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CIRD-F: Spread and Influence of COVID-19 in China
The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Therefore, it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies. Existing models...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Shanghai Jiaotong University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137851/ https://www.ncbi.nlm.nih.gov/pubmed/32288416 http://dx.doi.org/10.1007/s12204-020-2168-1 |
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author | Zhou, Lingyun Wu, Kaiwei Liu, Hanzhi Gao, Yuanning Gao, Xiaofeng |
author_facet | Zhou, Lingyun Wu, Kaiwei Liu, Hanzhi Gao, Yuanning Gao, Xiaofeng |
author_sort | Zhou, Lingyun |
collection | PubMed |
description | The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Therefore, it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies. Existing models for prediction, such as cabin models and individual-based models, are either oversimplified or too meticulous, and the influence of the epidemic was studied much more than that of official policies. To predict the epidemic tendency, we consider four groups of people, and establish a propagation dynamics model. We also create a negative feedback to quantify the public vigilance to the epidemic. We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country. Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78 191 (prediction interval, 74 872 to 82 474). By changing the parameters of the model accordingly, we demonstrate the control effect of the policies of the government on the epidemic situation, which can reduce about 68% possible infections. At the same time, we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries. |
format | Online Article Text |
id | pubmed-7137851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Shanghai Jiaotong University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-71378512020-04-07 CIRD-F: Spread and Influence of COVID-19 in China Zhou, Lingyun Wu, Kaiwei Liu, Hanzhi Gao, Yuanning Gao, Xiaofeng J Shanghai Jiaotong Univ Sci Article The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Therefore, it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies. Existing models for prediction, such as cabin models and individual-based models, are either oversimplified or too meticulous, and the influence of the epidemic was studied much more than that of official policies. To predict the epidemic tendency, we consider four groups of people, and establish a propagation dynamics model. We also create a negative feedback to quantify the public vigilance to the epidemic. We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country. Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78 191 (prediction interval, 74 872 to 82 474). By changing the parameters of the model accordingly, we demonstrate the control effect of the policies of the government on the epidemic situation, which can reduce about 68% possible infections. At the same time, we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries. Shanghai Jiaotong University Press 2020-04-07 2020 /pmc/articles/PMC7137851/ /pubmed/32288416 http://dx.doi.org/10.1007/s12204-020-2168-1 Text en © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Zhou, Lingyun Wu, Kaiwei Liu, Hanzhi Gao, Yuanning Gao, Xiaofeng CIRD-F: Spread and Influence of COVID-19 in China |
title | CIRD-F: Spread and Influence of COVID-19 in China |
title_full | CIRD-F: Spread and Influence of COVID-19 in China |
title_fullStr | CIRD-F: Spread and Influence of COVID-19 in China |
title_full_unstemmed | CIRD-F: Spread and Influence of COVID-19 in China |
title_short | CIRD-F: Spread and Influence of COVID-19 in China |
title_sort | cird-f: spread and influence of covid-19 in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137851/ https://www.ncbi.nlm.nih.gov/pubmed/32288416 http://dx.doi.org/10.1007/s12204-020-2168-1 |
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