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Simulating system dynamics of the HIV care continuum to achieve treatment as prevention

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 ca...

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Autores principales: Weeks, Margaret R., Lounsbury, David W., Li, Jianghong, Hirsch, Gary, Berman, Marcie, Green, Helena D., Rohena, Lucy, Gonzalez, Rosely, Montezuma-Rusca, Jairo M., Jackson, Seja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082036/
https://www.ncbi.nlm.nih.gov/pubmed/32191771
http://dx.doi.org/10.1371/journal.pone.0230568
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author Weeks, Margaret R.
Lounsbury, David W.
Li, Jianghong
Hirsch, Gary
Berman, Marcie
Green, Helena D.
Rohena, Lucy
Gonzalez, Rosely
Montezuma-Rusca, Jairo M.
Jackson, Seja
author_facet Weeks, Margaret R.
Lounsbury, David W.
Li, Jianghong
Hirsch, Gary
Berman, Marcie
Green, Helena D.
Rohena, Lucy
Gonzalez, Rosely
Montezuma-Rusca, Jairo M.
Jackson, Seja
author_sort Weeks, Margaret R.
collection PubMed
description 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.
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spelling pubmed-70820362020-03-24 Simulating system dynamics of the HIV care continuum to achieve treatment as prevention Weeks, Margaret R. Lounsbury, David W. Li, Jianghong Hirsch, Gary Berman, Marcie Green, Helena D. Rohena, Lucy Gonzalez, Rosely Montezuma-Rusca, Jairo M. Jackson, Seja PLoS One Research Article 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. Public Library of Science 2020-03-19 /pmc/articles/PMC7082036/ /pubmed/32191771 http://dx.doi.org/10.1371/journal.pone.0230568 Text en © 2020 Weeks et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Weeks, Margaret R.
Lounsbury, David W.
Li, Jianghong
Hirsch, Gary
Berman, Marcie
Green, Helena D.
Rohena, Lucy
Gonzalez, Rosely
Montezuma-Rusca, Jairo M.
Jackson, Seja
Simulating system dynamics of the HIV care continuum to achieve treatment as prevention
title Simulating system dynamics of the HIV care continuum to achieve treatment as prevention
title_full Simulating system dynamics of the HIV care continuum to achieve treatment as prevention
title_fullStr Simulating system dynamics of the HIV care continuum to achieve treatment as prevention
title_full_unstemmed Simulating system dynamics of the HIV care continuum to achieve treatment as prevention
title_short Simulating system dynamics of the HIV care continuum to achieve treatment as prevention
title_sort simulating system dynamics of the hiv care continuum to achieve treatment as prevention
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082036/
https://www.ncbi.nlm.nih.gov/pubmed/32191771
http://dx.doi.org/10.1371/journal.pone.0230568
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