Adaptive networks: Coevolution of disease and topology
Abstract
Adaptive networks have been recently introduced in the context of disease propagation on complex networks. They account for the mutual interaction between the network topology and the states of the nodes. Until now, existing models have been analyzed using low complexity analytical formalisms, revealing nevertheless some novel dynamical features. However, current methods have failed to reproduce with accuracy the simultaneous time evolution of the disease and the underlying network topology. In the framework of the adaptive susceptible-infectious-susceptible (SIS) model of Gross [Phys. Rev. Lett. 96, 208701 (2006)]10.1103/PhysRevLett.96.208701, we introduce an improved compartmental formalism able to handle this coevolutionary task successfully. With this approach, we analyze the interplay and outcomes of both dynamical elements, process and structure, on adaptive networks featuring different degree distributions at the initial stage.
- Publication:
-
Physical Review E
- Pub Date:
- September 2010
- DOI:
- 10.1103/PhysRevE.82.036116
- arXiv:
- arXiv:1005.1299
- Bibcode:
- 2010PhRvE..82c6116M
- Keywords:
-
- 89.75.Fb;
- 89.75.Hc;
- 87.10.Ed;
- Structures and organization in complex systems;
- Networks and genealogical trees;
- Ordinary differential equations partial differential equations integrodifferential models;
- Condensed Matter - Statistical Mechanics;
- Physics - Physics and Society;
- Quantitative Biology - Populations and Evolution
- E-Print:
- 11 pages, 8 figures, 1 appendix. To be published in Physical Review E