Issues in human immunodeficiency virus (HIV) screening programs.
Unlike test sensitivity and specificity, the false positive and negative predictive values (probabilities of mislabeling an individual being tested) depend heavily on the prevalence of the infection of the human immunodeficiency virus (HIV) as well as the quality of the kit. A consequence of this dependence is that the false positive predictive value can reach a high magnitude such as 0.9; that is, 90% of the positive tests are false. This raises many important issues pertaining to the current practice of HIV screening such as to how to control these misclassification errors, how to interpret test results, and how to estimate prevalence using test results. These issues are examined in detail here by considering the factors that dictate the quality of a screening program. Some real data examples are used to illustrate the importance of this consideration in designing programs to achieve the desired goals. The rationale behind the common two-step sequential protocol in HIV screening is examined to point out its limitations under practical situations. Finally, the use of entropy in evaluating the informativeness of a screening program is discussed.
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Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115.
Litvak
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Pagano
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D015492:AIDS Serodiagnosis / Q000379:methods / Q000592:standards*; D015982:Bias; D015658:HIV Infections / Q000175:diagnosis* / Q000453:epidemiology / Q000517:prevention & control; D015528:HIV Seroprevalence; D015497:HIV-1; D006801:Humans; D008403:Mass Screening / Q000379:methods / Q000592:standards*; D015233:Models, Statistical; D011786:Quality Control; D012680:Sensitivity and Specificity