意识扩散和SEIR病毒的双层网络传播模型

doi:10.16182/j.issn1004731x.joss.21-0734

系统仿真学报 ›› 2022, Vol. 34 ›› Issue (11): 2437-2447.doi: 10.16182/j.issn1004731x.joss.21-0734

• 仿真模型/系统置信度评估技术 • 上一篇下一篇

意识扩散和SEIR病毒的双层网络传播模型

宋玉蓉¹(), 鲍裕霖¹, 李汝琦²

^1.南京邮电大学　自动化学院，江苏　南京　210003
^2.南京邮电大学　计算机学院，江苏　南京　210003

收稿日期:2021-07-22 修回日期:2021-11-30 出版日期:2022-11-18 发布日期:2022-11-25
作者简介:宋玉蓉(1971-)，女，博士，教授，研究方向为复杂网络传播动力学。E-mail：songyr@njupt.edu.cn
基金资助:
国家自然科学基金(61672298);江苏高校哲学社会科学研究重点项目(2018SJZDI142)

A Two-Layer Network Propagation Model of Awareness Diffusion and SEIR Epidemic

Yurong Song¹(), Yulin Bao¹, Ruqi Li²

^1.School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
^2.School of Computing, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Received:2021-07-22 Revised:2021-11-30 Online:2022-11-18 Published:2022-11-25

摘要/Abstract

摘要：

针对类似于新型冠状病毒(coronavirus disease 2019, COVID-19)具有明显潜伏期特性的病毒，为了解其传播特性，做出相应预测和措施，提出了一种考虑时变因素的双层网络传播模型。上层网络采用考虑时变遗忘概率的UAU(unaware-aware-unaware)信息传播模型表示关于病毒的意识信息扩散过程；下层网络采用具有潜伏态的SEIR(susceptible-exposed-infected-recovered)类病毒传播模型描述受意识信息影响的病毒传播过程。利用MMCA(microscopic Markov chain approach)推导出传染病传播阈值，通过分析遗忘因素、感染衰减因子等关键因素，仿真结果表明了所提考虑时变因素的双层网络传播模型的有效性。

关键词: 双层网络, 时变遗忘概率, 病毒传播, 传播阈值, 意识扩散

Abstract:

In order to understand the transmission characteristics of epidemics similar to COVID-19 (coronavirus disease 2019) with obvious expose period, a two-layer network transmission model considering time-varying factors is proposed to make corresponding predictions and measures. The UAU (unaware-aware-unaware) information transmission model is used to represent the diffusion process of conscious information about epidemic. In the underlying network, the susceptible-exposed-infected- recovered (SEIR) epidemic-like transmission model with latent state is used to describe the epidemic transmission process affected by conscious information. The MMCA (microscopic Markov chain approach) is used to deduce the transmission threshold of epidemics diseases. By analyzing the key factors such as forgetting factors and infection attenuation factors, the simulation results demonstrate the effectiveness of proposed the two-layer network transmission model considering time-varying factors proposed.

Key words: two-layer network, time-varying forgetting probability, epidemic propagation, propagation threshold, awareness diffusion

中图分类号:

TP391.9

宋玉蓉, 鲍裕霖, 李汝琦. 意识扩散和SEIR病毒的双层网络传播模型[J]. 系统仿真学报, 2022, 34(11): 2437-2447.

Yurong Song, Yulin Bao, Ruqi Li. A Two-Layer Network Propagation Model of Awareness Diffusion and SEIR Epidemic[J]. Journal of System Simulation, 2022, 34(11): 2437-2447.

