Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks

doi:10.1109/TCSS.2023.3306014

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	Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks
	Luo, Tianyi 4; Xu, Duo 3; Cao, Zhidong 4; Zhao, Pengfei 4; Wang, Jiaojiao 4; Zhang, Qingpeng 1,2
刊名	IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
	2023-08-28
页码	13
关键词	COVID-19 heterogeneous coupling networks infectious disease transmission models information dissemination scenario modeling
ISSN号	2329-924X
DOI	10.1109/TCSS.2023.3306014
通讯作者	Cao, Zhidong(zhidong.cao@ia.ac.cn)
英文摘要	With the development of internet, transportation network, and other technologies, the transmission of information and disease presents complex and diverse new modes, which are mainly manifested as the coupling transmission of information and disease in the cyber-physical-social space. Inspired by this phenomenon, this article proposes a multilayer network-based information-behavior-disease coupling (IBDN) transmission model for the process of information diffusion-behavior change-disease transmission. The IBDN model considers various factors such as psychological drivers of information dissemination, the impact of herd mentality on behavioral transmission, the disease transmission dynamics of the current COVID-19 Omicron mutant strain and relevant countermeasures, and the interconnections between information, behavior, and disease transmission. Furthermore, within the framework of the COVID-19 Omicron mutant strain pandemic, the proposed IBDN model was leveraged to assess the effects of the propagation parameters of each layer and the interlayer coupling parameters on the magnitude of the COVID-19 outbreak and the strain on medical resources. A sensitivity analysis was carried out to determine the variability of the basic reproductive number of the Omicron mutant strains across various nations. Finally, the findings of the experiment were subjected to a thorough examination of policy implications to furnish valuable perspectives for the formulation of effective epidemic prevention strategies in the face of severe COVID-19 situation.
资助项目	New Generation Artificial Intelligence Development Plan of China[2021ZD0111205] ; National Natural Science Foundation of China[72304269] ; National Natural Science Foundation of China[62206282] ; National Natural Science Foundation of China[72025404] ; National Natural Science Foundation of China[72074209] ; National Natural Science Foundation of China[71974187] ; Beijing Natural Science Foundation[L192012] ; Beijing Nova Program[Z201100006820085]
WOS关键词	AGE-DIFFERENCES ; SOCIAL MEDIA ; DIFFUSION ; AWARENESS
WOS研究方向	Computer Science
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001060589400001
资助机构	New Generation Artificial Intelligence Development Plan of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Beijing Nova Program
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54164]
专题	舆论大数据科学与技术应用联合实验室
通讯作者	Cao, Zhidong
作者单位	1.Univ Hong Kong, LKS Fac Med, Dept Pharmacol & Pharm, Hong Kong, Peoples R China 2.Univ Hong Kong, Musketeers Fdn Inst Data Sci, Hong Kong, Peoples R China 3.Beihang Univ, Sch Math Sci, Beijing 100191, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Luo, Tianyi,Xu, Duo,Cao, Zhidong,et al. Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks[J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,2023:13.
APA	Luo, Tianyi,Xu, Duo,Cao, Zhidong,Zhao, Pengfei,Wang, Jiaojiao,&Zhang, Qingpeng.(2023).Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,13.
MLA	Luo, Tianyi,et al."Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks".IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2023):13.