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Generalized logistic growth modeling of the COVID-19 pandemic in Asia

Several months into the ongoing novel coronavirus disease 2019 (COVID-19) pandemic, this work provides a simple and direct projection of the outbreak spreading potential and the pandemic cessation dates in Chinese mainland, Iran, the Philippines and Chinese Taiwan, using the generalized logistic mod...

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Detalles Bibliográficos
Autores principales: Aviv-Sharon, Elinor, Aharoni, Asaph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378518/
https://www.ncbi.nlm.nih.gov/pubmed/32766462
http://dx.doi.org/10.1016/j.idm.2020.07.003
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author Aviv-Sharon, Elinor
Aharoni, Asaph
author_facet Aviv-Sharon, Elinor
Aharoni, Asaph
author_sort Aviv-Sharon, Elinor
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description Several months into the ongoing novel coronavirus disease 2019 (COVID-19) pandemic, this work provides a simple and direct projection of the outbreak spreading potential and the pandemic cessation dates in Chinese mainland, Iran, the Philippines and Chinese Taiwan, using the generalized logistic model (GLM). The short-term predicted number of cumulative COVID-19 cases matched the confirmed reports of those who were infected across the four countries and regions, and the long-term forecasts were capable to accurately evaluate the spread of the pandemic in Chinese mainland and Chinese Taiwan, where control measures such as social distancing were fully implemented and sustained, suggesting GLM as a valuable tool for characterizing the transmission dynamics process and the trajectory of COVID-19 pandemic along with the impact of interventions.
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spelling pubmed-73785182020-07-24 Generalized logistic growth modeling of the COVID-19 pandemic in Asia Aviv-Sharon, Elinor Aharoni, Asaph Infect Dis Model Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu Several months into the ongoing novel coronavirus disease 2019 (COVID-19) pandemic, this work provides a simple and direct projection of the outbreak spreading potential and the pandemic cessation dates in Chinese mainland, Iran, the Philippines and Chinese Taiwan, using the generalized logistic model (GLM). The short-term predicted number of cumulative COVID-19 cases matched the confirmed reports of those who were infected across the four countries and regions, and the long-term forecasts were capable to accurately evaluate the spread of the pandemic in Chinese mainland and Chinese Taiwan, where control measures such as social distancing were fully implemented and sustained, suggesting GLM as a valuable tool for characterizing the transmission dynamics process and the trajectory of COVID-19 pandemic along with the impact of interventions. KeAi Publishing 2020-07-24 /pmc/articles/PMC7378518/ /pubmed/32766462 http://dx.doi.org/10.1016/j.idm.2020.07.003 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu
Aviv-Sharon, Elinor
Aharoni, Asaph
Generalized logistic growth modeling of the COVID-19 pandemic in Asia
title Generalized logistic growth modeling of the COVID-19 pandemic in Asia
title_full Generalized logistic growth modeling of the COVID-19 pandemic in Asia
title_fullStr Generalized logistic growth modeling of the COVID-19 pandemic in Asia
title_full_unstemmed Generalized logistic growth modeling of the COVID-19 pandemic in Asia
title_short Generalized logistic growth modeling of the COVID-19 pandemic in Asia
title_sort generalized logistic growth modeling of the covid-19 pandemic in asia
topic Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378518/
https://www.ncbi.nlm.nih.gov/pubmed/32766462
http://dx.doi.org/10.1016/j.idm.2020.07.003
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