title: The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness.
abstract: Exploring the interplay between information spreading and epidemic spreading is a topic that has been receiving increasing attention. As an efficient means of depicting the spreading of information, which manifests as a cascade phenomenon, awareness cascading is utilized to investigate this coupled transmission. Because in reality, different individuals facing the same epidemic will exhibit distinct behaviors according to their own experiences and attributes, it is important for us to consider the heterogeneity of individuals. Consequently, we propose a heterogeneous spreading model. To describe the heterogeneity, two of the most important but radically different methods for this purpose, the degree and k-core measures, are studied in this paper through three models based on different assumptions. Adopting a Markov chain approach, we succeed in predicting the epidemic threshold trend. Furthermore, we find that when the k-core measure is used to classify individuals, the spreading process is robust to these models, meaning that regardless of the model used, the spreading process is nearly identical at the macroscopic level. In addition, the k-core measure leads to a much larger final epidemic size than the degree measure. These results are cross-checked through numerous simulations, not only of a synthetic network but also of a real multiplex network. The presented findings provide a better understanding of k-core individuals and reveal the importance of considering network structure when investigating various dynamic processes.
authors: School of Mathematics and Systems Science, Beihang University & Key Laboratory of Mathematics Informatics Behavioral Semantics(LMIB), Beijing 100191, China.
authors: Quantong
authors: Q
authors: Guo
authors: School of Mathematics and Systems Science, Beihang University & Key Laboratory of Mathematics Informatics Behavioral Semantics(LMIB), Beijing 100191, China.|School of Mathematical Sciences, Peking University, Beijing 100191, China.
authors: Yanjun
authors: Y
authors: Lei
authors: Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384, China.|Key Laboratory of Computer Vision and System (Ministry of Education),Tianjin University of Technology, Tianjin 300384, China.
authors: Chengyi
authors: C
authors: Xia
authors: Luoyang Branch of China Construction Bank, Luoyang 471000, China.
authors: Lu
authors: L
authors: Guo
authors: School of Mathematics and Systems Science, Beihang University & Key Laboratory of Mathematics Informatics Behavioral Semantics(LMIB), Beijing 100191, China.
authors: Xin
authors: X
authors: Jiang
authors: School of Mathematics and Systems Science, Beihang University & Key Laboratory of Mathematics Informatics Behavioral Semantics(LMIB), Beijing 100191, China.|School of Mathematical Sciences, Peking University, Beijing 100191, China.
authors: Zhiming
authors: Z
authors: Zheng
mesh_terms: D058872:Epidemics; D015658:HIV Infections / Q000453:epidemiology / Q000635:transmission; D015497:HIV-1 / Q000502:physiology; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D008962:Models, Theoretical