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参考文献 34

[1]	Peiris J S, Guan Y, Yuen K Y. Severe Acute Respiratory Syndrome[J]. Nature Medicine (S1078-8956), 2004, 10: 588-597.
[2]	Bruce Aylward, Philippe Barboza, Luke Bawo, et al. Ebola Virus Disease in West Africa - The First 9 Months of the Epidemic and Forward Projections[J]. The New England Journal of Medicine (S0028-4793), 2014, 371(16): 1481-1495.
[3]	Smith G, Dhanasekaran V, Justin B, et al. Origins and Evolutionary Genomics of the 2009 Swine-Origin H1N1 Influenza A Epidemic[J]. Nature (S0028-0836), 2021, 7520(459): 1122.
[4]	Barabási A L, Albert R, Jeong H. Mean-field Theory for Scale-free Random Networks[J]. Physica A - Statistical Mechanics and Its Applications (S0378-4371), 1999, 272(1/2): 173-187.
[5]	Albert R, Barabási A L. Statistical Mechanics of Complex Networks[J]. Reviews of Modern Physics (S0034-6861), 2002, 74: 47.
[6]	Li Huijia, Wang Hao, Chen Luonan. Measuring Robustness of Community Structure in Complex Networks[J]. Europhysics Letters (S0295-5075), 2014, 108(6): 68009.
[7]	Dorogovtsev S N, Goltsev A V, Mendes J F F. Critical Phenomena in Complex Networks[J]. Reviews of Modern Physics (S0034-6861), 2008, 80: 1275.
[8]	Li Huijia, Daniels Jasmine J. Social Significance of Community Structure: Statistical View[J]. Physical Review E Statistical Nonlinear & Soft Matter (S1539-3755), 2015, 91(1): 012801.
[9]	Li Chao, Wang Li, Sun Shiwen, et al. Identification of Influential Spreaders Based on Classified Neighbors in Real-World Complex Networks[J]. Applied Mathematics and Computation (S0096-3003), 2018, 320: 512-523.
[10]	Herbert W Hethcote. The Mathematics of Infectious Diseases[J]. SIAM Review (S0036-1445), 2000, 42(4): 599-653.
[11]	Pastor-Satorras R, Castellano C, Mieghem P V, et al. Epidemic Processes in Complex Networks[J]. Reviews of Modern Physics (S0034-6861), 2015, 87(3): 925-979.
[12]	Boccaletti S, Latora V, Moreno Y, et al. Complex Networks: Structure and Dynamics[J]. Physics Reports (S0370-1573), 2006, 424(4/5): 175-308.
[13]	Keeling M J, Eames K. Networks and Epidemic Models[J]. Journal of the Royal Society Interface (S1742-5689), 2005, 2(4): 295-307.
[14]	Wang Zhen, Bauch C T, Bhattacharyya S, et al. Statistical Physics of Vaccination[J]. Physics Reports (S0370-1573), 2016, 664: 1-113.
[15]	Hébert-Dufresne L, Allard A, Young J, et al. Global Efficiency of Local Immunization on Complex Networks[J]. Scientific Reports (S2352-409X), 2013, 3: 2171.
[16]	Iannelli F, Koher A, Brockmann D, et al. Effective Distances for Epidemics Spreading on Complex Networks[J]. Physical Review E (S2470-0053), 2017, 95(1): 012313.
[17]	Li Huijia, Bu Zhan, Li Aihua, et al. Fast and Accurate Mining the Community Structure: Integrating Center Locating and Membership Optimization[J]. IEEE Transactions on Knowledge and Data Engineering (S0169-023X), 2016, 28(9): 2349-2362.
[18]	Pastor-Satorras R, Vespignani A. Epidemic Spreading in Scale-free Networks[J]. Physical Review Letters (S0031-9007), 2001, 86(14): 3200-3203.
[19]	Castellano C, Pastor-Satorras R. Thresholds for Epidemic Spreading in Networks[J]. Physical Review E (S2470-0053), 2010, 18(11): 218701.
[20]	柳文艳, 张玉霞. 基于复杂行为响应的传染病爆发问题的研究[J]. 复杂系统与复杂性科学, 2017, 14(1): 8-14.
