Impact of non-Poissonian activity patterns on spreading processes.

By A. Vázquez, Balázs Rácz, András Lukács, Albert-László Barabási. Physical Review Letters, 2006

326 citations recorded by the source corpus.

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.

Subfields: Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/3cb0f3bf73b3232900cd871ba9cf197b0c52af04

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In Molecular Biology

In Statistical and Nonlinear Physics

Citations in the corpus

Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks (2008, background): “[17] Vázquez, A.”
Dynamics of information diffusion and its applications on complex networks (2016, background): “[147] with analyzing the spread of Email worms among Email users.”
Impact of human activity patterns on the dynamics of information diffusion. (2007, unknown): “As suggested in [28], the high variability of response times can be the origin of the prevalence of computer viruses.”