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Spatial and demographic dynamics of disease transfer at the wildlife-human interface

Institutions
Centre National de la Recherche Scientifique
Start date
2020
End date
2021
Objective
Infectious diseases present a significant and growing threat to public health, domestic livestock production, and biodiversity conservation. Due to their global distribution and wide-ranging movements, seabirds are important vectors for the spread of pathogens across continents and ocean basins. Coastal seabirds, which associate with and exploit anthropogenic food sources, are particularly likely to interact with human-associated pathogens and zoonotic agents, making them useful candidates for monitoring disease prevalence. However, many factors mediating the interactions between seabirds and pathogens remain unknown or poorly understood. Our study will combine targeted field data collection, laboratory analysis, and quantitative modeling to develop a mechanistic understanding of the factors affecting prevalence and transmission of infectious diseases by seabirds at the wildlife-human interface. We will explore spatial and demographic factors affecting exposure and transmission rates for two key zoonotic diseases, toxoplasmosis and avian influenza, by a generalist coastal seabird, the yellow-legged gull (Larus michahellis) in the western Mediterranean basin. Within this study system, we will combine movement analysis using biologging, serological sampling, habitat and demographic analysis, and agent-based models to develop a comprehensive understanding of epidemiological dynamics. We will also use experimental studies to directly test the development of disease immunity in nestling birds and the effects of management actions on disease transfer. We will then apply scenario planning to study the effects of both management and habitat change on disease dynamics. Our results will not only improve understanding of gulls as vectors for infectious agents, but also provide a comprehensive quantitative framework for modeling disease dynamics that can be adapted to predicting and managing the spread of infectious disease at the wildlife-human interface.
Funding Source
European Commission
Project source
View this project
Project number
843470
Categories
Bacterial Pathogens