The use of economic evidence to prioritise vaccines and delivery strategies to optimally use in immunisation systems is becoming a global priority, especially in low- and middle-income countries (LMICs), in view of challenges in funding and the need to make more efficient use of available resources. We undertook a scoping review to identify and synthesise available evidence on strategies that have been used to enhance the use of economic evidence in policy and decision-making in the immunisation ecosystem in LMICs. The review was also used to identify the facilitators and constraints to the use of economic evidence for vaccination policy and decision making in LMICs and the sustainability of the identified strategies.

A scoping literature review was undertaken to generate the evidence. The review adhered to the first five steps of Arksey and O’Malley’s methodological framework (identifying and refining the research questions, identifying relevant articles, selection of studies, data extraction and charting and data synthesis) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews.

Full-text articles were searched on PUBMED, HINARI and DOAJ using different combinations of search words as of 16 December 2024

We included articles from LMICs, including Africa, and global experiences, including those from LMICs. Papers must be written in English or have an English language translation available and published between 1 January 2004 and 16 December 2024.

Two independent reviewers used standardised methods to search, extract, and screen included studies. The findings from the review were summarized in themes that were synthesized qualitatively.

18 eligible articles met the inclusion criteria and were included in the synthesis. It was found that economic evidence was systematically requested and demonstrably influencing vaccine introduction or prioritisation decisions in only eight out of 32 LMIC settings with functional National Immunization Technical Advisory Groups (NITAGs) and in fewer than 20% of documented new vaccine introduction processes since 2015. In the majority of cases, decisions were reported as being driven primarily by disease burden, political priority, donor recommendations or historical precedent, with economic analyses either absent, produced post hoc or acknowledged but not used as a decisive factor.

There is minimal use of evidence from economics in decision-making within the immunisation ecosystem. Expert advisory committees in LMICS can, however, enhance the use of economic evidence in vaccination policy and decision-making. Hence, in order to use economic evidence for decision making, national advisory committees such as NITAGs need enhanced capacity, independence and close collaboration with researchers. LMIC NITAGs could also benefit from tailored adaptations, such as simplified cost-effectiveness tools and regional economic data hubs, to bridge this gap in decision-making and bring economic evidence to the fore of their decisions.

Different malaria control measures are deployed simultaneously in endemic settings globally, with varying impacts on malaria burden. In sub-Saharan Africa, which bears the greatest burden of malaria, evidence on the impact of implementing various control interventions on malaria immunity remains unknown. This systematic review seeks to collate evidence on the extent of progression from uncomplicated to severe malaria among populations in sub-Saharan Africa settings receiving concurrent deployment of various malaria control measures.

The review will use a priori criteria contained in the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. An experienced librarian (AAK) will independently search for articles from the following databases: PubMed, Web of Science, Embase, Scopus and Google Scholar. Boolean operators ‘AND’ and ‘OR’ will be used in the article search. Identified articles will be managed using EndNote. Article screening for inclusion and data extraction will be done in duplicate by two reviewers (EJO, and BM). Data extraction tools will be developed and customised in Excel. Data will be analysed using both narrative and quantitative synthesis. The level of heterogeneity between study outcomes will be measured using the I² statistic. Subgroup analysis will be conducted to explore heterogeneity and establish the impact of different control interventions on progression from uncomplicated to severe malaria. A full systematic review and meta-analysis is expected to be ready for dissemination by the end of December 2025.

This study did not involve human participants and so ethical approval was not sought. A full review and a meta-analysis will be published in a peer-reviewed journal and presented at national and international conferences.

CRD 42024619945.