权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Evaluating Portfolio Interventions for HIV Incidence Reduction in the United States: Development of a Novel Agent-Based Decision-Analytic Model for Dynamic Evaluations of Interventions

评估美国减少艾滋病毒发病率的组合干预措施：开发基于代理的新型决策分析模型，用于干预措施的动态评估

基本信息

批准号：
10217960
负责人：
Chaitra Gopalappa
金额：
$ 30.39万
依托单位：
UNIVERSITY OF MASSACHUSETTS AMHERST
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-15 至 2024-06-30
项目状态：
已结题

项目摘要

Project Summary/Abstract The number of people living with the human immunodeficiency virus (HIV) in the United States has been gradually increasing from 800,000 in the late 1990's to 1.2 million by 2011. This is partially due to HIV-infected persons living longer and closer to normal life years on highly-active antiretroviral therapy (ART) treatment for HIV. However, the number of persons becoming newly infected with HIV has not decreased in recent years, it has been stable at almost 50,000 persons each year since the late 1990's. While mortality due to acquired immune deficiency syndrome (AIDS) related causes have been decreasing because of effective ART treatment, it is estimated that persons with HIV could be at a higher risk of certain non-communicable diseases that could lead to mortality. Further, the lifetime costs of treating an HIV-infected person on ART is very high, ranging from USD 250,000 to USD 400,000. Thus, it is important to identify optimal investment strategies for the prevention of new infections, which will reduce future HIV-related disease burden and costs. The overall goal of the project is to identify population-specific cost-effective combinations of care and behavioral intervention measures (intervention portfolios) that would help reduce new infections. The U.S. National HIV/AIDS Strategy (NHAS), 2015, proposes a goal of a 25% reduction in new infections by year 2020 compared to 2010. The analyses from this proposal would inform the development of a national strategy for achieving the NHAS goal for 2020 and similar such strategies in the future. It specifically proposes to advance theoretical concepts for the development of novel structure and algorithms for individual-level simulation of contact dynamics for disease spread (Aim 1), construction of a new agent-based decision-analytic model for dynamic evaluations of HIV interventions in the US (Aim 2), and development and implementation of new algorithms for evaluation and identification of optimal intervention portfolios for HIV prevention in the US (Aim 3). In this age of `big data' and computational power for analyzing these data, development of innovative methodologies for simulating the complicated dynamics of disease spread, and integrating disparate data sources to derive significant information that otherwise cannot be inferred through any of the data sources independently, could significantly improve use of decision-analytic models for evaluation of national strategies for disease prevention. Models can also further inform data collection for more accurate design of models and intervention analyses in the future. The theoretical knowledge gained through Aim 1 could also be foundational for the development of new methodologies for real-time decision-analyses during outbreak of emerging infectious diseases, similar to previous disease outbreaks such as Ebola-virus Disease or the Middle-Eastern Respiratory Syndrome.

项目总结/摘要美国感染人类免疫缺陷病毒（HIV）的人数已逐渐减少从90年代末的80万增加到2011年的120万。这部分是由于艾滋病毒感染者生活在接受高效抗逆转录病毒疗法（ART）治疗艾滋病毒的寿命更长，更接近正常寿命。但最近几年，新感染艾滋病毒的人数没有减少，一直稳定在几乎自20世纪90年代末以来，每年有5万人。虽然由于获得性免疫缺陷综合症（艾滋病）由于有效的抗逆转录病毒治疗，相关原因一直在减少，据估计，艾滋病毒感染者可能在某些可能导致死亡的非传染性疾病的风险更高。此外，治疗癌症的终身成本艾滋病毒感染者接受抗逆转录病毒治疗的费用很高，从25万美元到40万美元不等。因此，重要的是要确定预防新感染的最佳投资战略，这将减少未来与艾滋病毒有关的疾病负担和成本。该项目的总体目标是确定特定人群的护理和行为的成本效益组合，干预措施（干预组合）将有助于减少新的感染。美国国家艾滋病毒/艾滋病 2015年《国家艾滋病战略》提出了到2020年将新感染病例比2010年减少25%的目标。的对该提案的分析将为制定实现2020年NHAS目标的国家战略提供信息以及类似的策略。它特别提出要为发展新的结构和算法，用于疾病传播的接触动力学的个体级模拟（目标1），构建一个新的基于主体的决策分析模型，用于对美国艾滋病干预措施进行动态评估（Aim 2）、开发和实施新的算法，用于评估和识别最佳干预措施美国艾滋病预防项目组合（目标3）。在这个“大数据”和计算能力的时代，数据，开发用于模拟疾病传播复杂动态的创新方法，以及整合不同的数据源，以获得重要的信息，否则无法通过任何数据来源独立，可以大大改善决策分析模型的使用，疾病预防战略。模型还可以进一步为数据收集提供信息，以便更准确地设计模型，未来的干预分析。通过目标1获得的理论知识也可以成为在新出现的传染病爆发期间，制定新的实时决策分析方法，类似于以前的疾病爆发，如埃博拉病毒病或中东呼吸综合征。