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Optimal incentives for allocating HIV/AIDS prevention resources among multiple populations

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  • Monali Malvankar-Mehta
  • Bin Xie

Abstract

Many agencies, such as the United Nations Program on HIV/AIDS (UNAIDS), the World Health Organization (WHO), the World Bank, the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR), and the Global Fund to Fight AIDS, Tuberculosis and Malaria, provide funding to prevent HIV/AIDS infections worldwide. These funds are allocated at multiple levels, resulting in a highly complicated distribution process. An oversight agency allocates funds to various national-level decision-makers who then allocate funds to regional-level decision-makers who in turn distribute the monies to local organizations, programs, or risk groups. Simple allocation techniques are often preferred by the decision-makers at each administrative level, but such methods can lead to sub-optimal allocation of funds. Thus, incentives could be provided to decisionmakers in order to encourage optimal allocation of HIV/AIDS prevention resources. We formulate an incentive-based resource allocation model that takes into consideration strategic interactions between decision-makers in a multiple-level resource-allocation process. We analyze each decision-maker’s behavior at the equilibrium and summarize the results that characterize the optimal solution to the resource-allocation problem. Our intended audiences are technical experts, decision-makers, and policy-makers in governments who can make use of incentives to encourage effective decisions regarding HIV/AIDS policy modeling and budget allocation at local levels. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Monali Malvankar-Mehta & Bin Xie, 2012. "Optimal incentives for allocating HIV/AIDS prevention resources among multiple populations," Health Care Management Science, Springer, vol. 15(4), pages 327-338, December.
  • Handle: RePEc:kap:hcarem:v:15:y:2012:i:4:p:327-338
    DOI: 10.1007/s10729-012-9194-y
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    References listed on IDEAS

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