间接相互作用影响接触网络结构和扩散动力学
Indirect interactions influence contact network structure and diffusion dynamics
摘要：
在个人层面上的相互作用模式影响接触网络上的扩散行为。现有的扩散模型大多只考虑个体间的直接相互作用来构建潜在的传染性物品传播网络。然而，延迟的间接相互作用，即易感个体在感染个体离开相互作用空间后与传染性物品相互作用，也可能导致传播事件。我们定义了一个扩散模型称为相同的地方不同的时间传输（SPDT）为基础的扩散，认为这些间接的相互作用的传输链路。我们的SPDT模型改变了网络动态，其中个体之间的连接性随链接传染性的衰减率而变化。我们研究SPDT扩散行为模拟空气传播疾病的数据驱动的接触网络。SPDT模型显著增加了扩散动力学（特别是对于具有低链接密度的网络，其中间接相互作用产生新的感染途径），并且能够产生现实的疾病繁殖数。我们的结果表明，与当前具有直接相互作用的扩散模型相比，SPDT模型更有可能导致疫情爆发。我们发现，包括间接联系的扩散动力学是不可重现的，目前的模型，突出了预测疫情的间接联系的重要性。
英文摘要：
Interaction patterns at the individual level influence the behaviour of diffusion over contact networks. Most of the current diffusion models only consider direct interactions among individuals to build underlying infectious items transmission networks. However, delayed indirect interactions, where a susceptible individual interacts with infectious items after the infected individual has left the interaction space, can also cause transmission events. We define a diffusion model called the same place different time transmission (SPDT) based diffusion that considers transmission links for these indirect interactions. Our SPDT model changes the network dynamics where the connectivity among individuals varies with the decay rates of link infectivity. We investigate SPDT diffusion behaviours by simulating airborne disease spreading on data-driven contact networks. The SPDT model significantly increases diffusion dynamics (particularly for networks with low link densities where indirect interactions create new infection pathways) and is capable of producing realistic disease reproduction number. Our results show that the SPDT model is significantly more likely to lead to outbreaks compared to current diffusion models with direct interactions. We find that the diffusion dynamics with including indirect links are not reproducible by the current models, highlighting the importance of the indirect links for predicting outbreaks.
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