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Effects of delayed recovery and nonuniform transmission on the spreading of diseases in complex networks
Authors:Cheng-yi Xia  Zhen Wang  Joaquin Sanz  Sandro Meloni  Yamir Moreno
Institution:1. Key Laboratory of Computer Vision and System (Ministry of Education), Tianjin University of Technology, Tianjin 300384, PR China;2. Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384, PR China;3. Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, 50018 Zaragoza, Spain;4. Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong;5. Center for Nonlinear Studies and the Beijing-Hong Kong-Singapore Joint Center for Nonlinear and Complex Systems (Hong Kong) Baptist University, Kowloon Tong, Hong Kong;6. Department of Theoretical Physics, University of Zaragoza, 50009 Zaragoza, Spain
Abstract:We investigate the effects of delaying the time to recovery (delayed recovery) and of nonuniform transmission on the propagation of diseases on structured populations. Through a mean-field approximation and large-scale numerical simulations, we find that postponing the transition from the infectious to the recovered states can largely reduce the epidemic threshold, therefore promoting the outbreak of epidemics. On the other hand, if we consider nonuniform transmission among individuals, the epidemic threshold increases, thus inhibiting the spreading process. When both mechanisms are at work, the latter might prevail, hence resulting in an increase of the epidemic threshold with respect to the standard case, in which both ingredients are absent. Our findings are of interest for a better understanding of how diseases propagate on structured populations and to a further design of efficient immunization strategies.
Keywords:Disease spreading  Complex networks  SIS model  Heterogeneous mean-field approach
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