Impact of heterogeneous human activities on epidemic spreading |
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Authors: | Zimo Yang Ai-Xiang Cui Tao Zhou |
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Institution: | 1. School of Computer Science And Technology, Zhejiang University, Hangzhou, 310024, PR China;2. Institute for Intelligent Robots, Fudan University, Shanghai, 200000, PR China;3. School of Information Science and Technology, Nantong University, Nantong, 226019, PR China;4. College of Artificial Intelligence and Big Data, Shandong First Medical University & Shandong Academy of Medical Sciences, Shandong, 271099, PR China;5. School of Engineering, Westlake University, Hangzhou 310024, PR China |
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Abstract: | Recent empirical observations suggest a heterogeneous nature of human activities. The heavy-tailed inter-event time distribution at the population level is well accepted, while whether the individual acts in a heterogeneous way is still under debate. Motivated by the impact of temporal heterogeneity of human activities on epidemic spreading, this paper studies the susceptible-infected model on a fully mixed population, where each individual acts in a completely homogeneous way but different individuals have different mean activities. Extensive simulations show that the heterogeneity of activities at the population level remarkably affects the speed of spreading, even though each individual behaves regularly. Furthermore, the spreading speed of this model is more sensitive to the change of system heterogeneity compared with the model consisted of individuals acting with heavy-tailed inter-event time distributions. This work refines our understanding of the impact of heterogeneous human activities on epidemic spreading. |
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