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20102019
most citedVaccination intervention on epidemic dynamics in networks

73 citations · 151 across the 6 of their papers we have counts for

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Showing physics.soc-phShow all

6 papers · 1 filter

physics.soc-ph2019★ 29 cited

An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints

Xiao-Long Peng, Ze-Qiong Zhang, Junyuan Yang +1

Network-based epidemic models have been extensively employed to understand the spread of infectious diseases, but have generally overlooked the fact that most realistic networks ar…

physics.soc-ph2016★ 32 cited

Prevention of infectious diseases by public vaccination and individual protection

Xiao-Long Peng, Xin-Jian Xu, Michael Small +2

In the face of serious infectious diseases, governments endeavour to implement containment measures such as public vaccination at a macroscopic level. Meanwhile, individuals tend t…

physics.soc-ph2013★ 11 cited

Temporal prediction of epidemic patterns in community networks

Xiao-Long Peng, Michael Small, Xin-Jian Xu +1

Most previous studies of epidemic dynamics on complex networks suppose that the disease will eventually stabilize at either a disease-free state or an endemic one. In reality, howe…

physics.soc-ph2013★ 4 cited

Modeling nonuniversal citation distributions: the role of scientific journals

Zheng Yao, Xiao-Long Peng, Li-Jie Zhang +1

Whether a scientific paper is cited is related not only to the influence of its author(s) but also to the journal publishing it. Scientists, either proficient or tender, usually su…

physics.soc-ph2013★ 73 cited

Vaccination intervention on epidemic dynamics in networks

Xiao-Long Peng, Xin-Jian Xu, Xinchu Fu +1

Vaccination is an important measure available for preventing or reducing the spread of infectious diseases. In this paper, an epidemic model including susceptible, infected, and im…

physics.soc-ph2010★ 2 cited

Fitness-driven deactivation in network evolution

Xin-Jian Xu, Xiao-Long Peng, Michael Small +1

Individual nodes in evolving real-world networks typically experience growth and decay --- that is, the popularity and influence of individuals peaks and then fades. In this paper,…