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Optimization Models for HIV/AIDS Resource Allocation: A Systematic Review.

Anton L V Avanceña1, David W Hutton2

  • 1Department of Health Management and Policy, University of Michigan, Ann Arbor, MI, USA.

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|October 31, 2020
PubMed
Summary
This summary is machine-generated.

This review of human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) optimization models found common features but misaligned objectives. Future research should target areas with declining HIV/AIDS funding.

Keywords:
operations researchoptimizationresource allocation

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Area of Science:

  • Public Health
  • Health Economics
  • Mathematical Modeling

Background:

  • Resource allocation for human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) is critical for effective intervention.
  • Optimization models offer a framework for maximizing the impact of limited resources in HIV/AIDS programs.
  • Previous reviews have not systematically synthesized the characteristics and objectives of these optimization models.

Purpose of the Study:

  • To systematically review and synthesize optimization models for HIV/AIDS resource allocation.
  • To identify common characteristics, objectives, and variations among existing models.
  • To assess the alignment of model objectives with global HIV/AIDS goals.

Main Methods:

  • A systematic literature search was conducted across two databases for peer-reviewed articles published from January 1985 to August 2019.
  • Articles describing optimization models for HIV/AIDS resource allocation, considering at least two competing interventions, were included.
  • Data extraction focused on model characteristics, interventions, study populations, and optimization objectives. Mathematical disease transmission models were assessed for quality.

Main Results:

  • Twenty-three articles utilizing 14 unique optimization models were included in the qualitative synthesis.
  • Common features included dynamic transmission modeling, focus on high-risk groups, and exploration of prevention and treatment interventions.
  • Models predominantly focused on sub-Saharan Africa and the United States, with minimizing HIV incidence as the most common objective, though objectives varied and did not consistently align with global targets.

Conclusions:

  • Optimization models for HIV/AIDS resource allocation share common features but exhibit variability in objectives.
  • A notable divergence exists between the objectives of reviewed models and established global HIV/AIDS goals.
  • Future research should prioritize the development and application of optimization models in regions experiencing significant reductions in HIV/AIDS funding.