title: Strategy to suppress epidemic explosion in heterogeneous metapopulation networks.
abstract: We propose an efficient strategy to suppress epidemic explosion in heterogeneous metapopulation networks, wherein each node represents a subpopulation with any number of individuals and is assigned a curing rate that is proportional to kα with the node degree k and an adjustable parameter α. We perform stochastic simulations of the dynamical reaction-diffusion processes associated with the susceptible-infected-susceptible model in scale-free networks. We find that the epidemic threshold reaches a maximum when α is tuned at αopt≃1.3. This nontrivial phenomenon is robust to the change of the network size and the average degree. In addition, we carry out a mean field analysis to further validate our scheme, which also demonstrates that epidemic explosion follows different routes for α larger or less than αopt. Our work suggests that in order to efficiently suppress epidemic spreading on heterogeneous complex networks, subpopulations with higher degrees should be allocated more resources than just being linearly dependent on k.
authors.affiliation: Hefei National Laboratory for Physical Sciences at Microscales and Department of Chemical Physics, University of Science and Technology of China, Hefei 230026, China.
authors.forename: Chuansheng
authors.initials: C
authors.lastname: Shen
authors.forename: Hanshuang
authors.initials: H
authors.lastname: Chen
authors.forename: Zhonghuai
authors.initials: Z
authors.lastname: Hou
mesh_terms: D003198:Computer Simulation; D004196:Disease Outbreaks / Q000517:prevention & control* / Q000706:statistics & numerical data*; D058872:Epidemics / Q000517:prevention & control*; D006801:Humans; D008962:Models, Theoretical; D011157:Population Dynamics