Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

doi:10.1088/1674-1056/ad1176

中国物理B ›› 2024, Vol. 33 ›› Issue (3): 38704-038704.doi: 10.1088/1674-1056/ad1176

Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

Xiao-Xiao Xie(谢笑笑)¹, Liang-An Huo(霍良安)^1,2,†, Ya-Fang Dong(董雅芳)¹, and Ying-Ying Cheng(程英英)³

1 Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;
2 School of Intelligent Emergency Management, University of Shanghai for Science and Technology, Shanghai 200093, China;
3 School of Management, Henan University of Science and Technology, Luoyang 471023, China

收稿日期:2023-09-20 修回日期:2023-10-22 接受日期:2023-12-01 出版日期:2024-02-22 发布日期:2024-03-06
通讯作者: Liang-An Huo E-mail:huohuolin@yeah.net
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos. 72174121 and 71774111), the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, and the Project for the Natural Science Foundation of Shanghai, China (Grant No. 21ZR1444100).

Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

Xiao-Xiao Xie(谢笑笑)¹, Liang-An Huo(霍良安)^1,2,†, Ya-Fang Dong(董雅芳)¹, and Ying-Ying Cheng(程英英)³

1 Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;
2 School of Intelligent Emergency Management, University of Shanghai for Science and Technology, Shanghai 200093, China;
3 School of Management, Henan University of Science and Technology, Luoyang 471023, China

Received:2023-09-20 Revised:2023-10-22 Accepted:2023-12-01 Online:2024-02-22 Published:2024-03-06
Contact: Liang-An Huo E-mail:huohuolin@yeah.net
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos. 72174121 and 71774111), the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, and the Project for the Natural Science Foundation of Shanghai, China (Grant No. 21ZR1444100).

摘要/Abstract

摘要： While the interaction between information and disease in static networks has been extensively investigated, many studies have ignored the characteristics of network evolution. In this study, we construct a new two-layer coupling model to explore the interactions between information and disease. The upper layer describes the diffusion of disease-related information, and the lower layer represents the disease transmission. We then use power-law distributions to examine the influence of asymmetric activity levels on dynamic propagation, revealing a mapping relationship characterizing the interconnected propagation of information and diseases among partial nodes within the network. Subsequently, we derive the disease outbreak threshold by using the microscopic Markov-chain approach (MMCA). Finally, we perform extensive Monte Carlo (MC) numerical simulations to verify the accuracy of our theoretical results. Our findings indicate that the activity levels of individuals in the disease transmission layer have a more significant influence on disease transmission compared with the individual activity levels in the information diffusion layer. Moreover, reducing the damping factor can delay disease outbreaks and suppress disease transmission, while improving individual quarantine measures can contribute positively to disease control. This study provides valuable insights into policymakers for developing outbreak prevention and control strategies.

关键词: information diffusion, disease transmission, asymmetric activity levels, quarantine strength

Abstract: While the interaction between information and disease in static networks has been extensively investigated, many studies have ignored the characteristics of network evolution. In this study, we construct a new two-layer coupling model to explore the interactions between information and disease. The upper layer describes the diffusion of disease-related information, and the lower layer represents the disease transmission. We then use power-law distributions to examine the influence of asymmetric activity levels on dynamic propagation, revealing a mapping relationship characterizing the interconnected propagation of information and diseases among partial nodes within the network. Subsequently, we derive the disease outbreak threshold by using the microscopic Markov-chain approach (MMCA). Finally, we perform extensive Monte Carlo (MC) numerical simulations to verify the accuracy of our theoretical results. Our findings indicate that the activity levels of individuals in the disease transmission layer have a more significant influence on disease transmission compared with the individual activity levels in the information diffusion layer. Moreover, reducing the damping factor can delay disease outbreaks and suppress disease transmission, while improving individual quarantine measures can contribute positively to disease control. This study provides valuable insights into policymakers for developing outbreak prevention and control strategies.

Key words: information diffusion, disease transmission, asymmetric activity levels, quarantine strength

中图分类号: (Dynamics of evolution)

87.23.Kg

87.23.Ge (Dynamics of social systems) 64.60.aq (Networks)

Xiao-Xiao Xie(谢笑笑), Liang-An Huo(霍良安), Ya-Fang Dong(董雅芳), and Ying-Ying Cheng(程英英). Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels[J]. 中国物理B, 2024, 33(3): 38704-038704.

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Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

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