Modelling to inform next-generation medical interventions for malaria prevention and treatment

Global progress against malaria has stagnated and novel medical interventions to prevent malaria are needed to fill gaps in existing tools and improve protection against infection and disease. Candidate selection for next-generation interventions should be supported by the best available evidence. Target product profiles and preferred product characteristics play a key role in setting selection criteria requirements and early endorsement by health authorities. While clinical evidence and expert opinion often inform product development decisions, integrating modelling evidence early and iteratively into this process provides an opportunity to link product characteristics with expected public health outcomes. Population models of malaria transmission can provide a better understanding of which, and at what magnitude, key intervention characteristics drive public health impact, and provide quantitative evidence to support selection of use-cases, transmission settings, and deployment strategies. We describe how modelling evidence can guide and accelerate development of new malaria vaccines, monoclonal antibodies, and chemoprevention. Nekkab, Malinga, Braunack-Mayer et al. discuss how modelling can be incorporated early on in the research and development of malaria tools alongside clinical evidence and expert opinion. In addition, population models can provide estimates of potential effectiveness of novel interventions to inform product criteria and support decision-making.

Automated summary

Global progress against malaria has stagnated, and there is a need for novel medical interventions to improve protection against infection and disease. The selection of candidates for these interventions should be evidence-based, with input from modeling evidence to link product characteristics with expected public health outcomes and inform decision-making.