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Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand
BACKGROUND: With the challenges that dengue fever (DF) presents to healthcare systems and societies, public health officials must determine where best to allocate scarce resources and restricted budgets. Constrained optimization (CO) helps to address some of the acknowledged limitations of conventio...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080389/ https://www.ncbi.nlm.nih.gov/pubmed/33906628 http://dx.doi.org/10.1186/s12889-021-10747-3 |
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author | Knerer, Gerhart Currie, Christine S. M. Brailsford, Sally C. |
author_facet | Knerer, Gerhart Currie, Christine S. M. Brailsford, Sally C. |
author_sort | Knerer, Gerhart |
collection | PubMed |
description | BACKGROUND: With the challenges that dengue fever (DF) presents to healthcare systems and societies, public health officials must determine where best to allocate scarce resources and restricted budgets. Constrained optimization (CO) helps to address some of the acknowledged limitations of conventional health economic analyses and has typically been used to identify the optimal allocation of resources across interventions subject to a variety of constraints. METHODS: A dynamic transmission model was developed to predict the number of dengue cases in Thailand at steady state. A CO was then applied to identify the optimal combination of interventions (release of Wolbachia-infected mosquitoes and paediatric vaccination) within the constraints of a fixed budget, set no higher than cost estimates of the current vector control programme, to minimize the number of dengue cases and disability-adjusted life years (DALYs) lost. Epidemiological, cost, and effectiveness data were informed by national data and the research literature. The time horizon was 10 years. Scenario analyses examined different disease management and intervention costs, budget constraints, vaccine efficacy, and optimization time horizon. RESULTS: Under base-case budget constraints, the optimal coverage of the two interventions to minimize dengue incidence was predicted to be nearly equal (Wolbachia 50%; paediatric vaccination 49%) with corresponding coverages under lower bound (Wolbachia 54%; paediatric vaccination 10%) and upper bound (Wolbachia 67%; paediatric vaccination 100%) budget ceilings. Scenario analyses indicated that the most impactful situations related to the costs of Wolbachia and paediatric vaccination with decreases/ increases in costs of interventions demonstrating a direct correlation with coverage (increases/ decreases) of the respective control strategies under examination. CONCLUSIONS: Determining the best investment strategy for dengue control requires the identification of the optimal mix of interventions to implement in order to maximize public health outcomes, often under fixed budget constraints. A CO model was developed with the objective of minimizing dengue cases (and DALYs lost) over a 10-year time horizon, within the constraints of the estimated budgets for vector control in the absence of vaccination and Wolbachia. The model provides a tool for developing estimates of optimal coverage of combined dengue control strategies that minimize dengue burden at the lowest budget. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-10747-3. |
format | Online Article Text |
id | pubmed-8080389 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80803892021-04-29 Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand Knerer, Gerhart Currie, Christine S. M. Brailsford, Sally C. BMC Public Health Research Article BACKGROUND: With the challenges that dengue fever (DF) presents to healthcare systems and societies, public health officials must determine where best to allocate scarce resources and restricted budgets. Constrained optimization (CO) helps to address some of the acknowledged limitations of conventional health economic analyses and has typically been used to identify the optimal allocation of resources across interventions subject to a variety of constraints. METHODS: A dynamic transmission model was developed to predict the number of dengue cases in Thailand at steady state. A CO was then applied to identify the optimal combination of interventions (release of Wolbachia-infected mosquitoes and paediatric vaccination) within the constraints of a fixed budget, set no higher than cost estimates of the current vector control programme, to minimize the number of dengue cases and disability-adjusted life years (DALYs) lost. Epidemiological, cost, and effectiveness data were informed by national data and the research literature. The time horizon was 10 years. Scenario analyses examined different disease management and intervention costs, budget constraints, vaccine efficacy, and optimization time horizon. RESULTS: Under base-case budget constraints, the optimal coverage of the two interventions to minimize dengue incidence was predicted to be nearly equal (Wolbachia 50%; paediatric vaccination 49%) with corresponding coverages under lower bound (Wolbachia 54%; paediatric vaccination 10%) and upper bound (Wolbachia 67%; paediatric vaccination 100%) budget ceilings. Scenario analyses indicated that the most impactful situations related to the costs of Wolbachia and paediatric vaccination with decreases/ increases in costs of interventions demonstrating a direct correlation with coverage (increases/ decreases) of the respective control strategies under examination. CONCLUSIONS: Determining the best investment strategy for dengue control requires the identification of the optimal mix of interventions to implement in order to maximize public health outcomes, often under fixed budget constraints. A CO model was developed with the objective of minimizing dengue cases (and DALYs lost) over a 10-year time horizon, within the constraints of the estimated budgets for vector control in the absence of vaccination and Wolbachia. The model provides a tool for developing estimates of optimal coverage of combined dengue control strategies that minimize dengue burden at the lowest budget. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-10747-3. BioMed Central 2021-04-27 /pmc/articles/PMC8080389/ /pubmed/33906628 http://dx.doi.org/10.1186/s12889-021-10747-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Knerer, Gerhart Currie, Christine S. M. Brailsford, Sally C. Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand |
title | Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand |
title_full | Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand |
title_fullStr | Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand |
title_full_unstemmed | Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand |
title_short | Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand |
title_sort | reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to thailand |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080389/ https://www.ncbi.nlm.nih.gov/pubmed/33906628 http://dx.doi.org/10.1186/s12889-021-10747-3 |
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