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The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness

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  • Quantong Guo
  • Yanjun Lei
  • Chengyi Xia
  • Lu Guo
  • Xin Jiang
  • Zhiming Zheng

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.

Suggested Citation

  • Quantong Guo & Yanjun Lei & Chengyi Xia & Lu Guo & Xin Jiang & Zhiming Zheng, 2016. "The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-19, August.
  • Handle: RePEc:plo:pone00:0161037
    DOI: 10.1371/journal.pone.0161037
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    References listed on IDEAS

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    1. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
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    3. Wang, Zhigang & Zhang, Haifeng & Wang, Zhen, 2014. "Multiple effects of self-protection on the spreading of epidemics," Chaos, Solitons & Fractals, Elsevier, vol. 61(C), pages 1-7.
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    1. Fang, Fanshu & Ma, Jing & Li, Yanli, 2023. "The coevolution of the spread of a disease and competing opinions in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    2. Feng, Meiling & Liu, Lijin & Chen, Jiaxing & Xia, Chengyi, 2024. "Heterogeneous propagation processes between awareness and epidemic on signed multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    3. Gao, Chao & Tang, Shaoting & Li, Weihua & Yang, Yaqian & Zheng, Zhiming, 2018. "Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 330-338.
    4. Dong Wang & Yi Zhao & Hui Leng, 2020. "Dynamics of Epidemic Spreading in the Group-Based Multilayer Networks," Mathematics, MDPI, vol. 8(11), pages 1-15, October.
    5. Li, Ling & Dong, Gaogao & Zhu, Huaiping & Tian, Lixin, 2024. "Impact of multiple doses of vaccination on epidemiological spread in multiple networks," Applied Mathematics and Computation, Elsevier, vol. 472(C).
    6. Li, Chao & Wang, Li & Sun, Shiwen & Xia, Chengyi, 2018. "Identification of influential spreaders based on classified neighbors in real-world complex networks," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 512-523.
    7. Pan, Cheng & Yang, Lu-Xing & Yang, Xiaofan & Wu, Yingbo & Tang, Yuan Yan, 2018. "An effective rumor-containing strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 80-91.

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