Authors
Sagan Friant, David Simons, Christina Harden, Natalie Imirzian, Ottar Bjornstad, Rory Gibb, Kate Jones, Abigail Smith, Katharine Thompson, Aaron Lever, Fisayomi Aderibigbe, Wilfred Ayambem, Nzube Ifebueme, Helen Ignatius, James Koninga, Martin Meremikwu, Lina Moses, David Redding
Published in
Wellcome open research. Volume 11. Pages 125. Epub Jul 28, 2026.
Abstract
Zoonotic spillover driven by human activity remains a critical challenge to human health. Research focusing on disease ecology or human-animal interactions provides detailed local insights, but these findings are often siloed and disconnected from global processes and policy. Broad-scale maps of predicted disease risk are more commonly used to inform decisions, yet their connection to local-scale drivers of pathogen transmission remains poorly understood. This study bridges these gaps through a cross-scale study of Lassa fever, a rodent-borne haemorrhagic fever of public health significance in West Africa and a WHO priority pathogen. We use a fine-scale quantitative and participatory modelling approach that explicitly integrates into broad-scale risk models to identify the patterns and processes that drive spillover within human-driven ecosystems. Lassa fever epidemics are dominated by endemic and seasonal transmission of Mammarenavirus lassaense (LASV) from rodent reservoirs to humans within a rural context, positioning LASV as a uniquely tractable system in which to study zoonotic spillover.
We describe parallel longitudinal observational studies of humans, rodents, and landscapes that are explicitly designed to feed into a cross-scale quantitative modelling framework. By integrating data on landcover, rodent dynamics, human behavior, and LASV infection, we examine how anthropogenic activities shape LASV ecology and human exposure. These data will inform spatial models of the human-rodent-LASV interface to predict key drivers of human exposure risk. Emergent patterns from these models will then be integrated into an existing broad-scale regression-based risk model, extending fine scale mechanism to regional prediction. Together, our empirical research and model predictions will clarify how zoonotic risk propagates from local to regional scales, providing evidence to inform disease management efforts for Lassa fever and zoonotic spillover more broadly.
PMID:
42723767
Bibliographic data and abstract were imported from PubMed on 11 Sep 2026.
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