Abstract
AbstractBackgroundIn 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.ObjectiveThis study reports on a multi‐criteria decision analysis (MCDA) and its testing on CEPI decisions.MethodsConsultations 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.ResultsReviewer 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.ConclusionsDespite 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.
Highlights
Following the successful vaccine research and development (R&D) response to the 2014 West‐African Ebola epidemic (Grobusch & Goorhuis, 2017), the World Health Organization (WHO) prioritized 11 epidemic infectious diseases (EIDs) most likely to cause severe outbreaks in the near future (WHO, 2016)
The analysis focused on 18 full proposals that were selected by the Coalition for Epidemic Preparedness Innovations (CEPI) Scientific Advisory Committee (SAC) for an extended review following on an initial review of 33 preliminary proposals (CEPI, 2017a)
The uncertainty in performance means that there is substantial overlap in the confidence intervals around most proposals' performance on: the likelihood of generating a suitable vaccine for one of the call for proposals (CfP) target pathogens (O1) and on the likelihood that the platform technology will be suitable for vaccine development against new pathogens (O2)
Summary
Following the successful vaccine research and development (R&D) response to the 2014 West‐African Ebola epidemic (Grobusch & Goorhuis, 2017), the World Health Organization (WHO) prioritized 11 epidemic infectious diseases (EIDs) most likely to cause severe outbreaks in the near future (WHO, 2016). A new entity, the Coalition of Epidemic Preparedness Innovations (CEPI), was set up in 2016 with a US$1 billion investment target to support the development of vaccines, contributing to the world's preparedness for EID outbreaks (CEPI, 2016a). CEPI is faced with complex decisions that involve confronting trade‐offs between multiple objectives, diverse stakeholder perspectives, and uncertainty in vaccine performance. 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. 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. 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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