Epidemic dynamics in finite size scale-free networks

Many real networks present a bounded scale-free behavior with a connectivity cutoff due to physical constraints or a finite network size. We study epidemic dynamics in bounded scale-free networks with soft and hard connectivity cutoffs. The finite size effects introduced by the cutoff induce an epid...

Full description

Bibliographic Details
Published:
Online Access:http://hdl.handle.net/2047/d20002155
id ndltd-NEU--neu-331336
record_format oai_dc
spelling ndltd-NEU--neu-3313362016-04-25T16:14:27ZEpidemic dynamics in finite size scale-free networksMany real networks present a bounded scale-free behavior with a connectivity cutoff due to physical constraints or a finite network size. We study epidemic dynamics in bounded scale-free networks with soft and hard connectivity cutoffs. The finite size effects introduced by the cutoff induce an epidemic threshold that approaches zero at increasing sizes. The induced epidemic threshold is very small even at a relatively small cutoff, showing that the neglection of connectivity fluctuations in bounded scale-free networks leads to a strong overestimation of the epidemic threshold. We provide the expression for the infection prevalence and discuss its finite size corrections. The present paper shows that the highly heterogeneous nature of scale-free networks does not allow the use of homogeneous approximations even for systems of a relatively small number of nodes.http://hdl.handle.net/2047/d20002155
collection NDLTD
sources NDLTD
description Many real networks present a bounded scale-free behavior with a connectivity cutoff due to physical constraints or a finite network size. We study epidemic dynamics in bounded scale-free networks with soft and hard connectivity cutoffs. The finite size effects introduced by the cutoff induce an epidemic threshold that approaches zero at increasing sizes. The induced epidemic threshold is very small even at a relatively small cutoff, showing that the neglection of connectivity fluctuations in bounded scale-free networks leads to a strong overestimation of the epidemic threshold. We provide the expression for the infection prevalence and discuss its finite size corrections. The present paper shows that the highly heterogeneous nature of scale-free networks does not allow the use of homogeneous approximations even for systems of a relatively small number of nodes.
title Epidemic dynamics in finite size scale-free networks
spellingShingle Epidemic dynamics in finite size scale-free networks
title_short Epidemic dynamics in finite size scale-free networks
title_full Epidemic dynamics in finite size scale-free networks
title_fullStr Epidemic dynamics in finite size scale-free networks
title_full_unstemmed Epidemic dynamics in finite size scale-free networks
title_sort epidemic dynamics in finite size scale-free networks
publishDate
url http://hdl.handle.net/2047/d20002155
_version_ 1718235744780156928