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.

项目概要/摘要美国人类免疫缺陷病毒（HIV）感染者数量已逐渐减少从 1990 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 HIV 的时间更长、更接近正常寿命。然而，近年来，新感染艾滋病病毒的人数并没有减少，几乎稳定在自 20 世纪 90 年代末以来，每年有 50,000 人。获得性免疫缺陷综合症（艾滋病）导致的死亡率由于有效的抗逆转录病毒治疗，相关原因已经减少，据估计，艾滋病毒感染者可以某些可能导致死亡的非传染性疾病的风险较高。此外，治疗的终生成本 HIV感染者接受ART治疗的费用非常高，从25万美元到40万美元不等。因此，重要的是要识别预防新感染的最佳投资策略，这将减少未来与艾滋病毒相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有助于减少新感染的干预措施（干预组合）。美国国家艾滋病毒/艾滋病 2015 年战略 (NHAS) 提出了到 2020 年新感染病例比 2010 年减少 25% 的目标。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未来类似的策略。它特别提出推进发展的理论理念用于疾病传播接触动力学个体级模拟的新颖结构和算法（目标 1），构建一个新的基于主体的决策分析模型，用于动态评估美国的艾滋病毒干预措施（Aim 2）、开发和实施用于评估和识别最佳干预的新算法美国艾滋病毒预防组合（目标 3）。在这个“大数据”和分析这些数据的计算能力的时代数据、开发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信息，否则无法通过任何方式推断出这些信息数据源独立，可以显着改进决策分析模型的使用，以评估国家疾病预防策略。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和未来的干预分析。通过目标 1 获得的理论知识也可以为开发新发传染病爆发期间实时决策分析的新方法，与之前的疾病爆发类似，例如埃博拉病毒病或中东呼吸综合症。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Progression and transmission of HIV (PATH 4.0)-A new agent-based evolving network simulation for modeling HIV transmission clusters.

HIV 的进展和传播 (PATH 4.0) - 一种新的基于代理的进化网络模拟，用于对 HIV 传播集群进行建模。

DOI：
发表时间：
2021-03-03
期刊：
影响因子：
0
作者：
Singh, Sonza;France, Anne Marie;Chen, Yao;Farnham, Paul G;Oster, Alexandra M;Gopalappa, Chaitra
通讯作者：
Gopalappa, Chaitra

Evaluating the sensitivity of jurisdictional heterogeneity and jurisdictional mixing in national level HIV prevention analyses: context of the U.S. ending the HIV epidemic plan.

评估国家级艾滋病毒预防分析中管辖区异质性和管辖区混合的敏感性：美国终止艾滋病毒流行计划的背景。

DOI：
发表时间：
2022-11-26
期刊：
影响因子：
4
作者：
Tatapudi, Hanisha;Gopalappa, Chaitra
通讯作者：
Gopalappa, Chaitra

Simulation of Full HIV Cluster Networks in a Nationally Representative Model Indicates Intervention Opportunities.

在全国代表性模型中模拟完整的艾滋病毒集群网络表明了干预机会。

DOI：
发表时间：
2024-04-01
期刊：
影响因子：
0
作者：
France, Anne Marie;Panneer, Nivedha;Farnham, Paul G;Oster, Alexandra M;Viguerie, Ale;Gopalappa, Chaitra
通讯作者：
Gopalappa, Chaitra

Agent-based evolving network modeling: a new simulation method for modeling low prevalence infectious diseases.

基于代理的演化网络建模：一种低流行传染病建模的新模拟方法。

DOI：
发表时间：
2021-09
期刊：
影响因子：
3.6
作者：
Eden, Matthew;Castonguay, Rebecca;Munkhbat, Buyannemekh;Balasubramanian, Hari;Gopalappa, Chaitra
通讯作者：
Gopalappa, Chaitra

A reinforcement learning model to inform optimal decision paths for HIV elimination.

强化学习模型，为消除艾滋病毒的最佳决策路径提供信息。