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Spatio-temporal propagation of COVID-19 pandemics
Bnaya Gross; Zhiguo Zheng; Shiyan Liu; Xiaoqi Chen; Alon Sela; Jianxin Li; Daqing Li; Shlomo Havlin.
Afiliação
  • Bnaya Gross; Bar Ilan University
  • Zhiguo Zheng; School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
  • Shiyan Liu; School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
  • Xiaoqi Chen; School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
  • Alon Sela; Department of Industrial Engineering, Ariel University, Ariel, Israel
  • Jianxin Li; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100083, China
  • Daqing Li; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100191, China
  • Shlomo Havlin; Department of Physics, Bar-Ilan University, Ramat-Gan 52900, Israel
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20041517
ABSTRACT
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. 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 it 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.
Licença
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Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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