	Liu Wenyan, Zhang Yuxia. The Study of Infections Disease Outbreaks Based on Complex Behavior Response[J]. Complex System and Complexity Science, 2017, 14(1): 8-14.
[21]	张强, 曹军海, 宋太亮. 基于SIRV病毒传播理论的装备保障网络级联失效分析[J]. 系统仿真学报, 2019, 31(12): 2657-2663.
	Zhang Qiang, Cao Junhai, Song Tailiang. Cascading Failure Analysis of Equipment Support Network Based on SIRV Virus Propagation Theory[J]. Journal of System Simulation, 2019, 31(12): 2657-2663.
[22]	Ferraz D, Rodrigues F A, Yamir M. Fundamentals of Spreading Processes in Single and Multilayer Complex Networks[J]. Physics Reports (S0370-1573), 2018, 756: 1-59.
[23]	Granell C, Gómez S, Arenas A. Competing Spreading Processes on Multiplex Networks: Awareness and Epidemics[J]. Physical Review E (S2470-0053), 2014, 90(1): 012808.
[24]	Zheng Chunyuan, Xia Chengyi, Guo Quantong, et al. Interplay between SIR-Based Disease Spreading and Awareness Diffusion on Multiplex Networks[J]. Journal of Parallel & Distributed Computing (S0743-7315), 2018, 115: 20-28.
[25]	Xia Chengyi, Wang Zhishuang, Zheng Chunyuan, et al. A New Coupled Disease-Awareness Spreading Model with Mass Media on Multiplex Networks[J]. Information Sciences (S0020-0255), 2019, 471: 185-200.
[26]	李盈科, 赵时. 新型冠状病毒肺炎的流行病参数与模型[J]. 物理学报, 2020, 69(9): 090202.
	Li Yingke, Zhao Shi. Epidemiological Parameters and Models of Coronavirus Disease 2019[J]. Acta Physica Sinica, 2020, 69(9): 090202.
[27]	王刚, 胡鑫, 陆世伟. 节点增减机制下的病毒传播模型及稳定性[J]. 电子科技大学学报, 2019, 48(1): 75-79.
	Wang Gang, Hu Xin, Lu Shiwei. Virus Spreading Model and Its Stability Based on the Mechanism of Node Increasing and Decreasing[J]. Journal of University of Electronic Science and Technology of China, 2019, 48(1): 75-79.
[28]	Funk S, Gilad E, Watkins C, et al. The Spread of Awareness and Its Impact on Epidemic Outbreaks[J]. Proceedings of the National Academy of Sciences of the United States of America (S0027-8424), 2009, 106(16): 6872-6877.
[29]	Wu Qingchu, Fu Xinchu, Small M, et al. The Impact of Awareness on Epidemic Spreading in Networks[J]. Chaos (S1054-1500), 2012, 22(1): 013101.
[30]	Granell C, Gomez S, Arenas A. Dynamical Interplay between Awareness and Epidemic Spreading in Multiplex Networks[J]. Physical Review Letters (S0031-9007), 2013, 111(12): 128701.
[31]	Wang Zhishuang, Guo Quantong, Sun Shiwen, et al. The Impact of Awareness Diffusion on SIR-like Epidemics in Multiplex Networks[J]. Applied Mathematics and Computation (S0096-3003), 2019, 349(5): 134-147.
[32]	Guo Quantong, Jiang Xin, Lei Yanjun, et al. Two-stage Effects of Awareness Cascade on Epidemic Spreading in Multiplex Networks[J]. Physical Review E (S2470-0053), 2015, 91(1): 012822.
[33]	Zhao Laijun, Wang Xiaoli, Qiu Xiaoyun, et al. A Model for the Spread of Rumors in Barrat-Barthelemy- Vespignani Networks[J]. Physica A-Statistical Mechanics and Its Applications (S0378-4371), 2013, 392(21): 5542-5551.
[34]	He Le, Zhu Linhe. Modeling the COVID-19 Epidemic and Awareness Diffusion on Multiplex Networks[J]. Communications in Theoretical Physics (S0253-6102), 2021, 73(3): 035002.

意识扩散和SEIR病毒的双层网络传播模型

A Two-Layer Network Propagation Model of Awareness Diffusion and SEIR Epidemic

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