MULTI-OBJECTIVE MODEL EXPLORATION OF HEPATITIS C ELIMINATION IN AN AGENT-BASED MODEL OF PEOPLE WHO INJECT DRUGS.
MULTI-OBJECTIVE MODEL EXPLORATION OF HEPATITIS C ELIMINATION IN AN AGENT-BASED MODEL OF PEOPLE WHO INJECT DRUGS.
复制标题
基于代理的注射吸毒者模型中消除丙型肝炎的多目标模型探索。
DOI：
10.1109/wsc40007.2019.9004747
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Boodram,Basmattee
中科院分区：
文献类型：
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作者：
Tatara,Eric;Collier,NicholsonT;Ozik,Jonathan;Gutfraind,Alexander;Cotler,ScottJ;Dahari,Harel;Major,Marian;Boodram,Basmattee
丙型肝炎（HCV）是世界范围内慢性肝病和死亡的主要原因，注射毒品（PWID）的人是获得和传播HCV感染的最高风险。我们开发了一个基于代理的模型（ABM），以确定和优化直接作用的抗病毒（DAA）治疗规模和治疗策略，以实现世界卫生组织（WHO）到2030年消除HCV的目标。虽然DAA非常有效，但也很昂贵，因此干预策略应该平衡消除目标和干预成本。在这里，我们提出并比较了两种方法，通过进行标准模型参数扫描，并将结果与进化多目标优化算法进行比较，找到PWID治疗招募策略。进化的方法提供了一个帕累托最优的解决方案，最大限度地减少治疗费用和发病率。
Hepatitis C (HCV) is a leading cause of chronic liver disease and mortality worldwide and persons who inject drugs (PWID) are at the highest risk for acquiring and transmitting HCV infection. We developed an agent-based model (ABM) to identify and optimize direct-acting antiviral (DAA) therapy scale-up and treatment strategies for achieving the World Health Organization (WHO) goals of HCV elimination by the year 2030. While DAA is highly efficacious, it is also expensive, and therefore intervention strategies should balance the goals of elimination and the cost of the intervention. Here we present and compare two methods for finding PWID treatment enrollment strategies by conducting a standard model parameter sweep and compare the results to an evolutionary multi-objective optimization algorithm. The evolutionary approach provides a pareto-optimal set of solutions that minimizes treatment costs and incidence rates.