Individual variation affects outbreak magnitude and predictability in multi-pathogen model of pigeons visiting dairy farms

Zoonotic disease transmission between animals and humans is a growing risk, and the agricultural context acts as a likely point of transition, with an important role of individual heterogeneity. Livestock often occurs at high local densities, facilitating spread within sites (e.g. among cows in a dairy farm), while wildlife is often more mobile, potentially connecting spatially isolated sites. Thus, understanding the dynamics of disease spread in the wildlife-livestock interface is crucial for mitigating these risks of transmission. Specifically, the interactions between pigeons (Columba livia, also known as ‘rock doves’) and in-door cows at dairy farms can lead to significant disease transmission and economic losses for farmers; putting livestock, adjacent human populations, and other wildlife species at risk. In this paper, we propose a novel spatio-temporal multi-pathogen model with continuous spatial movement. The model expands on the SEIRD framework and accounts for both within-species and cross-species transmission of pathogens, as well as the exploration–exploitation movement dynamics of pigeons, which play a critical role in the spread of infectious agents. In addition to model formulation, we also implement it as an agent-based simulation approach and use empirical field data to investigate different biologically realistic scenarios, evaluating the effect of various parameters on the epidemic spread. Namely, in agreement with theoretical expectations, the model predicts that the heterogeneity of the movement dynamics of pigeons (on top and beyond the obvious effect of an increase of mean level movement itself) can drastically affect both the magnitude and stability of outbreaks. In addition, joint infection by multiple pathogens can have an interactive effect, reflecting a non-intuitive inhibition of the outbreak compared to predictions from single-pathogen SIR models. Our findings highlight the impact of heterogeneity in host behavior on their pathogens and allow realistic predictions of outbreak dynamics in the multi-pathogen wildlife-livestock interface with consequences to zoonotic diseases in various systems.