SciTech Central COVID-19
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Accepted Abstracts

Spatio-Temporal Propagation of the First Wave of the COVID-19 Pandemic

Bnaya Gross1, ∗ Zhiguo Zheng2, Shiyan Liu2, Xiaoqi Chen2, Alon Sela3,1  Jianxin Li3, Daqing Li3,2 Shlomo Havlin1
1 Bar-Ilan University, Israel
2 Beihang University, China
3 Ariel University,  Israel

Citation: Gross B, Zheng Z, Liu S, Chen X, Sela A et al (2020) Spatio-Temporal Propagation of the First Wave of the COVID-19 Pandemic. SciTech Central COVID-19

Received: July 09, 2020         Accepted: July 13, 2020         Published: July 13, 2020


The new coronavirus known as COVID-19 is spread world-wide 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 about 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 and have significant importance for accurate modeling of the disease dynamics. We study and 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. At early times, at 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 the infection rate decays approximately exponentially due to quarantines. The time evolution of the death and recovery rates also distinguish between these two stages and reflect the health system situation which could be overloaded due to the many unexpected patients. Keywords: COVID-19; Quarantine efficiency; Spatio-temporal analysis; Scaling analysis