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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. 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.

  4. 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]

  5. Sensitivity and specificity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_and_specificity

    A negative result in a test with high sensitivity can be useful for "ruling out" disease, [4] since it rarely misdiagnoses those who do have the disease. A test with 100% sensitivity will recognize all patients with the disease by testing positive. In this case, a negative test result would definitively rule out the presence of the disease in a ...

  6. HIV - Wikipedia

    en.wikipedia.org/wiki/HIV

    The latest recommendations of the US Centers for Disease Control and Prevention (CDC) show that HIV testing must start with an immunoassay combination test for HIV-1 and HIV-2 antibodies and p24 antigen. A negative result rules out HIV exposure, while a positive one must be followed by an HIV-1/2 antibody differentiation immunoassay to detect ...

  7. False positives and false negatives - Wikipedia

    en.wikipedia.org/wiki/False_positives_and_false...

    The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.

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