE TEST and answers the question, “If someone tests positive, what is the probability that they actually have HIV?” 28.5%

Example 2: HIV Screening Botswana Tests Positive Tests Negative Total Has HIV 238,283 717 239,000 Doesn’t have HIV 11,415 749,585 761,000 249,698 750,302 1,000,000

What percentage of people in Botswana have HIV? What percentage of people without HIV test positive? FALSE POSITIVE RATE What percentage of people with HIV test negative? FALSE NEGATIVE RATE What percentage of people who test positive actually have HIV? PREDICTIVE VALUE OF POSITIVE TEST Compared to the data from the US, which of the computed values changed and which stayed the same?

What percentage of people in Botswana have HIV? 23.9% What percentage of people without HIV test positive? FALSE POSITIVE RATE 4.6% What percentage of people with HIV test negative? FALSE NEGATIVE RATE 0.1% What percentage of people who test positive actually have HIV? PREDICTIVE VALUE OF POSITIVE TEST 99.7% Compared to the data from the US, which of the computed values changed and which stayed the same?