ReviewCommunications medicine2023
Modelling to inform next-generation medical interventions for malaria prevention and treatment.
Review in Communications medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Heterogeneous mosquito exposure increasesProceedings. Biological sciences · 2024Article
- Design and selection of drug properties to increase the public health impact of next-generation seasonal malaria chemoprevention: a modelling study.The Lancet. Global health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.