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具有人群意识的随机网络中的易感-感染-康复流行病

Susceptible-infected-recovered epidemics in random networks with population awareness.

作者信息

Wu Qingchu, Chen Shufang

机构信息

College of Mathematics and Information Science, Jiangxi Normal University, Nanchang, Jiangxi 330022, People's Republic of China.

College of Physics and Communication Electronics, Jiangxi Normal University, Nanchang, Jiangxi 330022, People's Republic of China.

出版信息

Chaos. 2017 Oct;27(10):103107. doi: 10.1063/1.4994893.

Abstract

The influence of epidemic information-based awareness on the spread of infectious diseases on networks cannot be ignored. Within the effective degree modeling framework, we discuss the susceptible-infected-recovered model in complex networks with general awareness and general degree distribution. By performing the linear stability analysis, the conditions of epidemic outbreak can be deduced and the results of the previous research can be further expanded. Results show that the local awareness can suppress significantly the epidemic spreading on complex networks via raising the epidemic threshold and such effects are closely related to the formulation of awareness functions. In addition, our results suggest that the recovered information-based awareness has no effect on the critical condition of epidemic outbreak.

摘要

基于疫情信息的意识对传染病在网络上传播的影响不容忽视。在有效度建模框架内,我们讨论了具有一般意识和一般度分布的复杂网络中的易感-感染-康复模型。通过进行线性稳定性分析,可以推导出疫情爆发的条件,并进一步扩展先前的研究结果。结果表明,局部意识可以通过提高疫情阈值显著抑制复杂网络上的疫情传播,且这种影响与意识函数的形式密切相关。此外,我们的结果表明,基于康复信息的意识对疫情爆发的临界条件没有影响。

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