Effects of network temporality on coevolution spread epidemics in higher-order network

作者全名："Nie, Yanyi; Zhong, Xiaoni; Wu, Tao; Liu, Yanbing; Lin, Tao; Wang, Wei"

作者地址："[Nie, Yanyi; Wang, Wei] Chongqing Med Univ, Sch Publ Hlth & Management, Chongqing, Peoples R China; [Nie, Yanyi; Zhong, Xiaoni; Lin, Tao] Sichuan Univ, Coll Comp Sci, Chengdu, Peoples R China; [Wu, Tao] Chongqing Univ Posts & Telecommun, Sch Cybersecur & Informat Law, Chongqing, Peoples R China; [Liu, Yanbing] Chongqing Med Univ, Chongqing, Peoples R China"

通信作者："Wang, W (通讯作者)，Chongqing Med Univ, Sch Publ Hlth & Management, Chongqing, Peoples R China.; Lin, T (通讯作者)，Sichuan Univ, Coll Comp Sci, Chengdu, Peoples R China."

来源：JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES

ESI学科分类：　

WOS号：WOS:000836431200009

JCR分区：Q1

影响因子：6.9

年份：2022

卷号：34

期号：6

开始页：2871

结束页：2882

文献类型：Article

关键词：Network temporality; Higher-order social network; Coevolution epidemics spreading; Simplicial complexes

摘要："Interactions between people, including pairwise and higher-order interactions, can be approximated as temporal higher-order networks, where the connections are constantly created and broken over time. Meanwhile, in nature, multiple contagion processes, such as epidemics spreading, are co-evolutionary and exhibit synergistic, competitive, and asymmetric interactions. Traditional research focused on pairwise temporal effects on the single spreading dynamics. How the network temporality affects the coevolution epidemic spread on the higher-order network remains to be investigated. This paper presents a coevolution epidemics spread model on a temporal higher-order social network, which considers synergistic, competitive, and asymmetric interactions. The temporality of the network can facilitate and inhibit the transmission dynamics of different interaction patterns are drawn through a microscopic Markov Chain approach. The intensity of epidemic infection refers to the combined effect of the epidemic's infection rate and the promoting (or suppressing) effect of another epidemic. The network temporality promotes spread when the intensity of epidemic infection is at its maximum. In the study of synergistic spread, the network temporality is found to weaken the effect of initial infection density on outbreak thresholds. As the strength of network temporality diminishes, experimental results show that the higher the initial density, the smaller the outbreak threshold. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University."

基金机构："Social Science Foundation of Chongqing [2021PY53]; Natural Science Foundation of Chongqing [cstc2021jcyj-msxmX0132]; Natural Science Foundation of Yuzhong District, Chongqing [20210117]; National Natural Science Foundation of China [61903266]"

基金资助正文："This work was partially supported by the Social Science Foundation of Chongqing (No. 2021PY53), Natural Science Foundation of Chongqing (No. cstc2021jcyj-msxmX0132), Natural Science Foundation of Yuzhong District, Chongqing (No. 20210117), and National Natural Science Foundation of China under Grants (No. 61903266)."