Zoonotic disease transmission between animals and humans is a growing risk and the agricultural context acts as a likely point of transition, with individual heterogeneity acting as an important contributor. 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 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 Susceptible-Exposed-Infected-Recovered-Dead (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 infection 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 pigeons' movement dynamics can drastically affect both the magnitude and stability of outbreaks. In addition, joint infection by multiple pathogens can have an interactive effect unobservable in single-pathogen SIR models, reflecting a non-intuitive inhibition of the outbreak. 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.

翻译：人与动物间的人畜共患疾病传播风险日益增加，农业环境作为关键传播节点，其中个体异质性发挥着重要作用。因此，理解野生动植物-家畜界面中的疾病传播动态对于降低传播风险至关重要。具体而言，奶牛场中鸽子与舍饲牛的互动可导致显著疾病传播并造成农民经济损失，同时危及家畜、邻近人群及其他野生物种。本文提出一种包含连续空间运动的新型时空多病原体模型。该模型扩展了易感-暴露-感染-康复-死亡（SEIRD）框架，同时考虑了病原体的种内与种间传播，以及鸽子在感染物扩散中起关键作用的探索-开发运动动态。除模型构建外，我们还将其实现为基于智能体的模拟方法，并利用实地经验数据研究不同生物现实场景，评估各参数对疫情传播的影响。与理论预期一致，模型预测鸽子的运动动态异质性会显著影响疫情的规模与稳定性。此外，多病原体联合感染会引发单病原体SIR模型中不可观测的交互效应，反映出一种非直观的疫情抑制现象。我们的研究结果揭示了宿主行为异质性对其病原体的影响，并为多病原体野生动植物-家畜界面中的疫情动态提供了现实预测，对各类系统中的人畜共患疾病防控具有重要启示。