...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computers & Industrial Engineering >Stochastic dynamic resource allocation for HIV prevention and treatment: An approximate dynamic programming approach
【24h】

Stochastic dynamic resource allocation for HIV prevention and treatment: An approximate dynamic programming approach

机译：用于艾滋病毒预防和治疗的随机动态资源分配：一种近似的动态规划方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Human immunodeficiency virus (HIV) is a key global health concern, with 33 million people living with HIV worldwide and 2.7 million new infections occurring annually. To prevent the spread of this widely prevalent epidemic disease, prevention and treatment intervention strategies urgently need to be implemented. The goal of this study is to propose stochastic dynamic programming (SDP) and approximate dynamic programming (ADP) algorithms that will optimally allocate the limited intervention budget among the HIV disease compartments and determine the best set of interventions that should be applied to each disease compartment, while minimizing the number of HIV-infected and people diagnosed with acquired immune deficiency syndrome (AIDS) as well as related deaths over a multi-year planning horizon. A compartmental model is constructed and formulated as a nonstationary Markov decision process (MDP) in order to capture the progression of the disease among the highest risk group—African American/black men who have sex with men (BMSM). In order to alleviate the computational difficulties arising from the exponentially growing state space in the SDP, we propose ADP algorithms that determine the approximately optimal budget allocation policies over six years. Our results suggest a greater allocation of the limited budget to prevention measures rather than treatment interventions, such as antiretroviral therapy (ART). As opposed to traditional policies that allocate the budget only once at the beginning of the time horizon, the ADP model suggests using a dynamic proportional budget strategy, allocating the budget dynamically over a multi-period planning period as the uncertainty in disease transmission is revealed. Results show that our ADP approach provides significant increases in health benefits and cost savings in HIV prevention and intervention.
机译：人体免疫机能丧失病毒（HIV）是全球关注的主要健康问题，全世界有3300万人感染艾滋病毒，每年有270万例新感染。为了防止这种广泛流行的流行病的传播，迫切需要执行预防和治疗干预策略。这项研究的目的是提出随机动态规划（SDP）和近似动态规划（ADP）算法，以最佳地在HIV疾病区隔中分配有限的干预预算，并确定应应用于每个疾病区隔的最佳干预措施集，同时在多年的规划范围内，将艾滋病毒感染者和诊断为获得性免疫缺陷综合症（AIDS）以及相关死亡的人数降至最低。构建隔室模型并将其制定为非平稳的马尔可夫决策过程（MDP），以捕获疾病的发展过程，以了解高风险人群-与男性发生性关系的非洲裔美国人/黑人（BMSM）。为了缓解SDP中状态空间呈指数增长的计算难题，我们提出了ADP算法，该算法可确定六年内的近似最佳预算分配策略。我们的结果表明，将有限的预算更多地分配给预防措施，而不是像抗逆转录病毒疗法（ART）这样的治疗干预措施。与传统的政策只在时间范围开始时分配一次预算相反，ADP模型建议使用动态比例预算策略，因为揭示了疾病传播的不确定性，因此可以在多个时期的计划期内动态分配预算。结果表明，我们的ADP方法可显着提高健康效益，并节省艾滋病毒的预防和干预费用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号