Sixth International Conference on Simulation Tools and Techniques

Research Article

A Simulation-based Method for Efficient Resource Allocation of Combination HIV Prevention

  • @INPROCEEDINGS{10.4108/icst.simutools.2013.251726,
        author={Lucio Tolentino and Fei Meng and Wim Delva},
        title={A Simulation-based Method for Efficient Resource Allocation of Combination HIV Prevention},
        proceedings={Sixth International Conference on Simulation Tools and Techniques},
        publisher={ICST},
        proceedings_a={SIMUTOOLS},
        year={2013},
        month={7},
        keywords={simulation hiv individual-based modeling agent-based modeling stochastic modeling combination prevention},
        doi={10.4108/icst.simutools.2013.251726}
    }
    
  • Lucio Tolentino
    Fei Meng
    Wim Delva
    Year: 2013
    A Simulation-based Method for Efficient Resource Allocation of Combination HIV Prevention
    SIMUTOOLS
    ACM
    DOI: 10.4108/icst.simutools.2013.251726
Lucio Tolentino1,*, Fei Meng2, Wim Delva1
  • 1: Stellenbosch University
  • 2: Hasselt University
*Contact email: seanluciotolentino@gmail.com

Abstract

Over the past three decades there has been a wealth of operational research into effectively and efficiently combating human immunodeficiency virus (HIV). These interventions have had varying results. Condoms, for example, have been shown to decrease the probability of transmission per sexual act (PTSA) by 95%, but they tend to be used inconsistently. Male circumcision has been shown to reduce the PTSA by 50%, but provides consistent partial protection by design. Antiretroviral therapy (ART) is a medical treatment that slows the reproduction of HIV. ART has been associated with 96% reduction in PTSA, and has been shown to prolong the life of an infected individual. However, it is difficult to determine how to optimally distribute limited HIV prevention resources to prevention methods due to each method's different financial costs, levels of uptake and efficiency, and potential unintuitive interactions. In this paper we implement an individual-based model that simulates HIV transmission and prevention in a complex sexual network and use it to answer the question of combination prevention. Using optimization software, we find the best combination of prevention methods for a given budget and sexual network structure.