Vazquez Alexei, Rácz Balázs, Lukács András, Barabási Albert-László
The Simons Center for Systems Biology, Institute of Advanced Study, Einstein Drive, Princeton, New Jersey 08540, USA.
Phys Rev Lett. 2007 Apr 13;98(15):158702. doi: 10.1103/PhysRevLett.98.158702. Epub 2007 Apr 10.
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.
阻止计算机或生物病毒爆发需要详细了解易感个体和感染个体之间相互作用的时间。虽然目前的传播模型假设用户在时间上均匀交互，遵循泊松过程，但最近的一系列测量表明，接触时间分布是重尾的，这对应于时间上不均匀的突发接触过程。在这里，我们表明接触动态的非泊松性质导致流行率衰减时间显著大于基于标准泊松过程的模型所预测的时间。我们的预测与计算机病毒的详细时间分辨流行率数据一致，根据病毒公告，这些数据显示衰减时间接近一年，这与基于标准泊松过程的模型预测的1天衰减形成对比。
