Examining Multilevel System Dynamics Affecting HIV Community Viral Load

描述（由申请人提供）：这项为期3年的案例研究将研究影响通过促进检测和治疗（T&T）在社区一级减少艾滋病毒流行的因素。T&T策略的目的是将所有感染者的艾滋病毒病毒载量（VL）降低至无法检测到，从而降低每个人的传染性和社区病毒载量（CVL），以防止新病例。这些努力引起了人们对艾滋病毒感染者（PWH）在达到不可检测的VL之前脱离T&T连续体（称为治疗级联）的问题的新关注。尽管多部门努力应对艾滋病毒流行病，但这一流行病仍然存在，因为它很复杂，存在于一个由组织间网络结构和相互作用的社会和个人力量组成的动态系统中，这些力量产生了影响遏制这一流行病努力的非线性进程。有必要解开这些结构和动态，确定一个有科学依据的设计来组织服务网络，并建立“系统性干预措施”，以取得更好的结果。社会网络分析、系统动力学建模和混合方法人种学等系统科学方法为实现这些目标提供了概念框架和分析工具。这些系统科学方法使人们有可能了解动态过程的特点，治疗级联的观点和经验，直接参与它在多个层次的系统。本研究的主要目的是：（1）识别组织间网络因素（联系密度、集中/分散、桥梁、瓶颈、关系质量），这些因素会影响威尔斯亲王医院在整个T&T连续体中有效率和有成效地发展，方法是构建本地T&T服务机构的整体网络图;（2）考察产生非线性系统动力学的个体、组织间和社区社会结构因素（时间滞后，中断，正/负反馈，加速，逆转）的特点过渡PWH通过阶段的T&T连续使用混合方法来指定，语境化，（3）基于T&T网络和系统属性和动态的检查结果，开发一个解释性框架，该框架由一个概念性SD模型表示，该模型集成了组织网络和SD结构因素和过程，这些因素和过程共同阻碍了减少CVL的进展。本研究将在大都市哈特福德（CT）的高患病率地区进行，哈特福德是一个典型的中等规模东北城市。我们会采用混合数据收集方法（定性访谈、跨组织网络建模/分析、纵向队列调查、个案追踪、为系统模型开发和改进而进行的小组启发），以获取威尔斯亲王医院和整个T&T连续体提供者的观点和经验。研究结果将提供一个可分析推广的SD概念模型的治疗级联，可以测试，验证，并在随后的研究中复制。丰富的数据和概念模型对当地利益攸关方也具有直接的应用价值，可以制定更好的战略来减轻治疗级联。

DESCRIPTION (provided by applicant): This 3-year case study will examine factors that affect efforts to reduce the HIV epidemic at the community level through the promotion of testing and treatment (T&T). The T&T strategy was designed to reduce HIV viral load (VL) to undetectable in all infected persons, thereby lowering each person's infectivity and community viral load (CVL), in order to prevent new cases. These efforts have generated new attention to the problem of people with HIV (PWH) dropping off the T&T continuum before achieving undetectable VL, known as the treatment cascade. Despite multi-sector efforts to tackle it, the HIV epidemic endures because it is complex, embedded in a dynamic system of inter-organizational network structures and interacting social and personal forces that generate non-linear processes affecting efforts to curb the epidemic. It is necessary to unpack these structures and dynamics, identify a scientifically based design to organize service networks, and build "systemic interventions" to achieve better results. Systems science methodologies such as social network analysis, system dynamics modeling, and mixed methods ethnography offer both a conceptual framework and analytical tools to achieve these goals. These systems science methods make it possible to understand the dynamic processes that characterize the treatment cascade from the perspectives and experiences of those directly involved in it at multiple levels of the system. This study has the following aims: (1) Identify inter- organizational network factors (density of linkages, centralization/fragmentation, bridges, bottlenecks, quality of relations) that affect efficient and effective progression of PWH across the T&T continuum by constructing a whole network diagram of local T&T service organizations; (2) Examine the individual, inter-organizational, and community socio-structural factors that generate non-linear system dynamics (time lags, interruptions, positive/ negative feedback, acceleration, reversals) characterizing transitions of PWH through the stages of the T&T continuum using mixed methods to specify, contextualize, and track experiences of PWH and providers over time; and (3) Based on the results of examination of T&T network and systems properties and dynamics, develop an explanatory framework represented by a conceptual SD model that integrates organizational network and SD structural factors and processes that collectively impede progress toward reducing CVL. The study will be conducted in the high prevalence area of metropolitan Hartford, CT, a typical mid-sized, northeast city. Mixed data collection methods (qualitative interviews, inter-organizational network diagramming/analysis, longitudinal cohort survey, case tracking, group elicitation for systems model development and refinement) will be used to elicit perspectives and experiences of PWH and providers across the T&T continuum. Findings will provide an analytically generalizable SD conceptual model of the treatment cascade that can be tested, validated, and replicated in subsequent research. The rich data and the conceptual model also have immediate application value for local stakeholders to develop improved strategies to mitigate the treatment cascade.