Spatial-temporal distribution of COVID-19 in China and its prediction: A data-driven modeling analysis

Currently, the outbreak of COVID-19 is rapidly spreading especially in Wuhan city, and threatens 14 million people in central China. In the present study we applied the Moran index, a strong statistical tool, to the spatial panel to show that COVID-19 infection is spatially dependent and mainly spre...

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Bibliographic Details
Published in:Journal of infection in developing countries 2020-03, Vol.14 (3), p.246-253
Main Authors: Huang, Rui, Liu, Miao, Ding, Yongmei
Format: Article
Language:English
Subjects:
Betacoronavirus
China - epidemiology
Cities
Coronavirus Infections - epidemiology
Coronaviruses
COVID-19
Disease Outbreaks
Disease transmission
Forecasting
Humans
Logistic Models
Pandemics
Pneumonia, Viral - epidemiology
SARS-CoV-2
Spatio-Temporal Analysis
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Summary:Currently, the outbreak of COVID-19 is rapidly spreading especially in Wuhan city, and threatens 14 million people in central China. In the present study we applied the Moran index, a strong statistical tool, to the spatial panel to show that COVID-19 infection is spatially dependent and mainly spread from Hubei Province in Central China to neighbouring areas. Logistic model was employed according to the trend of available data, which shows the difference between Hubei Province and outside of it. We also calculated the reproduction number R0 for the range of [2.23, 2.51] via SEIR model. The measures to reduce or prevent the virus spread should be implemented, and we expect our data-driven modeling analysis providing some insights to identify and prepare for the future virus control.
ISSN:1972-2680
2036-6590
1972-2680
DOI:10.3855/jidc.12585