Heterogeneous recovery rates against SIS epidemics in directed networks

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2 Citations (Scopus)


The nodes in communication networks are possibly and most likely equipped with different recovery resources, which allow them to recover from a virus with different rates. In this paper, we aim to understand know how to allocate the limited recovery resources to efficiently prevent the spreading of epidemics. We study the susceptible-infected-susceptible (SIS) epidemic model on directed scale-free networks. In the classic SIS model, a susceptible node can be infected by an infected neighbor with the infection rate β and an infected node can be recovered to be susceptible again with the recovery rate δ. In the steady state a fraction y of nodes are infected, which shows how severely the network is infected. Instead of considering the same recovery rate for all the nodes in the SIS model, we propose to allocate the recovery rate δi for node i according to its indegree and outdegree-δi∼ kα in i, in kα out i, out given the finite average recovery rate (δ) representing the limited recovery resources over the whole network. We consider directed networks with the same power law indegree and outdegree distribution, but different values of the directionality ξ (the proportion of unidirectional links) and linear correlation coefficients ρ between the indegree and outdegree. We find that, by tuning the two scaling exponents αin and αout, we can always reduce the infection fraction y thus reducing the extent of infections, comparing to the homogeneous recovery rates allocation. Moreover, we can find our optimal strategy via the optimal choice of the exponent αin and αout. Our optimal strategy indicates that when the recovery resources are sufficient, more resources should be allocated to the nodes with a larger indegree or outdegree, but when the recovery resource is very limited, only the nodes with a larger outdegree should be equipped with more resources. We also find that our optimal strategy works better when the recovery resources are sufficient but not yet able to make the epidemic die out, and when the indegree outdegree correlation is small.

Original languageEnglish
Title of host publication2014 7th International Conference on Network Games, Control and Optimization, NetGCoop 2014
Place of PublicationPiscataway, NJ
Number of pages7
ISBN (Electronic)978-88-8443-574-3
Publication statusPublished - 2017
Event7th International Conference on Network Games, Control and Optimization, NetGCoop 2014 - Trento, Italy
Duration: 29 Oct 201431 Oct 2014


Conference7th International Conference on Network Games, Control and Optimization, NetGCoop 2014


  • Silicon
  • Correlation
  • Resource management
  • Immune system
  • Steady-state
  • Electronic mail
  • Communication networks


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