Validating Marker-Based Incidence Estimates in Repeatedly Screened Populations

Authors

  • Glen A. Satten ,

    Corresponding author
    1. Division of HIV/AIDS Prevention-Surveillance and Epidemiology, National Center for HIV, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia 30333, U.S.A
      *email:gas0@cdc.gov
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  • Robert Janssen,

    1. Division of HIV/AIDS Prevention-Surveillance and Epidemiology, National Center for HIV, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia 30333, U.S.A
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  • Michael P. Busch,

    1. Blood Centers of the Pacific San Francisco, California, U.S.A.
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  • Somnath Datta

    1. Department of Statistics, University of Georgia, Athens, Georgia, U.S.A.
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*email:gas0@cdc.gov

Abstract

Summary. Disease incidence (new cases of disease per person per year) is usually measured by using longitudinal data. However, several recent proposals for measuring the incidence of human immunodeficiency virus (HIV) rely on cross-sectional data only. These methods assume each person is only sampled once; however, in some instances, it is necessary to consider these cross-sectional methods when individuals are represented more than once in the survey sample. We derive an extension of the cross-sectional incidence estimator that is valid for data from repeatedly screened populations and show under what conditions our new estimator reduces to the old estimator. An example involving estimation of HIV incidence among repeat blood donors is presented.

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