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

This 2-year study is designed to build a computational and simulation model of the full HIV service system using a system dynamics (SD) modeling approach. 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 Greater Hartford, CT (R01-MH103176), to build the SD computational and simulation model of that system. Using GMB, diverse community stakeholders will work with researchers to develop, validate, and test the model. The study 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 Greater Hartford’s HIV T&T service system designed to simulate community viral load (CVL) over time in order to uncover system performance problems; (2) to combine GMB estimates, secondary data analysis, 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, through simulation, to identify weaknesses and negative drivers of the system and project and compare impacts of different systems-level intervention options to reduce 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.

Additional Information:

ICR
Margaret R. Weeks, Ph.D.
Principal Investigator

Jianghong Li, MD, MSc.
Co-Investigator

Heather Mosher, Ph.D.
Co-Investigator

Marcie Berman, Ph.D.
Research Associate

Albert Einstein School of Medicine of Yeshiva University
David Lounsbury, Ph.D.
Co-Investigator

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.