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HIV epidemic control—a model for optimal allocation of prevention and treatment resources

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  • Sabina Alistar
  • Elisa Long
  • Margaret Brandeau
  • Eduard Beck

Abstract

With 33 million people living with human immunodeficiency virus (HIV) worldwide and 2.7 million new infections occurring annually, additional HIV prevention and treatment efforts are urgently needed. However, available resources for HIV control are limited and must be used efficiently to minimize the future spread of the epidemic. We develop a model to determine the appropriate resource allocation between expanded HIV prevention and treatment services. We create an epidemic model that incorporates multiple key populations with different transmission modes, as well as production functions that relate investment in prevention and treatment programs to changes in transmission and treatment rates. The goal is to allocate resources to minimize R 0 , the reproductive rate of infection. We first develop a single-population model and determine the optimal resource allocation between HIV prevention and treatment. We extend the analysis to multiple independent populations, with resource allocation among interventions and populations. We then include the effects of HIV transmission between key populations. We apply our model to examine HIV epidemic control in two different settings, Uganda and Russia. As part of these applications, we develop a novel approach for estimating empirical HIV program production functions. Our study provides insights into the important question of resource allocation for a country’s optimal response to its HIV epidemic and provides a practical approach for decision makers. Better decisions about allocating limited HIV resources can improve response to the epidemic and increase access to HIV prevention and treatment services for millions of people worldwide. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Sabina Alistar & Elisa Long & Margaret Brandeau & Eduard Beck, 2014. "HIV epidemic control—a model for optimal allocation of prevention and treatment resources," Health Care Management Science, Springer, vol. 17(2), pages 162-181, June.
    • Handle: RePEc:kap:hcarem:v:17:y:2014:i:2:p:162-181
    DOI: 10.1007/s10729-013-9240-4
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    References listed on IDEAS

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    1. Sabina S. Alistar & Margaret L. Brandeau, 2012. "Decision Making for HIV Prevention and Treatment Scale up," Medical Decision Making, , vol. 32(1), pages 105-117, January.
    2. Zaric, G.S. & Barnett, P.G. & Brandeau, M.L., 2000. "HIV transmission and the cost-effectiveness of methadone maintenance," American Journal of Public Health, American Public Health Association, vol. 90(7), pages 1100-1111.
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    4. Arielle Lasry & Stephanie Sansom & Katherine Hicks & Vladislav Uzunangelov, 2011. "A model for allocating CDC’s HIV prevention resources in the United States," Health Care Management Science, Springer, vol. 14(1), pages 115-124, March.
    5. Gregory S. Zaric & Margaret L. Brandeau, 2001. "Optimal Investment in a Portfolio of HIV Prevention Programs," Medical Decision Making, , vol. 21(5), pages 391-408, October.
    6. Arielle Lasry & Stephanie L Sansom & Katherine A Hicks & Vladislav Uzunangelov, 2012. "Allocating HIV Prevention Funds in the United States: Recommendations from an Optimization Model," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-8, June.
    7. Margaret Brandeau & Gregory Zaric, 2009. "Optimal investment in HIV prevention programs: more is not always better," Health Care Management Science, Springer, vol. 12(1), pages 27-37, March.
    8. Anke Richter & Margaret L. Brandeau & Douglas K. Owens, 1999. "An Analysis of Optimal Resource Allocation for Prevention of Infection with Human Immunodeficiency Virus (HIV) in Injection Drug Users and Non-Users," Medical Decision Making, , vol. 19(2), pages 167-179, April.
    9. 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.
    10. Neil M. Ferguson & Derek A.T. Cummings & Simon Cauchemez & Christophe Fraser & Steven Riley & Aronrag Meeyai & Sopon Iamsirithaworn & Donald S. Burke, 2005. "Strategies for containing an emerging influenza pandemic in Southeast Asia," Nature, Nature, vol. 437(7056), pages 209-214, September.
    11. Sabina S Alistar & Douglas K Owens & Margaret L Brandeau, 2011. "Effectiveness and Cost Effectiveness of Expanding Harm Reduction and Antiretroviral Therapy in a Mixed HIV Epidemic: A Modeling Analysis for Ukraine," PLOS Medicine, Public Library of Science, vol. 8(3), pages 1-15, March.
    12. Gregory S. Zaric & Margaret L. Brandeau & Paul G. Barnett, 2000. "Methadone Maintenance and HIV Prevention: A Cost-Effectiveness Analysis," Management Science, INFORMS, vol. 46(8), pages 1013-1031, August.
    13. Sabina S. Alistar & Margaret L. Brandeau & Eduard J. Beck, 2013. "REACH: A Practical HIV Resource Allocation Tool for Decision Makers," International Series in Operations Research & Management Science, in: Gregory S. Zaric (ed.), Operations Research and Health Care Policy, edition 127, chapter 0, pages 201-223, Springer.
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    4. 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.
    5. Huo, Jingjing & Zhao, Hongyong, 2016. "Dynamical analysis of a fractional SIR model with birth and death on heterogeneous complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 41-56.
    6. Turgay Ayer & Can Zhang & Anthony Bonifonte & Anne C. Spaulding & Jagpreet Chhatwal, 2019. "Prioritizing Hepatitis C Treatment in U.S. Prisons," Operations Research, INFORMS, vol. 67(3), pages 853-873, May.

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