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Optimal allocation of HIV prevention funds for state health departments

OBJECTIVE: To estimate the optimal allocation of Centers for Disease Control and Prevention (CDC) HIV prevention funds for health departments in 52 jurisdictions, incorporating Health Resources and Services Administration (HRSA) Ryan White HIV/AIDS Program funds, to improve outcomes along the HIV ca...

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Autores principales: Yaylali, Emine, Farnham, Paul G., Cohen, Stacy, Purcell, David W., Hauck, Heather, Sansom, Stephanie L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955542/
https://www.ncbi.nlm.nih.gov/pubmed/29768489
http://dx.doi.org/10.1371/journal.pone.0197421
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author Yaylali, Emine
Farnham, Paul G.
Cohen, Stacy
Purcell, David W.
Hauck, Heather
Sansom, Stephanie L.
author_facet Yaylali, Emine
Farnham, Paul G.
Cohen, Stacy
Purcell, David W.
Hauck, Heather
Sansom, Stephanie L.
author_sort Yaylali, Emine
collection PubMed
description OBJECTIVE: To estimate the optimal allocation of Centers for Disease Control and Prevention (CDC) HIV prevention funds for health departments in 52 jurisdictions, incorporating Health Resources and Services Administration (HRSA) Ryan White HIV/AIDS Program funds, to improve outcomes along the HIV care continuum and prevent infections. METHODS: Using surveillance data from 2010 to 2012 and budgetary data from 2012, we divided the 52 health departments into 5 groups varying by number of persons living with diagnosed HIV (PLWDH), median annual CDC HIV prevention budget, and median annual HRSA expenditures supporting linkage to care, retention in care, and adherence to antiretroviral therapy. Using an optimization and a Bernoulli process model, we solved for the optimal CDC prevention budget allocation for each health department group. The optimal allocation distributed the funds across prevention interventions and populations at risk for HIV to prevent the greatest number of new HIV cases annually. RESULTS: Both the HIV prevention interventions funded by the optimal allocation of CDC HIV prevention funds and the proportions of the budget allocated were similar across health department groups, particularly those representing the large majority of PLWDH. Consistently funded interventions included testing, partner services and linkage to care and interventions for men who have sex with men (MSM). Sensitivity analyses showed that the optimal allocation shifted when there were differences in transmission category proportions and progress along the HIV care continuum. CONCLUSION: The robustness of the results suggests that most health departments can use these analyses to guide the investment of CDC HIV prevention funds into strategies to prevent the most new cases of HIV.
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spelling pubmed-59555422018-05-25 Optimal allocation of HIV prevention funds for state health departments Yaylali, Emine Farnham, Paul G. Cohen, Stacy Purcell, David W. Hauck, Heather Sansom, Stephanie L. PLoS One Research Article OBJECTIVE: To estimate the optimal allocation of Centers for Disease Control and Prevention (CDC) HIV prevention funds for health departments in 52 jurisdictions, incorporating Health Resources and Services Administration (HRSA) Ryan White HIV/AIDS Program funds, to improve outcomes along the HIV care continuum and prevent infections. METHODS: Using surveillance data from 2010 to 2012 and budgetary data from 2012, we divided the 52 health departments into 5 groups varying by number of persons living with diagnosed HIV (PLWDH), median annual CDC HIV prevention budget, and median annual HRSA expenditures supporting linkage to care, retention in care, and adherence to antiretroviral therapy. Using an optimization and a Bernoulli process model, we solved for the optimal CDC prevention budget allocation for each health department group. The optimal allocation distributed the funds across prevention interventions and populations at risk for HIV to prevent the greatest number of new HIV cases annually. RESULTS: Both the HIV prevention interventions funded by the optimal allocation of CDC HIV prevention funds and the proportions of the budget allocated were similar across health department groups, particularly those representing the large majority of PLWDH. Consistently funded interventions included testing, partner services and linkage to care and interventions for men who have sex with men (MSM). Sensitivity analyses showed that the optimal allocation shifted when there were differences in transmission category proportions and progress along the HIV care continuum. CONCLUSION: The robustness of the results suggests that most health departments can use these analyses to guide the investment of CDC HIV prevention funds into strategies to prevent the most new cases of HIV. Public Library of Science 2018-05-16 /pmc/articles/PMC5955542/ /pubmed/29768489 http://dx.doi.org/10.1371/journal.pone.0197421 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Yaylali, Emine
Farnham, Paul G.
Cohen, Stacy
Purcell, David W.
Hauck, Heather
Sansom, Stephanie L.
Optimal allocation of HIV prevention funds for state health departments
title Optimal allocation of HIV prevention funds for state health departments
title_full Optimal allocation of HIV prevention funds for state health departments
title_fullStr Optimal allocation of HIV prevention funds for state health departments
title_full_unstemmed Optimal allocation of HIV prevention funds for state health departments
title_short Optimal allocation of HIV prevention funds for state health departments
title_sort optimal allocation of hiv prevention funds for state health departments
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955542/
https://www.ncbi.nlm.nih.gov/pubmed/29768489
http://dx.doi.org/10.1371/journal.pone.0197421
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