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A one health framework to estimate the cost of antimicrobial resistance

OBJECTIVES/PURPOSE: The costs attributable to antimicrobial resistance (AMR) remain theoretical and largely unspecified. Current figures fail to capture the full health and economic burden caused by AMR across human, animal, and environmental health; historically many studies have considered only di...

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Autores principales: Morel, Chantal M., Alm, Richard A., Årdal, Christine, Bandera, Alessandra, Bruno, Giacomo M., Carrara, Elena, Colombo, Giorgio L., de Kraker, Marlieke E. A., Essack, Sabiha, Frost, Isabel, Gonzalez-Zorn, Bruno, Goossens, Herman, Guardabassi, Luca, Harbarth, Stephan, Jørgensen, Peter S., Kanj, Souha S., Kostyanev, Tomislav, Laxminarayan, Ramanan, Leonard, Finola, Hara, Gabriel Levy, Mendelson, Marc, Mikulska, Malgorzata, Mutters, Nico T., Outterson, Kevin, Baňo, Jesus Rodriguez, Tacconelli, Evelina, Scudeller, Luigia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7689633/
https://www.ncbi.nlm.nih.gov/pubmed/33243302
http://dx.doi.org/10.1186/s13756-020-00822-6
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author Morel, Chantal M.
Alm, Richard A.
Årdal, Christine
Bandera, Alessandra
Bruno, Giacomo M.
Carrara, Elena
Colombo, Giorgio L.
de Kraker, Marlieke E. A.
Essack, Sabiha
Frost, Isabel
Gonzalez-Zorn, Bruno
Goossens, Herman
Guardabassi, Luca
Harbarth, Stephan
Jørgensen, Peter S.
Kanj, Souha S.
Kostyanev, Tomislav
Laxminarayan, Ramanan
Leonard, Finola
Hara, Gabriel Levy
Mendelson, Marc
Mikulska, Malgorzata
Mutters, Nico T.
Outterson, Kevin
Baňo, Jesus Rodriguez
Tacconelli, Evelina
Scudeller, Luigia
author_facet Morel, Chantal M.
Alm, Richard A.
Årdal, Christine
Bandera, Alessandra
Bruno, Giacomo M.
Carrara, Elena
Colombo, Giorgio L.
de Kraker, Marlieke E. A.
Essack, Sabiha
Frost, Isabel
Gonzalez-Zorn, Bruno
Goossens, Herman
Guardabassi, Luca
Harbarth, Stephan
Jørgensen, Peter S.
Kanj, Souha S.
Kostyanev, Tomislav
Laxminarayan, Ramanan
Leonard, Finola
Hara, Gabriel Levy
Mendelson, Marc
Mikulska, Malgorzata
Mutters, Nico T.
Outterson, Kevin
Baňo, Jesus Rodriguez
Tacconelli, Evelina
Scudeller, Luigia
author_sort Morel, Chantal M.
collection PubMed
description OBJECTIVES/PURPOSE: The costs attributable to antimicrobial resistance (AMR) remain theoretical and largely unspecified. Current figures fail to capture the full health and economic burden caused by AMR across human, animal, and environmental health; historically many studies have considered only direct costs associated with human infection from a hospital perspective, primarily from high-income countries. The Global Antimicrobial Resistance Platform for ONE-Burden Estimates (GAP-ON€) network has developed a framework to help guide AMR costing exercises in any part of the world as a first step towards more comprehensive analyses for comparing AMR interventions at the local level as well as more harmonized analyses for quantifying the full economic burden attributable to AMR at the global level. METHODS: GAP-ON€ (funded under the JPIAMR 8th call (Virtual Research Institute) is composed of 19 international networks and institutions active in the field of AMR. For this project, the Network operated by means of Delphi rounds, teleconferences and face-to-face meetings. The resulting costing framework takes a bottom-up approach to incorporate all relevant costs imposed by an AMR bacterial microbe in a patient, in an animal, or in the environment up through to the societal level. RESULTS: The framework itemizes the epidemiological data as well as the direct and indirect cost components needed to build a realistic cost picture for AMR. While the framework lists a large number of relevant pathogens for which this framework could be used to explore the costs, the framework is sufficiently generic to facilitate the costing of other resistant pathogens, including those of other aetiologies. CONCLUSION: In order to conduct cost-effectiveness analyses to choose amongst different AMR-related interventions at local level, the costing of AMR should be done according to local epidemiological priorities and local health service norms. Yet the use of a common framework across settings allows for the results of such studies to contribute to cumulative estimates that can serve as the basis of broader policy decisions at the international level such as how to steer R&D funding and how to prioritize AMR amongst other issues. Indeed, it is only by building a realistic cost picture that we can make informed decisions on how best to tackle major health threats.
