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Prioritizing investments in new vaccines against epidemic infectious diseases: A multi‐criteria decision analysis

BACKGROUND: In 2016, the Coalition for Epidemic Preparedness Innovations (CEPI) launched a call for proposals (CfP) for vaccine development against Lassa, MERS, and Nipah. CEPI is faced with complex decisions that involve confronting trade‐offs between multiple objectives, diverse stakeholder perspe...

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Autores principales: Gouglas, Dimitrios, Marsh, Kevin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7168397/
http://dx.doi.org/10.1002/mcda.1683
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author Gouglas, Dimitrios
Marsh, Kevin
author_facet Gouglas, Dimitrios
Marsh, Kevin
author_sort Gouglas, Dimitrios
collection PubMed
description BACKGROUND: In 2016, the Coalition for Epidemic Preparedness Innovations (CEPI) launched a call for proposals (CfP) for vaccine development against Lassa, MERS, and Nipah. CEPI is faced with complex decisions that involve confronting trade‐offs between multiple objectives, diverse stakeholder perspectives, and uncertainty in vaccine performance. OBJECTIVE: This study reports on a multi‐criteria decision analysis (MCDA) and its testing on CEPI decisions. METHODS: Consultations with CEPI's Scientific Advisory Committee (SAC) and document reviews helped identify and structure the criteria against which to evaluate proposals. Forty four subject‐matter experts assessed performance of 18 proposals on multiple criteria. SAC preferences were elicited via a survey employing an adapted swing‐weighting technique and were incorporated into measures of value and cost‐to‐value. A Monte Carlo simulation estimated overall value and ranking probabilities by value and by cost‐to‐value for each proposal. RESULTS: Reviewer assessments and SAC preferences varied significantly. Despite this uncertainty, 14 preferred proposals emerged from the analysis and SAC recommendations on the basis of value and cost‐to‐value. In some cases, SAC recommendations deviated from the analysis because of: less emphasis on cost‐to‐value if budgets seemed underestimated by applicants, more emphasis on the likelihood of generating vaccines for target pathogens versus platform potential against unknown pathogens, and emphasis on funding a diversity of platforms per pathogen. CONCLUSIONS: Despite vaccine performance uncertainty and stakeholder preference heterogeneity, MCDA distinguished between options in a way that broadly corresponded to decisions. Divergence between the MCDA and the SAC point to potential updates needed to the model such as platform diversity trade‐offs.
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spelling pubmed-71683972020-04-20 Prioritizing investments in new vaccines against epidemic infectious diseases: A multi‐criteria decision analysis Gouglas, Dimitrios Marsh, Kevin Journal of Multi‐Criteria Decision Analysis Research Articles BACKGROUND: In 2016, the Coalition for Epidemic Preparedness Innovations (CEPI) launched a call for proposals (CfP) for vaccine development against Lassa, MERS, and Nipah. CEPI is faced with complex decisions that involve confronting trade‐offs between multiple objectives, diverse stakeholder perspectives, and uncertainty in vaccine performance. OBJECTIVE: This study reports on a multi‐criteria decision analysis (MCDA) and its testing on CEPI decisions. METHODS: Consultations with CEPI's Scientific Advisory Committee (SAC) and document reviews helped identify and structure the criteria against which to evaluate proposals. Forty four subject‐matter experts assessed performance of 18 proposals on multiple criteria. SAC preferences were elicited via a survey employing an adapted swing‐weighting technique and were incorporated into measures of value and cost‐to‐value. A Monte Carlo simulation estimated overall value and ranking probabilities by value and by cost‐to‐value for each proposal. RESULTS: Reviewer assessments and SAC preferences varied significantly. Despite this uncertainty, 14 preferred proposals emerged from the analysis and SAC recommendations on the basis of value and cost‐to‐value. In some cases, SAC recommendations deviated from the analysis because of: less emphasis on cost‐to‐value if budgets seemed underestimated by applicants, more emphasis on the likelihood of generating vaccines for target pathogens versus platform potential against unknown pathogens, and emphasis on funding a diversity of platforms per pathogen. CONCLUSIONS: Despite vaccine performance uncertainty and stakeholder preference heterogeneity, MCDA distinguished between options in a way that broadly corresponded to decisions. Divergence between the MCDA and the SAC point to potential updates needed to the model such as platform diversity trade‐offs. John Wiley and Sons Inc. 2019-07-01 2019 /pmc/articles/PMC7168397/ http://dx.doi.org/10.1002/mcda.1683 Text en © 2019 The Authors Journal of Multi-Criteria Decision Analysis Published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Gouglas, Dimitrios
Marsh, Kevin
Prioritizing investments in new vaccines against epidemic infectious diseases: A multi‐criteria decision analysis
title Prioritizing investments in new vaccines against epidemic infectious diseases: A multi‐criteria decision analysis
title_full Prioritizing investments in new vaccines against epidemic infectious diseases: A multi‐criteria decision analysis
title_fullStr Prioritizing investments in new vaccines against epidemic infectious diseases: A multi‐criteria decision analysis
title_full_unstemmed Prioritizing investments in new vaccines against epidemic infectious diseases: A multi‐criteria decision analysis
title_short Prioritizing investments in new vaccines against epidemic infectious diseases: A multi‐criteria decision analysis
title_sort prioritizing investments in new vaccines against epidemic infectious diseases: a multi‐criteria decision analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7168397/
http://dx.doi.org/10.1002/mcda.1683
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