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Modeling the transmission dynamics of COVID-19 epidemic: a systematic review

The outbreak and rapid spread of COVID-19 has become a public health emergency of international concern. A number of studies have used modeling techniques and developed dynamic models to estimate the epidemiological parameters, explore and project the trends of the COVID-19, and assess the effects o...

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Detalles Bibliográficos
Autores principales: Guan, Jinxing, Wei, Yongyue, Zhao, Yang, Chen, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Editorial Department of Journal of Biomedical Research 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718076/
https://www.ncbi.nlm.nih.gov/pubmed/33243940
http://dx.doi.org/10.7555/JBR.34.20200119
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author Guan, Jinxing
Wei, Yongyue
Zhao, Yang
Chen, Feng
author_facet Guan, Jinxing
Wei, Yongyue
Zhao, Yang
Chen, Feng
author_sort Guan, Jinxing
collection PubMed
description The outbreak and rapid spread of COVID-19 has become a public health emergency of international concern. A number of studies have used modeling techniques and developed dynamic models to estimate the epidemiological parameters, explore and project the trends of the COVID-19, and assess the effects of intervention or control measures. We identified 63 studies and summarized the three aspects of these studies: epidemiological parameters estimation, trend prediction, and control measure evaluation. Despite the discrepancy between the predictions and the actuals, the dynamic model has made great contributions in the above three aspects. The most important role of dynamic models is exploring possibilities rather than making strong predictions about longer-term disease dynamics.
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spelling pubmed-77180762020-12-30 Modeling the transmission dynamics of COVID-19 epidemic: a systematic review Guan, Jinxing Wei, Yongyue Zhao, Yang Chen, Feng J Biomed Res Review Article The outbreak and rapid spread of COVID-19 has become a public health emergency of international concern. A number of studies have used modeling techniques and developed dynamic models to estimate the epidemiological parameters, explore and project the trends of the COVID-19, and assess the effects of intervention or control measures. We identified 63 studies and summarized the three aspects of these studies: epidemiological parameters estimation, trend prediction, and control measure evaluation. Despite the discrepancy between the predictions and the actuals, the dynamic model has made great contributions in the above three aspects. The most important role of dynamic models is exploring possibilities rather than making strong predictions about longer-term disease dynamics. Editorial Department of Journal of Biomedical Research 2020-11 2020-10-30 /pmc/articles/PMC7718076/ /pubmed/33243940 http://dx.doi.org/10.7555/JBR.34.20200119 Text en Copyright and License information: Journal of Biomedical Research, CAS Springer-Verlag Berlin Heidelberg 2020 http://creativecommons.org/licenses/by-nc-sa/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Review Article
Guan, Jinxing
Wei, Yongyue
Zhao, Yang
Chen, Feng
Modeling the transmission dynamics of COVID-19 epidemic: a systematic review
title Modeling the transmission dynamics of COVID-19 epidemic: a systematic review
title_full Modeling the transmission dynamics of COVID-19 epidemic: a systematic review
title_fullStr Modeling the transmission dynamics of COVID-19 epidemic: a systematic review
title_full_unstemmed Modeling the transmission dynamics of COVID-19 epidemic: a systematic review
title_short Modeling the transmission dynamics of COVID-19 epidemic: a systematic review
title_sort modeling the transmission dynamics of covid-19 epidemic: a systematic review
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718076/
https://www.ncbi.nlm.nih.gov/pubmed/33243940
http://dx.doi.org/10.7555/JBR.34.20200119
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