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spelling pubmed-76896332020-11-27 A one health framework to estimate the cost of antimicrobial resistance Morel, Chantal M. Alm, Richard A. Årdal, Christine Bandera, Alessandra Bruno, Giacomo M. Carrara, Elena Colombo, Giorgio L. de Kraker, Marlieke E. A. Essack, Sabiha Frost, Isabel Gonzalez-Zorn, Bruno Goossens, Herman Guardabassi, Luca Harbarth, Stephan Jørgensen, Peter S. Kanj, Souha S. Kostyanev, Tomislav Laxminarayan, Ramanan Leonard, Finola Hara, Gabriel Levy Mendelson, Marc Mikulska, Malgorzata Mutters, Nico T. Outterson, Kevin Baňo, Jesus Rodriguez Tacconelli, Evelina Scudeller, Luigia Antimicrob Resist Infect Control Research OBJECTIVES/PURPOSE: The costs attributable to antimicrobial resistance (AMR) remain theoretical and largely unspecified. Current figures fail to capture the full health and economic burden caused by AMR across human, animal, and environmental health; historically many studies have considered only direct costs associated with human infection from a hospital perspective, primarily from high-income countries. The Global Antimicrobial Resistance Platform for ONE-Burden Estimates (GAP-ON€) network has developed a framework to help guide AMR costing exercises in any part of the world as a first step towards more comprehensive analyses for comparing AMR interventions at the local level as well as more harmonized analyses for quantifying the full economic burden attributable to AMR at the global level. METHODS: GAP-ON€ (funded under the JPIAMR 8th call (Virtual Research Institute) is composed of 19 international networks and institutions active in the field of AMR. For this project, the Network operated by means of Delphi rounds, teleconferences and face-to-face meetings. The resulting costing framework takes a bottom-up approach to incorporate all relevant costs imposed by an AMR bacterial microbe in a patient, in an animal, or in the environment up through to the societal level. RESULTS: The framework itemizes the epidemiological data as well as the direct and indirect cost components needed to build a realistic cost picture for AMR. While the framework lists a large number of relevant pathogens for which this framework could be used to explore the costs, the framework is sufficiently generic to facilitate the costing of other resistant pathogens, including those of other aetiologies. CONCLUSION: In order to conduct cost-effectiveness analyses to choose amongst different AMR-related interventions at local level, the costing of AMR should be done according to local epidemiological priorities and local health service norms. Yet the use of a common framework across settings allows for the results of such studies to contribute to cumulative estimates that can serve as the basis of broader policy decisions at the international level such as how to steer R&D funding and how to prioritize AMR amongst other issues. Indeed, it is only by building a realistic cost picture that we can make informed decisions on how best to tackle major health threats. BioMed Central 2020-11-26 /pmc/articles/PMC7689633/ /pubmed/33243302 http://dx.doi.org/10.1186/s13756-020-00822-6 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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
Morel, Chantal M.
Alm, Richard A.
Årdal, Christine
Bandera, Alessandra
Bruno, Giacomo M.
Carrara, Elena
Colombo, Giorgio L.
de Kraker, Marlieke E. A.
Essack, Sabiha
Frost, Isabel
Gonzalez-Zorn, Bruno
Goossens, Herman
Guardabassi, Luca
Harbarth, Stephan
Jørgensen, Peter S.
Kanj, Souha S.
Kostyanev, Tomislav
Laxminarayan, Ramanan
Leonard, Finola
Hara, Gabriel Levy
Mendelson, Marc
Mikulska, Malgorzata
Mutters, Nico T.
Outterson, Kevin
Baňo, Jesus Rodriguez
Tacconelli, Evelina
Scudeller, Luigia
A one health framework to estimate the cost of antimicrobial resistance
title A one health framework to estimate the cost of antimicrobial resistance
title_full A one health framework to estimate the cost of antimicrobial resistance
title_fullStr A one health framework to estimate the cost of antimicrobial resistance
title_full_unstemmed A one health framework to estimate the cost of antimicrobial resistance
title_short A one health framework to estimate the cost of antimicrobial resistance
title_sort one health framework to estimate the cost of antimicrobial resistance
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7689633/
https://www.ncbi.nlm.nih.gov/pubmed/33243302
http://dx.doi.org/10.1186/s13756-020-00822-6
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