Panpan Shu

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Epidemic threshold has always been a very hot topic for studying epidemic dynamics on complex networks. The previous studies have provided different theoretical predictions of the epidemic threshold for the susceptible-infected-recovered (SIR) model, but the numerical verification of these theoretical predictions is still lacking. Considering that the large(More)
Individuals are always limited by some inelastic resources, such as time and energy, which restrict them to dedicate to social interaction and limit their contact capacities. Contact capacity plays an important role in dynamics of social contagions, which so far has eluded theoretical analysis. In this paper, we first propose a non-Markovian model to(More)
Weak ties play a significant role in the structures and the dynamics of community networks. Based on the contact process, we study numerically how weak ties influence the predictability of epidemic dynamics. We first investigate the effects of the degree of bridge nodes on the variabilities of both the arrival time and the prevalence of disease, and find(More)
Heterogeneous adoption thresholds exist widely in social contagions, but were always neglected in previous studies. We first propose a non-Markovian spreading threshold model with general adoption threshold distribution. In order to understand the effects of heterogeneous adoption thresholds quantitatively, an edge-based compartmental theory is developed(More)
Accurate identification of effective epidemic threshold is essential for understanding epidemic dynamics on complex networks. In this paper, we systematically study how the recovery rate affects the susceptible-infected-removed spreading dynamics on complex networks, where synchronous and asynchronous updating processes are taken into account. We derive the(More)
In this paper, under the complex network framework, we study a seasonal influenza-like disease model by incorporating the interplay between subsidy policies and human behavioral responses. In the model a small proportion of individuals are freely vaccinated according to either the targeted or random subsidy policy in advance, while the remaining individuals(More)
Hai-Feng Zhang,1, 2, 3 Pan-Pan Shu,4 Ming Tang,4, ∗ and Michael Small5, † School of Mathematical Science, Anhui University, Hefei 230039, P. R. China Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education Department of Communication Engineering, North University of China, Taiyuan, Shan’xi 030051, P. R.(More)
  • Panpan Shu
  • 2014 IEEE 17th International Conference on…
  • 2014
Understanding human-driven dynamics has attracted increasing attention recently. Here we propose a variable information model to investigate the effects of memory on information spreading in complex networks. We find the prevalence of information can be enlarged once the individuals have memory of the states of their neighbors. Owing to the difference in(More)
Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical(More)
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