在访问奶牛场的鸽子的扩展多病原体SIR模型中，个体差异影响暴发规模与可预测性
Individual Variation Affects Outbreak Magnitude and Predictability in an Extended Multi-Pathogen SIR Model of Pigeons Vising Dairy Farms
AI总结：
本研究针对奶牛场鸽子与家畜的人兽共患病传播问题，构建纳入个体移动异质性的多病原体时空扩展SEIRD模型并开展智能体仿真，发现个体差异影响暴发规模与稳定性，多病原共存存在非直观抑制效应，可为交界区域疫病预测提供支撑。
摘要：
动物与人类之间的人兽共患病传播风险正不断上升，农业环境是这类传播的潜在高发场景，而个体异质性是重要的影响因素。因此，理解野生动物-家畜交界区域的疾病传播动态，对于降低这类传播风险至关重要。具体而言，奶牛场中鸽子与圈养奶牛的互动会造成显著的疾病传播，给养殖户带来经济损失，同时也将家畜、周边人群及其他野生物种置于风险之中。\n本文提出了一种具备连续空间移动特性的新型时空多病原体模型。该模型基于易感-暴露-感染-恢复-死亡（SEIRD）框架扩展而来，既考虑病原体的种内传播，也考虑跨物种传播，同时纳入了对感染媒介传播起关键作用的鸽子的“探索-利用”移动动态。除了模型构建，我们还将其实现为基于智能体的仿真方法，并利用实地实测数据探究不同的生物学真实场景，评估各类参数对疫病传播的影响。\n研究结果与理论预期一致：模型预测鸽子移动动态的异质性会显著影响疫病暴发的规模与稳定性。此外，多种病原体的联合感染会产生单病原体SIR模型中无法观测到的交互效应，体现为一种反直觉的暴发抑制作用。本研究结果凸显了宿主行为异质性对其携带病原体的影响，可为多病原体共存的野生动物-家畜交界区域的暴发动态提供符合实际的预测，对各类系统中的人兽共患病防控具有参考意义。
英文摘要：
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.
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