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

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Abstract

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.

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Author and article information

Journal

Journal ID (iso-abbrev): J Infect Dev Ctries

Title: Journal of infection in developing countries

Publisher: Journal of Infection in Developing Countries

ISSN (Electronic): 1972-2680

ISSN (Print): 1972-2680

Publication date (Electronic): March 31 2020

Volume: 14

Issue: 3

Affiliations

[1 ] Department of Mathematics and Statistics, College of Science, Wuhan University of Science and Technology, Wuhan, Hubei Province, China. 2305411797@qq.com.

[2 ] Department of Pathology, Brigham and Women's Hospital, Harvard Medical School Boston, MA, United States. mliu0@bwh.harvard.edu.

[3 ] Department of Mathematics and Statistics, College of Science, Wuhan University of Science and Technology, Wuhan, Hubei Province, China. dingyongmei@wust.edu.cn.

Article

DOI: 10.3855/jidc.12585

PubMed ID: 32235084

SO-VID: 079f1a33-d2ee-4d62-b771-43de251b5a5f

History

Keywords: COVID-19,Logistic model,SEIR,Spatial-temporal distribution

Data availability:

Keywords: COVID-19, Logistic model, SEIR, Spatial-temporal distribution

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