Sagan Friant, David Simons, Christina A. Harden, Natalie Imirzian, Ottar Bjornstad, Rory Gibb, Kate Jones, Abigail Smith, Katharine E. T. Thompson, Aaron Lever, Fisayomi Aderibigbe, Wilfred A. Ayambem, Nzube M. Ifebueme, Helen Onyinyechi Ignatius, James Koninga, Martin Meremikwu, Moses Lina, David Redding
Introduction Zoonotic spillover driven by human activity remains a critical challenge. 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. Risk maps are more commonly used to inform decisions, yet their connection to local-scale drivers of transmission remains poorly understood. This study bridges these gaps through a cross-scale study of Lassa fever, a rodent-borne hemorrhagic 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 at the animal-human interface. 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. Methods and Analysis 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 exposure risk. Finally, data from these empirical studies and emergent patterns from the interface model(s) will be integrated into an existing broad-scale regression-based risk model. Together, our local-scale 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.