Universal Urban Spreading Pattern of COVID-19 and Its Underlying Mechanism
Abstract
Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical measures. Previous studies investigated such an issue in large-scale (e.g., inter-country or inter-state) scenarios while urban spreading pattern still remains an open issue. Here, we fill this gap by leveraging the trajectory data of 197,808 smartphone users (including 17,808 anonymous confirmed cases) in 9 cities in China. We find a universal spreading pattern in all cities: the spatial distribution of confirmed cases follows a power-law-like model and the spreading centroid is time-invariant. Moreover, we reveal that human mobility in a city drives the spatialtemporal spreading process: long average travelling distance results in a high growth rate of spreading radius and wide spatial diffusion of confirmed cases. With such insight, we adopt Kendall model to simulate urban spreading of COVID-19 that can well fit the real spreading process. Our results unveil the underlying mechanism behind the spatial-temporal urban evolution of COVID-19, and can be used to evaluate the performance of mobility restriction policies implemented by many governments and to estimate the evolving spreading situation of COVID-19.
Keywords
Cite
@article{arxiv.2012.15161,
title = {Universal Urban Spreading Pattern of COVID-19 and Its Underlying Mechanism},
author = {Yongtao Zhang and Hongshen Zhang and Mincheng Wu and Shibo He and Yi Fang and Yanggang Cheng and Zhiguo Shi and Cunqi Shao and Chao Li and Songmin Ying and Zhenyu Gong and Yu Liu and Xinjiang Ye and Jinlai Chen and Youxian Sun and Jiming Chen and H. Eugene Stanley},
journal= {arXiv preprint arXiv:2012.15161},
year = {2021}
}