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Governance structure affects transboundary disease management under alternative objectives

BACKGROUND: The development of public health policy is inextricably linked with governance structure. In our increasingly globalized world, human migration and infectious diseases often span multiple administrative jurisdictions that might have different systems of government and divergent managemen...

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Autores principales: Blackwood, Julie C., Malakhov, Mykhaylo M., Duan, Junyan, Pellett, Jordan J., Phadke, Ishan S., Lenhart, Suzanne, Sims, Charles, Shea, Katriona
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487237/
https://www.ncbi.nlm.nih.gov/pubmed/34600500
http://dx.doi.org/10.1186/s12889-021-11797-3
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author Blackwood, Julie C.
Malakhov, Mykhaylo M.
Duan, Junyan
Pellett, Jordan J.
Phadke, Ishan S.
Lenhart, Suzanne
Sims, Charles
Shea, Katriona
author_facet Blackwood, Julie C.
Malakhov, Mykhaylo M.
Duan, Junyan
Pellett, Jordan J.
Phadke, Ishan S.
Lenhart, Suzanne
Sims, Charles
Shea, Katriona
author_sort Blackwood, Julie C.
collection PubMed
description BACKGROUND: The development of public health policy is inextricably linked with governance structure. In our increasingly globalized world, human migration and infectious diseases often span multiple administrative jurisdictions that might have different systems of government and divergent management objectives. However, few studies have considered how the allocation of regulatory authority among jurisdictions can affect disease management outcomes. METHODS: Here we evaluate the relative merits of decentralized and centralized management by developing and numerically analyzing a two-jurisdiction SIRS model that explicitly incorporates migration. In our model, managers choose between vaccination, isolation, medication, border closure, and a travel ban on infected individuals while aiming to minimize either the number of cases or the number of deaths. RESULTS: We consider a variety of scenarios and show how optimal strategies differ for decentralized and centralized management levels. We demonstrate that policies formed in the best interest of individual jurisdictions may not achieve global objectives, and identify situations where locally applied interventions can lead to an overall increase in the numbers of cases and deaths. CONCLUSIONS: Our approach underscores the importance of tailoring disease management plans to existing regulatory structures as part of an evidence-based decision framework. Most importantly, we demonstrate that there needs to be a greater consideration of the degree to which governance structure impacts disease outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12889-021-11797-3).
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spelling pubmed-84872372021-10-04 Governance structure affects transboundary disease management under alternative objectives Blackwood, Julie C. Malakhov, Mykhaylo M. Duan, Junyan Pellett, Jordan J. Phadke, Ishan S. Lenhart, Suzanne Sims, Charles Shea, Katriona BMC Public Health Research BACKGROUND: The development of public health policy is inextricably linked with governance structure. In our increasingly globalized world, human migration and infectious diseases often span multiple administrative jurisdictions that might have different systems of government and divergent management objectives. However, few studies have considered how the allocation of regulatory authority among jurisdictions can affect disease management outcomes. METHODS: Here we evaluate the relative merits of decentralized and centralized management by developing and numerically analyzing a two-jurisdiction SIRS model that explicitly incorporates migration. In our model, managers choose between vaccination, isolation, medication, border closure, and a travel ban on infected individuals while aiming to minimize either the number of cases or the number of deaths. RESULTS: We consider a variety of scenarios and show how optimal strategies differ for decentralized and centralized management levels. We demonstrate that policies formed in the best interest of individual jurisdictions may not achieve global objectives, and identify situations where locally applied interventions can lead to an overall increase in the numbers of cases and deaths. CONCLUSIONS: Our approach underscores the importance of tailoring disease management plans to existing regulatory structures as part of an evidence-based decision framework. Most importantly, we demonstrate that there needs to be a greater consideration of the degree to which governance structure impacts disease outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12889-021-11797-3). BioMed Central 2021-10-02 /pmc/articles/PMC8487237/ /pubmed/34600500 http://dx.doi.org/10.1186/s12889-021-11797-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Blackwood, Julie C.
Malakhov, Mykhaylo M.
Duan, Junyan
Pellett, Jordan J.
Phadke, Ishan S.
Lenhart, Suzanne
Sims, Charles
Shea, Katriona
Governance structure affects transboundary disease management under alternative objectives
title Governance structure affects transboundary disease management under alternative objectives
title_full Governance structure affects transboundary disease management under alternative objectives
title_fullStr Governance structure affects transboundary disease management under alternative objectives
title_full_unstemmed Governance structure affects transboundary disease management under alternative objectives
title_short Governance structure affects transboundary disease management under alternative objectives
title_sort governance structure affects transboundary disease management under alternative objectives
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487237/
https://www.ncbi.nlm.nih.gov/pubmed/34600500
http://dx.doi.org/10.1186/s12889-021-11797-3
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