Paper Info
Title
Spatiotemporal Dynamic Of Covid-19 Diffusion In China: A Dynamic Spatial Autoregressive Model Analysis
Abstract
COVID-19 has seriously threatened people's health and well-being across the globe since it was first reported in Wuhan, China in late 2019. This study investigates the mechanism of COVID-19 transmission in different periods within and between cities in China to better understand the nature of the outbreak. We use Moran's I, a measure of spatial autocorrelation, to examine the spatial dependency of COVID-19 and a dynamic spatial autoregressive model to explore the transmission mechanism. We find that the spatial dependency of COVID-19 decreased over time and that the transmission of the disease could be divided into three distinct stages: an eruption stage, a stabilization stage, and a declination stage. The infection rate between cities was close to one-third of the infection rate within cities at the eruption stage, while it reduced to zero at the declination stage. We also find that the infection rates within cities at the eruption stage and declination stage were similar. China's policies for controlling the spread of the epidemic, specifically with respect to limiting inter-city mobility and implementing intra-city travel restrictions (social isolation), were most effective in reducing the viral transmission of COVID-19. The findings from this study indicate that the elimination of inter-city mobility had the largest impact on controlling disease transmission.
Year
DOI
Venue
2021
10.3390/ijgi10080510
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
DocType
Volume
COVID-19, spatial dependency, dynamic spatial autoregressive model, spatial diffusion
Journal
10
Issue
Citations 
PageRank 
8
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Hanchen Yu102.03
Jingwei Li200.34
Sarah Bardin300.34
Hengyu Gu400.34
Chenjing Fan500.68