Application of a standardized research framework to the research priorities for high-consequence pathogens

Abstract Background The coronavirus disease 2019 (COVID-19) pandemic underscored the importance of setting health research priorities in global health. However, priority-setting for health research is complex and multidimensional, with variable practices. The WHO have therefore proposed a standardized framework for reporting and aggregating different research priority exercises – the WHO research cycle framework (WHO RCF). This article aims to evaluate how the existing practice of research prioritization of high-consequence pathogens (HCPs) aligns with such a standardized research framework. Methods This study represents a secondary data analysis of documents identified through a scoping review (SR) on research priorities for preparedness and response to HCPs. We mapped and analysed the alignment of the research priorities identified within these documents to the WHO RCF. We also analysed the linkages and overlaps between the components of the WHO RCF at the level of publications to compute the correlation matrix/coefficient to determine the strength of the association. Results We identified 720 research priorities from the 125 included articles and reports published between 1975 and 2022. These priorities mapped well to the framework’s components, with some mapping to more than one component 36% (259/720). Because the 720 priorities could receive multiple RCF classifications, 1032 discrete RCF components were generated, and “solution” accounts for most of the priorities, 39.1% (403/1032). Of the 125 publications in the scoping review, only seven papers (5.6%) gave recommendations relevant for priority-setting. Conclusions We found that the inconsistencies in research priority-setting exercises and reporting approaches make it difficult to aggregate, measure and compare prioritization results. As a methodological case study, our analysis demonstrates how retrospective mapping of heterogeneous research prioritization outputs to a standardized framework can support their aggregation, comparison, and monitoring and evaluation, while identifying areas of concentration and gaps across the research cycle.