Literature DB >> 32235084

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

Rui Huang1, Miao Liu2, Yongmei Ding3.   

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. Copyright (c) 2020 Rui Huang, Miao Liu, Yongmei Ding.

Entities:  

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

Mesh:

Year:  2020        PMID: 32235084     DOI: 10.3855/jidc.12585

Source DB:  PubMed          Journal:  J Infect Dev Ctries        ISSN: 1972-2680            Impact factor:   0.968


  35 in total

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3.  Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment.

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Journal:  Int J Environ Res Public Health       Date:  2022-06-08       Impact factor: 4.614

4.  Common trends in the epidemic of Covid-19 disease.

Authors:  Milad Radiom; Jean-François Berret
Journal:  Eur Phys J Plus       Date:  2020-06-22       Impact factor: 3.911

5.  Monoclonal antibody pairs against SARS-CoV-2 for rapid antigen test development.

Authors:  Nol Salcedo; Ankita Reddy; Adam R Gomez; Irene Bosch; Bobby Brooke Herrera
Journal:  PLoS Negl Trop Dis       Date:  2022-03-31

6.  Risk clusters of COVID-19 transmission in northeastern Brazil: prospective space-time modelling.

Authors:  D S Gomes; L A Andrade; C J N Ribeiro; M V S Peixoto; S V M A Lima; A M Duque; T M Cirilo; M A O Góes; A G C F Lima; M B Santos; K C G M Araújo; A D Santos
Journal:  Epidemiol Infect       Date:  2020-08-24       Impact factor: 2.451

7.  Spatiotemporal analysis of COVID-19 outbreaks in Wuhan, China.

Authors:  Wei Liu; Dongming Wang; Shuiqiong Hua; Cong Xie; Bin Wang; Weihong Qiu; Tao Xu; Zi Ye; Linling Yu; Meng Yang; Yang Xiao; Xiaobing Feng; Tingming Shi; Mingyan Li; Weihong Chen
Journal:  Sci Rep       Date:  2021-07-01       Impact factor: 4.379

8.  The impacts of the built environment on the incidence rate of COVID-19: A case study of King County, Washington.

Authors:  Zerun Liu; Chao Liu; Chenghe Guan
Journal:  Sustain Cities Soc       Date:  2021-07-10       Impact factor: 7.587

9.  Modeling future spread of infections via mobile geolocation data and population dynamics. An application to COVID-19 in Brazil.

Authors:  Pedro S Peixoto; Diego Marcondes; Cláudia Peixoto; Sérgio M Oliva
Journal:  PLoS One       Date:  2020-07-16       Impact factor: 3.240

10.  Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity.

Authors:  Diego F Cuadros; Yanyu Xiao; Zindoga Mukandavire; Esteban Correa-Agudelo; Andrés Hernández; Hana Kim; Neil J MacKinnon
Journal:  Health Place       Date:  2020-07-25       Impact factor: 4.931

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