Literature DB >> 17501392

Impact of non-Poissonian activity patterns on spreading processes.

Alexei Vazquez1, Balázs Rácz, András Lukács, Albert-László Barabási.   

Abstract

Halting a computer or biological virus outbreak requires a detailed understanding of the timing of the interactions between susceptible and infected individuals. While current spreading models assume that users interact uniformly in time, following a Poisson process, a series of recent measurements indicates that the intercontact time distribution is heavy tailed, corresponding to a temporally inhomogeneous bursty contact process. Here we show that the non-Poisson nature of the contact dynamics results in prevalence decay times significantly larger than predicted by the standard Poisson process based models. Our predictions are in agreement with the detailed time resolved prevalence data of computer viruses, which, according to virus bulletins, show a decay time close to a year, in contrast with the 1 day decay predicted by the standard Poisson process based models.

Mesh:

Year:  2007        PMID: 17501392     DOI: 10.1103/PhysRevLett.98.158702

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  48 in total

1.  Microdynamics in stationary complex networks.

Authors:  Aurelien Gautreau; Alain Barrat; Marc Barthélemy
Journal:  Proc Natl Acad Sci U S A       Date:  2009-05-19       Impact factor: 11.205

2.  Temporal motifs reveal homophily, gender-specific patterns, and group talk in call sequences.

Authors:  Lauri Kovanen; Kimmo Kaski; János Kertész; Jari Saramäki
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-21       Impact factor: 11.205

3.  Diffusion on networked systems is a question of time or structure.

Authors:  Jean-Charles Delvenne; Renaud Lambiotte; Luis E C Rocha
Journal:  Nat Commun       Date:  2015-06-09       Impact factor: 14.919

4.  Diffusion in networks and the virtue of burstiness.

Authors:  Mohammad Akbarpour; Matthew O Jackson
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-09       Impact factor: 11.205

5.  Predicting and containing epidemic risk using on-line friendship networks.

Authors:  Lorenzo Coviello; Massimo Franceschetti; Manuel García-Herranz; Iyad Rahwan
Journal:  PLoS One       Date:  2019-05-16       Impact factor: 3.240

6.  Evidence for a bimodal distribution in human communication.

Authors:  Ye Wu; Changsong Zhou; Jinghua Xiao; Jürgen Kurths; Hans Joachim Schellnhuber
Journal:  Proc Natl Acad Sci U S A       Date:  2010-10-19       Impact factor: 11.205

7.  Dynamical patterns of cattle trade movements.

Authors:  Paolo Bajardi; Alain Barrat; Fabrizio Natale; Lara Savini; Vittoria Colizza
Journal:  PLoS One       Date:  2011-05-18       Impact factor: 3.240

8.  Predicting and controlling infectious disease epidemics using temporal networks.

Authors:  Naoki Masuda; Petter Holme
Journal:  F1000Prime Rep       Date:  2013-03-04

9.  On the robustness of in- and out-components in a temporal network.

Authors:  Mario Konschake; Hartmut H K Lentz; Franz J Conraths; Philipp Hövel; Thomas Selhorst
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

10.  Bursts of vertex activation and epidemics in evolving networks.

Authors:  Luis E C Rocha; Vincent D Blondel
Journal:  PLoS Comput Biol       Date:  2013-03-21       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.