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  2. Diagnosis of HIV/AIDS - Wikipedia

    en.wikipedia.org/wiki/Diagnosis_of_HIV/AIDS

    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.

  3. Seroconversion - Wikipedia

    en.wikipedia.org/wiki/Seroconversion

    Current CDC recommendations are to begin with a test that screens for both antigen and antibody, then follow up with an immunoassay to differentiate between HIV-1 and HIV-2 antibodies. Non-reactive (negative) tests are followed up with nucleic acid tests for viral RNA. [27]

  4. HIV - Wikipedia

    en.wikipedia.org/wiki/HIV

    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.

  5. Serostatus - Wikipedia

    en.wikipedia.org/wiki/Serostatus

    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]

  6. Vaccine-induced seropositivity - Wikipedia

    en.wikipedia.org/wiki/Vaccine-induced_seropositivity

    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.

  7. Talk:Diagnosis of HIV/AIDS - Wikipedia

    en.wikipedia.org/wiki/Talk:Diagnosis_of_HIV/AIDS

    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.

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