Increasingly intimate associations between human society and the natural environment are driving the emergence of novel pathogens, with devastating consequences for humans and animals alike. Prior to emergence, these pathogens exist within complex ecological systems that are characterized by trophic interactions between parasites, their hosts and the environment. Predicting how disturbance to these ecological systems places people and animals at risk from emerging pathogens—and the best ways to manage this—remains a significant challenge. Predictive systems ecology models are powerful tools for the reconstruction of ecosystem function but have yet to be considered for modelling infectious disease. Part of this stems from a mistaken tendency to forget about the role that pathogens play in structuring the abundance and interactions of the free-living species favoured by systems ecologists. Here, we explore how developing and applying these more complete systems ecology models at a landscape scale would greatly enhance our understanding of the reciprocal interactions between parasites, pathogens and the environment, placing zoonoses in an ecological context, while identifying key variables and simplifying assumptions that underly pathogen host switching and animal-to-human spillover risk. As well as transforming our understanding of disease ecology, this would also allow us to better direct resources in preparation for future pandemics.
J.H., D.Z. and Y.-M.L. were supported by the US Army Medical Research and Development Command under contract no. W81XWH-21-C-0001 and the Armed Forces Health Surveillance Division, Global Emerging Infections Surveillance branch (AFHSC-GEIS) award P0031_21_WR. The views, opinions and/or findings contained in this report are those of the author(s) and should not be construed as an official Department of the Army position, policy or decision unless so designated by other documentation. T.N. is supported by two grants from the Leverhulme Trust (RPG-2015-073 and RPG-2018-069). L.H.V.F. is supported by the Natural Environment Research Council (NE-J001570–1)