Spatio-temporal propagation of COVID-19 pandemics

¹ Department of Physics, Bar- Ilan University - Ramat-Gan 52900, Israel
² School of Reliability and Systems Engineering, Beihang University - Beijing 100191, China
³ Department of Industrial Engineering, Ariel University - Ariel, Israel
⁴ Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University Beijing 100191, China
⁵ School of Computer Science & Engineering, Beihang University - Beijing 100191, China
⁶ Beijing Advanced Innovation Center for Big Data- Based Precision Medicine, Beihang University Beijing 100191, China

^(a) bnaya.gross@gmail.com

Received: 2 July 2020
Accepted: 27 August 2020

Abstract

The coronavirus known as COVID-19 has spread worldwide since December 2019. Without any vaccination or medicine, the means of controlling it are limited to quarantine and social distancing. Here we study the spatio-temporal propagation of the first wave of the COVID-19 virus in China and compare it to other global locations. We provide a comprehensive picture of the spatial propagation from Hubei to other provinces in China in terms of distance, population size, and human mobility and their scaling relations. Since strict quarantine has been usually applied between cities, more insight into the temporal evolution of the disease can be obtained by analyzing the epidemic within cities, especially the time evolution of the infection, death, and recovery rates which affected by policies. We compare the infection rate in different cities in China and provinces in Italy and find that the disease spread is characterized by a two-stages process. In early times, of the order of few days, the infection rate is close to a constant probably due to the lack of means to detect infected individuals before infection symptoms are observed. Then at later times it decays approximately exponentially due to quarantines. This exponential decay allows us to define a characteristic time of controlling the disease which we found to be approximately 20 days for most cities in China in marked contrast to different provinces in Italy which are characterized with much longer controlling time indicating less efficient controlling policies. Moreover, we study the time evolution of the death and recovery rates which we found to show similar behavior as the infection rate and reflect the health system situation which could be overloaded.