Three-level global resource allocation model for hiv control: A hierarchical decision system approach.

Area of Science:

• Public Health
• Health Economics
• Operations Research

Background:

• Global organizations like The Global Fund and The World Bank are major funders of HIV prevention programs, particularly in low- and middle-income countries.
• Fund allocation often involves multiple decision-making levels with heuristic approaches, potentially leading to suboptimal resource distribution.
• Effective allocation of scarce resources is critical for maximizing the impact of HIV prevention initiatives.

Purpose of the Study:

• To develop and analyze a hierarchical mathematical optimization model for optimally allocating funds in HIV prevention programs.
• To address the inefficiencies in resource distribution caused by heuristic decision-making processes.
• To incorporate epidemiological models and current intervention practices into a resource allocation framework.

Main Methods:

• A 3-level hierarchical decision-making model was developed by integrating existing epidemiological models with practical intervention strategies.
• The model was analyzed to determine optimal resource allocation for HIV prevention programs.
• The impact of antiretroviral therapy (ART) was included in the model's analysis.

Main Results:

• The proposed hierarchical model offers a structured approach to optimize resource allocation for HIV prevention.
• Analysis revealed that including antiretroviral therapy (ART) introduces a non-convex minimization problem in the lower-level allocation variables, even with linear production functions.
• The findings highlight the complexity of optimizing resource allocation in HIV prevention when considering advanced treatment modalities.

Conclusions:

• A hierarchical mathematical optimization model can improve the efficiency of global HIV prevention fund allocation.
• The non-convex nature of the objective function when including ART necessitates advanced optimization techniques for precise resource allocation.
• Further research is needed to refine these models for practical implementation in diverse global health settings.