2012/12/05 by Stefan Wieland, Tomas Aquino, Wieland, Stefan +6
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Distributed Control Multi-Agent Systems #Neural Networks Stability and Synchronization #Opinion Dynamics and Social Influence #nlin.AO #physics.soc-ph #q-bio.PE
paper · pdf · doi:10.48550/arxiv.1212.1060
deterministic precursor to stochastic node-cycle model, contributed paper at ECCS 2010 in Lisbon
arxiv created 2012/12/05 · arxiv updated 2012/12/06
Disease awareness in epidemiology can be modelled with adaptive contact networks, where the interplay of disease dynamics and network alteration often adds new phases to the standard models (Gross et al. 2006, Shaw et al. 2008) and, in stochastic simulations, lets network topology settle down to a steady state that can be static (in the frozen phase) or dynamic (in the endemic phase). We show for the SIS model that, in the endemic phase, this steady state does not depend on the initial network topology, only on the disease and rewiring parameters and on the link density of the network, which is conserved. We give an analytic description of the structure of this co-evolving network of infection through its steady-state degree distribution.