Evolution of scaling emergence in large-scale spatial epidemic spreading

TL;DR

This paper investigates how Zipf's law and Heaps' law evolve and coexist during large-scale spatial epidemic spreading, revealing their dynamic relationship and the impact of infrastructure heterogeneity on epidemic evolution.

Contribution

It uncovers the temporal evolution and transition of scaling laws in epidemic spreading and highlights the role of infrastructure heterogeneity in this process.

Findings

Zipf's law and Heaps' law coexist initially but diverge over time.

Heterogeneity in infrastructure influences the evolution of scaling behaviors.

Targeted containment strategies are crucial early in a pandemic.

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 is 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(U.S.) 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.