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大规模空间流行病传播中尺度涌现的进化。

Evolution of scaling emergence in large-scale spatial epidemic spreading.

机构信息

Adaptive Networks and Control Lab, Department of Electronic Engineering, Fudan University, Shanghai, People's Republic of China.

出版信息

PLoS One. 2011;6(7):e21197. doi: 10.1371/journal.pone.0021197. Epub 2011 Jul 1.

Abstract

BACKGROUND

Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which has still hardly been clarified.

METHODOLOGY/PRINCIPAL FINDINGS: In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence.

CONCLUSIONS/SIGNIFICANCE: The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.

摘要

背景

齐夫定律和海普斯定律是两个具有代表性的标度概念,在复杂性科学研究中发挥着重要作用。齐夫定律和海普斯定律的共存激发了人们对这两种标度之间的依赖性的不同理解,而这种依赖性仍然很难被阐明。

方法/主要发现:在本文中,我们观察到了一个标度的演化过程:在初始时间,齐夫定律和海普斯定律自然地形成共存,而在更大的时间之前,随着它们之间的不一致性的出现,会出现交叉,直到达到一个稳定的状态,在这个状态下,尽管严格的齐夫定律消失了,但海普斯定律仍然存在。这种发现通过一个大规模空间传染病传播的场景来说明,大流行疾病的经验结果支持了对两种定律之间关系的普遍分析,而不论疾病的生物学细节如何。利用美国国内航空运输和人口数据构建了一个元种群模型,以模拟美国国家层面的大流行传播,我们发现基础设施的广泛异质性在标度出现的演化中起着关键作用。

结论/意义:对大规模空间传染病传播的分析有助于理解标度的时间演化,表明齐夫定律和海普斯定律的共存取决于传染病过程的集体动力学,而传染病传播的异质性表明在大流行疾病的早期实施有针对性的遏制策略的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfb1/3128583/39ed7e38c97e/pone.0021197.g001.jpg

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