Mechanistic yellow fever modelling under climate change in Brazil and beyond: information gaps and future steps
Author(s)
Type
Journal Article
Abstract
Yellow fever (YF) remains a significant public health threat in tropical regions, particularly in South America and Africa. The combined forces of climate change, land-use, urbanisation, globalisation, and insufficient surveillance and health infrastructure are driving the re-emergence and expansion of YF into new areas. While mathematical models have been used to estimate transmission risk, disease burden, and the impact of vaccination, there remains a crucial gap in mechanistic models that explicitly capture how climate and environmental changes directly influence YF transmission. To address this gap, we convened a workshop in Brazil as part of the Vaccine Impact Modelling Consortium’s Climate Change programme, bringing together national and international experts. The workshop aimed to present current modelling approaches, identify key knowledge gaps, and develop strategies to improve data collection and model applicability. Discussions highlighted major uncertainties regarding vectors, non-human primates, surveillance sensitivity, vaccination, and climatic and environmental drivers. This paper synthesises the outcomes of the workshop, including priority areas for future research and recommendations for advancing mechanistic YF modelling in the context of climate change, with a focus on both Brazil and broader tropical regions.
Date Issued
2026-03-13
Date Acceptance
2026-03-13
Citation
Wellcome Open Research, 2026, 10
ISSN
2398-502X
Publisher
Wellcome
Journal / Book Title
Wellcome Open Research
Volume
10
Copyright Statement
Copyright: © 2026 Abdalla L et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/41929637
Subjects
Yellow fever; Brazil; Mathematical modelling; Climate change; Surveillance
Publication Status
Published
Coverage Spatial
England
Article Number
596
Date Publish Online
2026-03-13