Impacts of multitype interactions on epidemic spreading in temporal networks

NingNing Dong (), YueXing Han, Qing Li () and Bing Wang
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NingNing Dong: School of Computer Engineering and Science, Shanghai University, No. 99, Shangda Rd., Shanghai, P. R. China
YueXing Han: School of Computer Engineering and Science, Shanghai University, No. 99, Shangda Rd., Shanghai, P. R. China†Shanghai Institute for Advanced Communication and Data Science, Shanghai University, No. 99, Shangda Rd., Shanghai, P. R. China
Qing Li: School of Computer Engineering and Science, Shanghai University, No. 99, Shangda Rd., Shanghai, P. R. China
Bing Wang: School of Computer Engineering and Science, Shanghai University, No. 99, Shangda Rd., Shanghai, P. R. China

International Journal of Modern Physics C (IJMPC), 2020, vol. 31, issue 01, 1-13

Abstract: Individuals have often been found to interact with each other with different intensity in a dynamical way due to their various types in real networks, which plays a fundamental role in dynamical process such as epidemic spreading. To understand the relationship between the network structure and the spreading process, we propose a kind of temporal network model which contains diverse types of individuals. Furthermore, we also assume that the transmission rate is also related to the individuals’ types. Theoretical analysis and numerical results show that the epidemic threshold is affected by several factors, such as parameters described network structure and the ratio of intra-transmission rate to inter-transmission rate. Finally, we investigate immunization strategies for the network model and propose an immunization strategy by considering the mutual effect of individual’s degree connected with the same type and those with different types. By comparing a kind of immunization strategies, we find that the proposed immunization strategy is able to suppress the outbreak with less observation time and that it is able to suppress the outbreak almost as efficient as the target immunization strategy with appropriate observation time.

Keywords: Temporal networks; epidemic spreading process; multitype interactions; complex networks (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0129183120500205

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