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Confirming the test result (i.e., by repeating the test, if this option is available) could reduce the ultimate likelihood of a false positive to about 1 result in 250,000 tests given. The sensitivity rating, likewise, indicates that, in 1,000 test results of HIV infected people, 3 will actually be a false negative result.
A non-reactive (negative) rapid point of care test should still be followed up with immunoassay testing such as by a fourth-generation test after the window period. [27] Similarly, individuals taking pre-exposure prophylaxis (PrEP) can experience extended window periods compared to the average population, leading to ambiguous testing. [ 28 ]
The term serostatus is commonly used in HIV/AIDS prevention efforts. In the late 20th and early 21st centuries, social advocacy has emphasized the importance of learning one's HIV/AIDS serostatus in an effort to curtail the spread of the disease. [1]
Cross-reactivity, in a general sense, is the reactivity of an observed agent which initiates reactions outside the main reaction expected.This has implications for any kind of test or assay, including diagnostic tests in medicine, and can be a cause of false positives.
HIV-1 testing is initially done using an enzyme-linked immunosorbent assay (ELISA) to detect antibodies to HIV-1. Specimens with a non-reactive result from the initial ELISA are considered HIV-negative, unless new exposure to an infected partner or partner of unknown HIV status has occurred.
When an HIV-negative person exhibits VISP and gets an HIV-positive result from a test then that person may have difficulty donating blood or negotiating for a life insurance policy. [ 2 ] Between 1987 and 2003 the number of persons who received experimental HIV vaccinations was about 10,000, and this number was considered small.
If the likelihood ratio for a test in a population is not clearly better than one, the test will not provide good evidence: the post-test probability will not be meaningfully different from the pretest probability. Knowing or estimating the likelihood ratio for a test in a population allows a clinician to better interpret the result. [7]
So, if there is a specificity of 98.5%, it means that out of 1000 people who take the test and do not have HIV, 15 of them will receive a false positive result. To find the number of false positive results out of 1000 positive HIV test results, you would need to calculate the positive predictive value.