Examining Multilevel System Dynamics Affecting HIV Community Viral Load

摘要 政策制定者和医疗保健提供者越来越多地寻求广泛的、多部门的应对措施来管理、缓解、 并最终消除艾滋病毒的流行。这样的社区健康结果取决于协调一致的 高效的本地艾滋病毒检测和治疗(T&T)服务系统，以发现、治疗和维持对所有病毒的抑制 艾滋病毒携带者(PWH)。系统改进需要来自整个护理连续体的利益相关者联盟 有能力识别服务差距并制定和执行战略计划以改进服务集成 和送货。然而，这样的计划可能会受到利益相关者对系统不完整的“心理模型”的影响 影响人口健康结果的复杂性和系统动力学(SD)。具有以下功能的SD模拟模型 通过参与式模型构建进行了开发和验证，提供了概念、方法和 实现这些目标的分析工具。SD模拟建模允许社区联盟了解 系统复杂性，并确定可能影响系统改进的机制。他们可以假设 单一、多项或按顺序采取的干预措施和其他有望实现所需社区水平的行动 和公共卫生结果，然后通过模型模拟进行虚拟测试，然后再投入精力和 实施它们所需的资源。然而，需要更好地理解利益相关者 联盟可以使用SD模拟模型，模拟是否可以帮助他们设计他们拥有的战略计划 信心将改善社区一级的健康结果，以及这一进程如何增强联盟能力 来推进他们的计划。我们为期3年的研究(R01-MH103176)采用混合方法和参与式SD 建模以建立康涅狄格州哈特福德HIV T&T护理连续体的SD模型。额外资金(R21- MH110335)我们将专家知识、当地主要和次要数据以及科学证据进行三角测量 对SD模型进行标定，以进行仿真。SD模拟模型的用户界面工具允许重新校准/ 定制并启用SD建模-天真的联盟使用模拟进行战略规划。这项为期两年的续订 的新的具体目标，这些目标不在当前的 学习。采用定性和定量相结合的研究方法，文件和测量：目标1： 使用经过验证的SD模拟模型时新的利益相关者联盟的战略规划过程 艾滋病毒T&T系统，以制定预期可减少社区一级艾滋病毒的战略；目标2：比较战略 联盟在培训之前和之后以及在整个迭代使用期间设计和选择的计划 艾滋病毒技术和技术系统的可持续发展模拟模型；和目标3：联盟能力的变化，包括成员， 关系和组织能力，预计将提高其实施拟议计划的能力 实现系统的长期改进。此更新研究的结果将用于制作工具包 这将使其他社区的联盟有可能复制SD模拟建模方法 以便于在随后的实施研究中进行严格的多站点测试。

ABSTRACT Policy makers and healthcare providers increasingly seek broad, multi-sectoral responses to manage, mitigate, and eventually eliminate the HIV epidemic. Such community health outcomes depend on a coordinated and highly effective local HIV test-and-treat (T&T) service system to find, treat and maintain viral suppression in all people with HIV (PWH). System improvements require stakeholder coalitions from across the care continuum with capacity to identify service gaps and develop and carry out strategic plans to improve service integration and delivery. However, such plans may suffer from stakeholders' incomplete `mental models' of system complexity and system dynamics (SD) that affect population health outcomes. A SD simulation model that has been developed and validated through participatory model building offers conceptual, methodological and analytical tools to achieve these goals. SD simulation modeling allows community coalitions to learn about system complexity and identify mechanisms likely to affect system improvements. They can hypothesize single, multiple, or sequenced interventions and other actions expected to achieve desired community-level and public health outcomes, then test those virtually through model simulation before expending effort and resources to implement them. However better understanding is needed of the process by which stakeholder coalitions can use SD simulation models, whether simulation can help them design strategic plans they have confidence will improve community-level health outcomes, and how this process enhances coalition capacities to move their plans forward. Our 3-year study (R01-MH103176) used mixed methods and participatory SD modeling to build a SD model of the HIV T&T care continuum in Hartford, CT. With additional funding (R21- MH110335) we triangulated expert knowledge, local primary and secondary data, and scientific evidence to calibrate the SD model for simulation. User interface tools of the SD simulation model allow recalibration/ tailoring and enable SD-modeling-naïve coalitions to use simulation for strategic planning. This 2-year renewal of our current R01 will address the following new specific aims that are outside the scope of the current studies. Using mixed qualitative and quantitative research methods, document and measure: Aim 1: the strategic planning process of a new stakeholder coalition when using a validated SD simulation model of the HIV T&T system to develop strategies expected to reduce community-level HIV; Aim 2: comparative strategic plans designed and selected by the coalition before and after training in, and throughout iterative use of, the SD simulation model of the HIV T&T system; and Aim 3: changes in coalition capacities, including member, relational, and organizational capacities, expected to improve their ability to implement proposed plans to achieve long-term system improvements. Findings from this renewal study will be used to produce a Toolkit that will make possible replication of the SD simulation modeling approach by coalitions in other communities to facilitate rigorous multisite testing in a subsequent implementation study.