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Simulating the Control of a Heterosexual HIV Epidemic in a Severely Affected East African City

Author

Listed:
  • Robert S. Bernstein

    (UNICEF JAKARTA, PO Box 5747, Grand Central Station, New York, New York 10163-5747)

  • David C. Sokal

    (Family Health International, PO Box 13950, Research Triangle Park, North Carolina 27709)

  • Steven T. Seitz

    (University of Illinois, 505 East Green Street, Champaign, Illinois 61820)

  • Bertran Auvert

    (Hospicio Nationale De St-Maurice, 94415 Saint-Maurice, France)

  • John Stover

    (The Futures Group International, 1050 17th Street, Washington, DC 20036)

  • Warren Naamara

    (PO Box 1646, Kigali, Rwanda)

Abstract

We compared three intervention strategies for preventing heterosexual transmission of the human immunodeficiency virus (HIV) using deterministic and stochastic models to simulate the epidemic of acquired immunodeficiency syndromes (AIDS). We estimated demographic, biological, and behavioral parameters for a severely affected east African city early in the epidemic, and used these parameter values in computing the spread of HIV under five scenarios: (1) a baseline scenario with no public health interventions; three single-intervention scenarios with strategies to (2) reduce the number and rate of change of sex partners, (3) increase condom use, or (4) improve treatment of sexually transmitted diseases (STD); and a (5) combined-intervention scenario. The rankings were the same in both models—decreasing partner change was most effective, followed by condom use and STD treatment. Combined interventions were more effective than single interventions. They interacted to produce impacts that varied with the trajectory of the epidemic at the onset of the interventions. Their timely, targeted, and sustained implementation appears critical to slow the epidemic significantly.

Suggested Citation

  • Robert S. Bernstein & David C. Sokal & Steven T. Seitz & Bertran Auvert & John Stover & Warren Naamara, 1998. "Simulating the Control of a Heterosexual HIV Epidemic in a Severely Affected East African City," Interfaces, INFORMS, vol. 28(3), pages 101-126, June.
    • Handle: RePEc:inm:orinte:v:28:y:1998:i:3:p:101-126
    DOI: 10.1287/inte.28.3.101
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    References listed on IDEAS

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    1. Catharina P. B. Van der Ploeg & Carina Van Vliet & Sake J. De Vlas & Jeckoniah O. Ndinya-Achola & Lieve Fransen & Gerrit J. Van Oortmarssen & J. Dik F. Habbema, 1998. "STDSIM: A Microsimulation Model for Decision Support in STD Control," Interfaces, INFORMS, vol. 28(3), pages 84-100, June.
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    Cited by:

    1. White, Leroy & Smith, Honora & Currie, Christine, 2011. "OR in developing countries: A review," European Journal of Operational Research, Elsevier, vol. 208(1), pages 1-11, January.
    2. Nadia N Abuelezam & Kathryn Rough & George R Seage III, 2013. "Individual-Based Simulation Models of HIV Transmission: Reporting Quality and Recommendations," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    3. Brandeau, Margaret L. & Zaric, Gregory S. & Richter, Anke, 2003. "Resource allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 22(4), pages 575-598, July.
    4. Suja S Rajan & David C Sokal, 2009. "Comparison of Projected and Actual Outcomes of the HIV/AIDS Epidemic in Malawi, 1990–2000," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-4, August.
    5. Linus Nyiwul, 2021. "Epidemic Control and Resource Allocation: Approaches and Implications for the Management of COVID-19," Studies in Microeconomics, , vol. 9(2), pages 283-305, December.

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