Abstract
We investigate the dynamics of an epidemiological susceptible-infected-susceptible (SIS) model on an adaptive network. This model combines epidemic spreading (dynamics on the network) with rewiring of network connections (topological evolution of the network). We propose and implement a computational approach that enables us to study the dynamics of the network directly on an emergent, coarse-grained level. The approach sidesteps the derivation of closed low-dimensional approximations. Our investigations reveal that global coupling, which enters through the awareness of the population to the disease, can result in robust large-amplitude oscillations of the state and topology of the network.
Original language | English |
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Article number | 38004 |
Number of pages | 6 |
Journal | EPL |
DOIs | |
Publication status | Published - 2008 |
Research Groups and Themes
- Engineering Mathematics Research Group