Spreading dynamics following bursty human activity patterns

Byungjoon Min, Kwang-Il Goh, Alexei Vazquez

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

We study the susceptible-infected model with power-law waiting time distributions P(τ)∼τ -α, as a model of spreading dynamics under heterogeneous human activity patterns. We found that the average number of new infections n(t) at time t decays as a power law in the long-time limit, n(t)∼t -β, leading to extremely slow prevalence decay. We also found that the exponent in the spreading dynamics β is related to that in the waiting time distribution α in a way depending on the interactions between agents but insensitive to the network topology. These observations are well supported by both the theoretical predictions and the long prevalence decay time in real social spreading phenomena. Our results unify individual activity patterns with macroscopic collective dynamics at the network level.

Original languageEnglish
Article number036102
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume83
Issue number3
DOIs
Publication statusPublished - 2011 Mar 7

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Waiting Time Distribution
Decay
Power-law Distribution
decay
Network Topology
Infection
Power Law
Exponent
infectious diseases
Prediction
Interaction
Model
topology
Human
exponents
predictions
interactions
Observation

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Statistics and Probability

Cite this

Spreading dynamics following bursty human activity patterns. / Min, Byungjoon; Goh, Kwang-Il; Vazquez, Alexei.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 83, No. 3, 036102, 07.03.2011.

Research output: Contribution to journalArticle

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