Many real-world networks are characterized by adaptive changes in their topology depending on the state of their nodes. Here we study epidemic dynamics on an adaptive network, where the susceptibles are able to avoid contact with the infected by rewiring their network connections. This gives rise to assortative degree correlation, oscillations, hysteresis, and first order transitions. We propose a low-dimensional model to describe the system and present a full local bifurcation analysis. Our results indicate that the interplay between dynamics and topology can have important consequences for the spreading of infectious diseases and related applications.
%0 Journal Article
%1 Gross2006Epidemic
%A Gross, Thilo
%A D'Lima, Carlos
%A Blasius, Bernd
%D 2006
%I American Physical Society
%J Physical Review Letters
%K adaptive-sis, adaptive-voter-model, temporal-networks epidemic-models sis
%N 20
%P 208701+
%R 10.1103/physrevlett.96.208701
%T Epidemic Dynamics on an Adaptive Network
%U http://dx.doi.org/10.1103/physrevlett.96.208701
%V 96
%X Many real-world networks are characterized by adaptive changes in their topology depending on the state of their nodes. Here we study epidemic dynamics on an adaptive network, where the susceptibles are able to avoid contact with the infected by rewiring their network connections. This gives rise to assortative degree correlation, oscillations, hysteresis, and first order transitions. We propose a low-dimensional model to describe the system and present a full local bifurcation analysis. Our results indicate that the interplay between dynamics and topology can have important consequences for the spreading of infectious diseases and related applications.
@article{Gross2006Epidemic,
abstract = {{Many real-world networks are characterized by adaptive changes in their topology depending on the state of their nodes. Here we study epidemic dynamics on an adaptive network, where the susceptibles are able to avoid contact with the infected by rewiring their network connections. This gives rise to assortative degree correlation, oscillations, hysteresis, and first order transitions. We propose a low-dimensional model to describe the system and present a full local bifurcation analysis. Our results indicate that the interplay between dynamics and topology can have important consequences for the spreading of infectious diseases and related applications.}},
added-at = {2019-06-10T14:53:09.000+0200},
author = {Gross, Thilo and D'Lima, Carlos and Blasius, Bernd},
biburl = {https://www.bibsonomy.org/bibtex/230dd56574b9b43ba7b324bbb236f403e/nonancourt},
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citeulike-linkout-3 = {http://link.aps.org/abstract/PRL/v96/i20/e208701},
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doi = {10.1103/physrevlett.96.208701},
interhash = {844967ddec93adfa2f0799a4792abcbd},
intrahash = {30dd56574b9b43ba7b324bbb236f403e},
issn = {0031-9007},
journal = {Physical Review Letters},
keywords = {adaptive-sis, adaptive-voter-model, temporal-networks epidemic-models sis},
month = may,
number = 20,
pages = {208701+},
posted-at = {2012-11-15 10:35:07},
priority = {2},
publisher = {American Physical Society},
timestamp = {2019-08-22T16:24:38.000+0200},
title = {{Epidemic Dynamics on an Adaptive Network}},
url = {http://dx.doi.org/10.1103/physrevlett.96.208701},
volume = 96,
year = 2006
}