Clark Ruaridh A, Macdonald Malcolm
Department of Electronic and Electrical Engineering, University of Strathclyde, George Street, Glasgow, UK.
Appl Netw Sci. 2021;6(1):5. doi: 10.1007/s41109-021-00351-0. Epub 2021 Jan 19.
Contact networks provide insights on disease spread due to the duration of close proximity interactions. For systems governed by consensus dynamics, network structure is key to optimising the spread of information. For disease spread over contact networks, the structure would be expected to be similarly influential. However, metrics that are essentially agnostic to the network's structure, such as weighted degree (strength) centrality and its variants, perform near-optimally in selecting effective spreaders. These degree-based metrics outperform eigenvector centrality, despite disease spread over a network being a random walk process. This paper improves eigenvector-based spreader selection by introducing the non-linear relationship between contact time and the probability of disease transmission into the assessment of network dynamics. This approximation of disease spread dynamics is achieved by altering the Laplacian matrix, which in turn highlights why nodes with a high degree are such influential disease spreaders. From this approach, a trichotomy emerges on the definition of an effective spreader where, for susceptible-infected simulations, eigenvector-based selections can either optimise the initial rate of infection, the average rate of infection, or produce the fastest time to full infection of the network. Simulated and real-world human contact networks are examined, with insights also drawn on the effective adaptation of ant colony contact networks to reduce pathogen spread and protect the queen ant.
接触网络由于近距离交互的持续时间而提供了关于疾病传播的见解。对于由共识动力学控制的系统，网络结构是优化信息传播的关键。对于通过接触网络传播的疾病，预计该结构也会有类似的影响力。然而，诸如加权度（强度）中心性及其变体等本质上与网络结构无关的指标，在选择有效传播者方面表现近乎最优。尽管疾病在网络上的传播是一个随机游走过程，但这些基于度的指标优于特征向量中心性。本文通过将接触时间与疾病传播概率之间的非线性关系引入网络动力学评估，改进了基于特征向量的传播者选择。通过改变拉普拉斯矩阵实现对疾病传播动力学的这种近似，这反过来突出了为什么高度数的节点是如此有影响力的疾病传播者。从这种方法中，在有效传播者的定义上出现了一种三分法，即在易感 - 感染模拟中，基于特征向量的选择可以优化初始感染率、平均感染率，或者产生网络完全感染的最快时间。研究了模拟的和现实世界中的人类接触网络，还探讨了蚁群接触网络为减少病原体传播和保护蚁后的有效适应性。
