Open AccessSimulating system dynamics of the HIV care continuum to achieve treatment as prevention
Author(s) -
Margaret R. Weeks,
David W. Lounsbury,
Jianghong Li,
Gary B. Hirsch,
Marcie Berman,
Helena D Green,
Lucy Rohena,
Rosely Gonzalez,
Jairo M. Montezuma-Rusca,
Seja Jackson
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0230568
Subject(s) - stakeholder , process management , generalizability theory , system dynamics , service delivery framework , continuum of care , computer science , management science , knowledge management , risk analysis (engineering) , business , service (business) , health care , public relations , engineering , psychology , political science , marketing , artificial intelligence , developmental psychology , law
The continuing HIV pandemic calls for broad, multi-sectoral responses that foster community control of local prevention and care services, with the goal of leveraging high quality treatment as a means of reducing HIV incidence. Service system improvements require stakeholder input from across the care continuum to identify gaps and to inform strategic plans that improve HIV service integration and delivery. System dynamics modeling offers a participatory research approach through which stakeholders learn about system complexity and about ways to achieve sustainable system-level improvements. Via an intensive group model building process with a task force of community stakeholders with diverse roles and responsibilities for HIV service implementation, delivery and surveillance, we designed and validated a multi-module system dynamics model of the HIV care continuum, in relation to local prevention and care service capacities. Multiple sources of data were used to calibrate the model for a three-county catchment area of central Connecticut. We feature a core module of the model for the purpose of illustrating its utility in understanding the dynamics of treatment as prevention at the community level. We also describe the methods used to validate the model and support its underlying assumptions to improve confidence in its use by stakeholders for systems understanding and decision making. The model’s generalizability and implications of using it for future community-driven strategic planning and implementation efforts are discussed.