Participatory System Dynamics Modeling to Simulate HIV Test-and-Treat Improvements

摘要 疾病预防控制中心越来越多地推广测试和治疗（T&T）作为预防艾滋病毒的一种有前途的方法， 通过减少社区病毒载量（CVL）或社区中所有病毒的总和来降低人群水平。然而，在这方面， T&T服务系统中的程序不充分或中断会产生级联处理。先前的努力， 模型级联没有充分解决复杂和动态的驱动器的CVL和城市一级的艾滋病毒 整个T&T连续体的服务效率。社会、行为和公共卫生科学家 越来越多地需要系统科学，如系统动力学（SD）建模，来理解和解决 动态的、复杂的问题，如艾滋病治疗级联。这项为期两年的模型开发研究，称为 “模拟艾滋病毒测试和治疗改进的扩展系统动力学建模”旨在建立 一个完整的艾滋病毒服务系统的计算和模拟模型，使用SD建模方法。 社区可以受益于参与研究人员建立这样一个模型，他们的地方T&T服务 系统，它可以阐明系统结构内的时间延迟和反馈回路， 系统行为中的非线性模式或意外后果。该模型和由此产生的 模拟工具将使不同的利益相关者了解T&T连续体作为一个整体，动态的艾滋病毒 保健系统，以确定该系统的弱点和消极驱动因素，并预测和比较未来 在没有大量资源的情况下通过模拟确定不同系统级干预方案的影响 投资我们将使用组模型构建（GMB）和多个辅助数据源，由我们的 最近资助的深入研究当地的T&T服务系统在哈特福德，CT（R 01-MH 103176），以建立 系统SD计算/模拟模型。使用专线小巴，不同的社区利益相关者将与 研究人员开发，验证和测试模型。目标是：（1）让一个社区团体参与 利益相关者（N=20）在一个迭代的，参与式的GMB过程中，开发，完善和批评一个计算 哈特福德HIV T&T服务系统的SD模型，旨在模拟CVL随时间的变化，以揭示 系统性能问题;（2）结合联合收割机GMB估计，二次数据分析（从R 01和 地方/州/国家流行病学/服务利用数据）和相关文献进行校准/参数化 并在计算SD模型中制定变量，并开发参考模式（流行趋势）， 验证整个GMB过程中的仿真模型;（3）演示SD计算的使用 模型和基于网络的模拟器应用程序作为一个试点分析和实用工具，使利益相关者能够预测 并比较不同干预方案在城市/人口水平上减少艾滋病毒CVL的影响。的SD 计算模型和模拟工具可以转移到其他城市寻求减少艾滋病毒CVL， 利用当地数据和利益相关者的意见进行修改。本研究为R 01的实现奠定了基础 测试社区利益相关者使用该工具设计长期结构性干预措施以减少CVL的研究。

ABSTRACT The CDC has increasingly promoted Test & Treat (T&T) as a promising approach to prevent HIV at the population level by reducing community viral load (CVL), or the sum of all virus in a community. However, inadequate or interrupted procedures in the T&T service system generate a treatment cascade. Prior efforts to model the cascade have inadequately addressed complex and dynamic drives of CVL and city level HIV service effectiveness across the entire T&T continuum. Social, behavioral, and public health scientists increasingly call for systems science, such as system dynamics (SD) modeling, to understand and solve dynamic, complex problems like the HIV treatment cascade. This 2-year model development study, called “Participatory System Dynamics Modeling to Simulate HIV Test-and-Treat Improvements,” is designed to build a computational and simulation model of the full HIV service system using a SD modeling approach. Communities could benefit from participating with researchers to build such a model of their local T&T service system, which can elucidate time delays and feedback loops within the structure of the system that lead to non-linear patterns or unintended consequences in the behavior of the system. This model and the resulting simulation tool would allow diverse stakeholders to understand the T&T continuum as a holistic, dynamic HIV care system, to identify weaknesses and negative drivers of the system, and to project and compare future impact of different systems level intervention options through simulation without significant resource investment. We will use group model building (GMB) and multiple secondary data sources, supported by our recently funded in-depth study of the local T&T service system in Hartford, CT (R01-MH103176), to build the SD computational/simulation model of that system. Using GMB, diverse community stakeholders will work with researchers to develop, validate, and test the model. The aims are: (1) to engage a group of community stakeholders (N=20) in an iterative, participatory GMB process to develop, refine, and critique a computational SD model of Hartford's HIV T&T service system designed to simulate CVL over time in order to uncover system performance problems; (2) to combine GMB estimates, secondary data analysis (from the R01 and local/state/national epidemiological/ service utilization data), and relevant literature to calibrate/parameterize and formulate variables in the computational SD model and develop reference modes (epidemic trends) to validate the simulation model throughout the GMB process; (3) to demonstrate use of the SD computational model and web-based simulator app as a pilot analytical and practical tool that allows stakeholders to predict and compare impacts of different intervention options to reduce HIV CVL at the city/population level. The SD computational model and simulator tool may be transferrable to other cities seeking to reduce HIV CVL with modifications using local data and stakeholder input. This study lays the foundation for an R01 implementation study to test community stakeholder use of the tool to design long-term structural interventions to reduce CVL.