About: In this work, we study the evolution of the susceptible individuals during the spread of an epidemic modeled by the susceptible-infected-recovered (SIR) process spreading on the top of complex networks. Using an edge-based compartmental approach and percolation tools, we find that a time-dependent quantity [Image: see text], namely, the probability that a given neighbor of a node is susceptible at time [Image: see text], is the control parameter of a node void percolation process involving those nodes on the network not-reached by the disease. We show that there exists a critical time [Image: see text] above which the giant susceptible component is destroyed. As a consequence, in order to preserve a macroscopic connected fraction of the network composed by healthy individuals which guarantee its functionality, any mitigation strategy should be implemented before this critical time [Image: see text]. Our theoretical results are confirmed by extensive simulations of the SIR process.   Goto Sponge  NotDistinct  Permalink

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  • In this work, we study the evolution of the susceptible individuals during the spread of an epidemic modeled by the susceptible-infected-recovered (SIR) process spreading on the top of complex networks. Using an edge-based compartmental approach and percolation tools, we find that a time-dependent quantity [Image: see text], namely, the probability that a given neighbor of a node is susceptible at time [Image: see text], is the control parameter of a node void percolation process involving those nodes on the network not-reached by the disease. We show that there exists a critical time [Image: see text] above which the giant susceptible component is destroyed. As a consequence, in order to preserve a macroscopic connected fraction of the network composed by healthy individuals which guarantee its functionality, any mitigation strategy should be implemented before this critical time [Image: see text]. Our theoretical results are confirmed by extensive simulations of the SIR process.
Subject
  • Network theory
  • Percolation theory
  • Software companies based in Seattle
  • Graph invariants
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