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

传输(电信) 联轴节(管道) 疾病 爆发 计算机科学 扩散 大流行 信息级联 过程(计算) 电信 计算机安全 模拟 分布式计算 医学 2019年冠状病毒病(COVID-19) 工程类 心理学 物理 社会心理学 病毒学 传染病(医学专业) 机械工程 病理 热力学 操作系统
作者
Tianyi Luo,Duo Xu,Zhidong Cao,Pengfei Zhao,Jiaojiao Wang,Qingpeng Zhang
出处
期刊:IEEE Transactions on Computational Social Systems [Institute of Electrical and Electronics Engineers]
卷期号:: 1-13 被引量:1
标识
DOI:10.1109/tcss.2023.3306014
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.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
隐形曼青应助milos采纳,获得10
1秒前
1秒前
張肉肉发布了新的文献求助10
2秒前
Yallabo发布了新的文献求助200
3秒前
qwertyu111发布了新的文献求助10
3秒前
ethanxiang发布了新的文献求助20
5秒前
Lurant完成签到,获得积分10
6秒前
复杂的茉莉完成签到,获得积分10
6秒前
6秒前
6秒前
眼睛大的冰蓝完成签到,获得积分10
7秒前
8秒前
沐晴完成签到,获得积分10
10秒前
tsumugi发布了新的文献求助10
10秒前
hk发布了新的文献求助10
11秒前
12秒前
Owen应助冬不拉的红糖纸采纳,获得10
12秒前
ding应助Hoolyshit采纳,获得10
12秒前
12秒前
刘骁萱完成签到 ,获得积分10
13秒前
鲤鱼灵波完成签到,获得积分20
14秒前
15秒前
谢天遇你发布了新的文献求助10
15秒前
15秒前
深情安青应助直率的珍采纳,获得10
16秒前
大意的小小完成签到 ,获得积分10
16秒前
璩qu发布了新的文献求助10
17秒前
量子星尘发布了新的文献求助10
19秒前
Orange应助吴华余采纳,获得10
19秒前
19秒前
科研通AI6应助小新采纳,获得10
19秒前
了晨完成签到 ,获得积分10
20秒前
scjgf完成签到 ,获得积分10
20秒前
脑洞疼应助qwertyu111采纳,获得10
20秒前
20秒前
满意的伊发布了新的文献求助10
22秒前
香蕉觅云应助心信鑫采纳,获得10
23秒前
无奈的大门完成签到,获得积分20
23秒前
ebby发布了新的文献求助10
23秒前
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Washback Research in Language Assessment:Fundamentals and Contexts 400
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5469534
求助须知:如何正确求助?哪些是违规求助? 4572619
关于积分的说明 14336346
捐赠科研通 4499426
什么是DOI,文献DOI怎么找? 2465098
邀请新用户注册赠送积分活动 1453599
关于科研通互助平台的介绍 1428091