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Informing decision makers seeking to improve vaccination programs: case-study Serbia
Background:The optimisation of vaccine policies before their implementation is beholden upon public health decision makers, seeking to maximise population health. In this case study in Serbia, the childhood vaccines under consideration included pneumococcal conjugate vaccination (PCV), rotavirus (RV...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Routledge
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317957/ https://www.ncbi.nlm.nih.gov/pubmed/34367530 http://dx.doi.org/10.1080/20016689.2021.1938894 |
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author | Sauboin, Christophe Mihajlović, Jovan Postma, Maarten Jacobus Geets, Regine Antic, Djurdja Standaert, Baudouin |
author_facet | Sauboin, Christophe Mihajlović, Jovan Postma, Maarten Jacobus Geets, Regine Antic, Djurdja Standaert, Baudouin |
author_sort | Sauboin, Christophe |
collection | PubMed |
description | Background:The optimisation of vaccine policies before their implementation is beholden upon public health decision makers, seeking to maximise population health. In this case study in Serbia, the childhood vaccines under consideration included pneumococcal conjugate vaccination (PCV), rotavirus (RV) vaccination and varicella zoster virus (VZV) vaccination. Objective: The objective of this study is to define the optimal order of introduction of vaccines to minimise deaths, quality adjusted life years (QALYs) lost, or hospitalisation days, under budget and vaccine coverage constraints. Methods: A constrained optimisation model was developed including a static multi-cohort decision-tree model for the three infectious diseases. Budget and vaccine coverage were constrained, and to rank the vaccines, the optimal solution to the linear programming problem was based upon the ratio of the outcome (deaths, QALYs or hospitalisation days) per unit of budget. A probabilistic decision analysis Monte Carlo simulation technique was used to test the robustness of the rankings. Results: PCV was the vaccine ranked first to minimise deaths, VZV vaccination for QALY loss minimisation and RV vaccination for hospitalisation day reduction. Sensitivity analysis demonstrated the most robust ranking was that for PCV minimizing deaths. Conclusion: Constrained optimisation modelling, whilst considering all potential interventions currently, provided a comprehensive and rational approach to decision making. [Figure: see text] |
format | Online Article Text |
id | pubmed-8317957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Routledge |
record_format | MEDLINE/PubMed |
spelling | pubmed-83179572021-08-06 Informing decision makers seeking to improve vaccination programs: case-study Serbia Sauboin, Christophe Mihajlović, Jovan Postma, Maarten Jacobus Geets, Regine Antic, Djurdja Standaert, Baudouin J Mark Access Health Policy Original Research Article Background:The optimisation of vaccine policies before their implementation is beholden upon public health decision makers, seeking to maximise population health. In this case study in Serbia, the childhood vaccines under consideration included pneumococcal conjugate vaccination (PCV), rotavirus (RV) vaccination and varicella zoster virus (VZV) vaccination. Objective: The objective of this study is to define the optimal order of introduction of vaccines to minimise deaths, quality adjusted life years (QALYs) lost, or hospitalisation days, under budget and vaccine coverage constraints. Methods: A constrained optimisation model was developed including a static multi-cohort decision-tree model for the three infectious diseases. Budget and vaccine coverage were constrained, and to rank the vaccines, the optimal solution to the linear programming problem was based upon the ratio of the outcome (deaths, QALYs or hospitalisation days) per unit of budget. A probabilistic decision analysis Monte Carlo simulation technique was used to test the robustness of the rankings. Results: PCV was the vaccine ranked first to minimise deaths, VZV vaccination for QALY loss minimisation and RV vaccination for hospitalisation day reduction. Sensitivity analysis demonstrated the most robust ranking was that for PCV minimizing deaths. Conclusion: Constrained optimisation modelling, whilst considering all potential interventions currently, provided a comprehensive and rational approach to decision making. [Figure: see text] Routledge 2021-07-25 /pmc/articles/PMC8317957/ /pubmed/34367530 http://dx.doi.org/10.1080/20016689.2021.1938894 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Article Sauboin, Christophe Mihajlović, Jovan Postma, Maarten Jacobus Geets, Regine Antic, Djurdja Standaert, Baudouin Informing decision makers seeking to improve vaccination programs: case-study Serbia |
title | Informing decision makers seeking to improve vaccination programs: case-study Serbia |
title_full | Informing decision makers seeking to improve vaccination programs: case-study Serbia |
title_fullStr | Informing decision makers seeking to improve vaccination programs: case-study Serbia |
title_full_unstemmed | Informing decision makers seeking to improve vaccination programs: case-study Serbia |
title_short | Informing decision makers seeking to improve vaccination programs: case-study Serbia |
title_sort | informing decision makers seeking to improve vaccination programs: case-study serbia |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317957/ https://www.ncbi.nlm.nih.gov/pubmed/34367530 http://dx.doi.org/10.1080/20016689.2021.1938894 |
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