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Snapshot Estimators of Recent HIV Incidence Rates

Author

Listed:
  • Edward H. Kaplan

    (Yale University School of Management, New Haven, Connecticut)

  • Ron Brookmeyer

    (Johns Hopkins University, Baltimore, Maryland)

Abstract

The recent HIV incidence rate (or hazard rate for infection) is an important quantity for use in monitoring the HIV/AIDS epidemic, evaluating HIV prevention programs, and allocating HIV prevention resources. Direct measurement of HIV incidence is difficult and time consuming, while estimating HIV incidence via backcalculation (deconvolution) using AIDS incidence data and the (presumed known) HIV incubation time distribution yields little information about recent infection. We propose a method for estimating recent HIV incidence in a population via a single sample at a single point in time. The method relies on understanding the progression of certain markers such as CD4 counts following infection. The actual formulas derived for the point and interval estimates of HIV incidence are simple and easy to use while the sample sizes needed to implement our approach are reasonable. We present two applications of our approach, comparing our results to those obtained from more conventional methods where possible.

Suggested Citation

  • Edward H. Kaplan & Ron Brookmeyer, 1999. "Snapshot Estimators of Recent HIV Incidence Rates," Operations Research, INFORMS, vol. 47(1), pages 29-37, February.
    • Handle: RePEc:inm:oropre:v:47:y:1999:i:1:p:29-37
    DOI: 10.1287/opre.47.1.29
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    References listed on IDEAS

    as
    1. Edward H. Kaplan, 1995. "Probability Models of Needle Exchange," Operations Research, INFORMS, vol. 43(4), pages 558-569, August.
    2. Winkelstein Jr., W. & Samuel, M. & Padian, N.S. & Wiley, J.A. & Lang, W. & Anderson, R.E. & Levy, J.A., 1987. "The San Francisco Men's Health Study: III. Reduction in human immunodeficiency virus transmission among homosexual/bisexual men, 1982-86," American Journal of Public Health, American Public Health Association, vol. 77(6), pages 685-689.
    3. David R. Holtgrave & Noreen L. Qualls, 1995. "Threshold Analysis and Programs for Prevention of HIV Infection," Medical Decision Making, , vol. 15(4), pages 311-317, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Doug Morrison & Oliver Laeyendecker & Ron Brookmeyer, 2022. "Regression with interval‐censored covariates: Application to cross‐sectional incidence estimation," Biometrics, The International Biometric Society, vol. 78(3), pages 908-921, September.
    2. Raji Balasubramanian & Stephen W. Lagakos, 2010. "Estimating HIV Incidence Based on Combined Prevalence Testing," Biometrics, The International Biometric Society, vol. 66(1), pages 1-10, March.
    3. Rui Wang & Stephen W. Lagakos, 2010. "Augmented Cross-Sectional Prevalence Testing for Estimating HIV Incidence," Biometrics, The International Biometric Society, vol. 66(3), pages 864-874, September.
    4. Stephen E. Chick & Sada Soorapanth & James S. Koopman, 2003. "Inferring Infection Transmission Parameters That Influence Water Treatment Decisions," Management Science, INFORMS, vol. 49(7), pages 920-935, July.
    5. Raji Balasubramanian & Stephen W. Lagakos, 2010. "Correction to article “Estimating HIV Incidence Based on Combined Prevalence Testing”," Biometrics, The International Biometric Society, vol. 66(1), pages 326-326, March.

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