Modeling dual-scale epidemic dynamics on complex networks with reaction diffusion processes

Xiao-gang JIN; Yong MIN

doi:10.1631/jzus.C1300243

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Modeling dual-scale epidemic dynamics on complex networks with reaction diffusion processes

Computer & Automation | Updated：2022-05-19

- Modeling dual-scale epidemic dynamics on complex networks with reaction diffusion processes
- 基于反应扩散过程的复杂网络双尺度传播动力学建模
- Frontiers of Information Technology & Electronic Engineering Vol. 15, Issue 4, Pages: 265-274(2014)
- Affiliations：
  
  1.AI Institute in College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
  2.College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310024, China
- Author bio：
  
  [ "Xiao-gang JIN, E-mail: xiaogangj@cise.zju.edu.cn" ]
  Yong MIN, E-mail: myong@zju.edu.cn
- Funds：
- DOI：10.1631/jzus.C1300243
  CLC： TP39;R18
- Received：31 August 2013，
  
  Revised：2014-;3-17，
  
  Published：2014-04
- Accepted：
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Xiao-gang JIN, Yong MIN. Modeling dual-scale epidemic dynamics on complex networks with reaction diffusion processes[J]. Frontiers of Information Technology & Electronic Engineering, 2014, 15(4): 265-274.
DOI：

Xiao-gang JIN, Yong MIN. Modeling dual-scale epidemic dynamics on complex networks with reaction diffusion processes[J]. Frontiers of Information Technology & Electronic Engineering, 2014, 15(4): 265-274. DOI： 10.1631/jzus.C1300243.

摘要

研究目的

全球范围内的食物源传染病呈现出许多新的特征，包括病原体载体多样性、人与传播载体之间的复杂交互以及动力学行为的多尺度特性等。如何发展新的模型和方法来应对这些新的特征是一项关乎国计民生的重要课题。本文使用反应扩散过程，结合平均场分析，从计算机模拟和数学分析两个层面对新的传播动力学进行了建模和研究。

创新要点

经典的SIR和SIS传播模型都忽略了实际传播过程中的多尺度动力学过程，仅仅关注单一扩散行为。本文模型为多尺度复杂传播动力学的建模提供一种可行的思路。

方法提亮

利用反应扩散过程（reaction-diffusion processes），本文提出的模型简洁而又清晰地描述了复杂网络上不同尺度的传播行为，包括节点内部的增殖过程以及网络尺度的扩散过程。同时，利用平均场分析方法（mean-field analysis），为相关模型找到了数学求解的途径，从而为探索多尺度传播过程中的突现等非线性行为找到一种方法。

重要结论

（1）在多尺度动力学条件下，网络的非均匀度数分布的作用被削弱了，而节点内部的增殖机制扮演着更为重要的作用；（2）穿透效应降低了网络社团对于传播的阻碍；（3）基于双尺度的评价机制可以更准确地反映节点在传播中的重要程度。计算机模拟和数学分析均支持以上结论。

Abstract

The frequent outbreak of severe foodborne diseases (e.g.

haemolytic uraemic syndrome and

Listeriosis

) in 2011 warns of a potential threat that world trade could spread fatal pathogens (e.g.

enterohemorrhagic

Escherichia coli

). The epidemic potential from trade involves both intra-proliferation and inter-diffusion. Here

we present a worldwide vegetable trade network and a stochastic computational model to simulate global trade-mediated epidemics by considering the weighted nodes and edges of the network and the dual-scale dynamics of epidemics. We address two basic issues of network structural impact in global epidemic patterns: (1) in contrast to the prediction of heterogeneous network models

the broad variability of node degree and edge weights of the vegetable trade network do not determine the threshold of global epidemics; (2) a 'penetration effect'

by which community structures do not restrict propagation at the global scale

quickly facilitates bridging the edges between communities

and leads to synchronized diffusion throughout the entire network. We have also defined an appropriate metric that combines dual-scale behavior and enables quantification of the critical role of bridging edges in disease diffusion from widespread trading. The unusual structure mechanisms of the trade network model may be useful in producing strategies for adaptive immunity and reducing international trade frictions.

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references

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