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Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis
Objective: The aim of this study is to analyze the latent class of basic reproduction number (R(0)) trends of the 2019 novel coronavirus disease (COVID-19) in the major endemic areas of China. Methods: The provinces that reported more than 500 cases of COVID-19 till February 18, 2020 were selected a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476846/ https://www.ncbi.nlm.nih.gov/pubmed/34595146 http://dx.doi.org/10.3389/fpubh.2021.575315 |
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author | Xu, Honglv Zhang, Yi Yuan, Min Ma, Liya Liu, Meng Gan, Hong Liu, Wenwen Lum, Gillian Gianna Anne Tao, Fangbiao |
author_facet | Xu, Honglv Zhang, Yi Yuan, Min Ma, Liya Liu, Meng Gan, Hong Liu, Wenwen Lum, Gillian Gianna Anne Tao, Fangbiao |
author_sort | Xu, Honglv |
collection | PubMed |
description | Objective: The aim of this study is to analyze the latent class of basic reproduction number (R(0)) trends of the 2019 novel coronavirus disease (COVID-19) in the major endemic areas of China. Methods: The provinces that reported more than 500 cases of COVID-19 till February 18, 2020 were selected as the major endemic areas. The Verhulst model was used to fit the growth rate of cumulative confirmed cases. The R(0) of COVID-19 was calculated using the parameters of severe acute respiratory syndrome (SARS) and COVID-19. The latent class of R(0) was analyzed using the latent profile analysis (LPA) model. Results: The median R(0) calculated from the SARS and COVID-19 parameters were 1.84–3.18 and 1.74–2.91, respectively. The R(0) calculated from the SARS parameters was greater than that calculated from the COVID-19 parameters (Z = −4.782 to −4.623, p < 0.01). Both R(0) can be divided into three latent classes. The initial value of R(0) in class 1 (Shandong Province, Sichuan Province, and Chongqing Municipality) was relatively low and decreased slowly. The initial value of R(0) in class 2 (Anhui Province, Hunan Province, Jiangxi Province, Henan Province, Zhejiang Province, Guangdong Province, and Jiangsu Province) was relatively high and decreased rapidly. Moreover, the initial R(0) value of class 3 (Hubei Province) was in the range between that of classes 1 and 2, but the higher R(0) level lasted longer and decreased slowly. Conclusion: The results indicated that the overall R(0) trend is decreased with the strengthening of comprehensive prevention and control measures of China for COVID-19, however, there are regional differences. |
format | Online Article Text |
id | pubmed-8476846 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84768462021-09-29 Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis Xu, Honglv Zhang, Yi Yuan, Min Ma, Liya Liu, Meng Gan, Hong Liu, Wenwen Lum, Gillian Gianna Anne Tao, Fangbiao Front Public Health Public Health Objective: The aim of this study is to analyze the latent class of basic reproduction number (R(0)) trends of the 2019 novel coronavirus disease (COVID-19) in the major endemic areas of China. Methods: The provinces that reported more than 500 cases of COVID-19 till February 18, 2020 were selected as the major endemic areas. The Verhulst model was used to fit the growth rate of cumulative confirmed cases. The R(0) of COVID-19 was calculated using the parameters of severe acute respiratory syndrome (SARS) and COVID-19. The latent class of R(0) was analyzed using the latent profile analysis (LPA) model. Results: The median R(0) calculated from the SARS and COVID-19 parameters were 1.84–3.18 and 1.74–2.91, respectively. The R(0) calculated from the SARS parameters was greater than that calculated from the COVID-19 parameters (Z = −4.782 to −4.623, p < 0.01). Both R(0) can be divided into three latent classes. The initial value of R(0) in class 1 (Shandong Province, Sichuan Province, and Chongqing Municipality) was relatively low and decreased slowly. The initial value of R(0) in class 2 (Anhui Province, Hunan Province, Jiangxi Province, Henan Province, Zhejiang Province, Guangdong Province, and Jiangsu Province) was relatively high and decreased rapidly. Moreover, the initial R(0) value of class 3 (Hubei Province) was in the range between that of classes 1 and 2, but the higher R(0) level lasted longer and decreased slowly. Conclusion: The results indicated that the overall R(0) trend is decreased with the strengthening of comprehensive prevention and control measures of China for COVID-19, however, there are regional differences. Frontiers Media S.A. 2021-09-14 /pmc/articles/PMC8476846/ /pubmed/34595146 http://dx.doi.org/10.3389/fpubh.2021.575315 Text en Copyright © 2021 Xu, Zhang, Yuan, Ma, Liu, Gan, Liu, Lum and Tao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Xu, Honglv Zhang, Yi Yuan, Min Ma, Liya Liu, Meng Gan, Hong Liu, Wenwen Lum, Gillian Gianna Anne Tao, Fangbiao Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis |
title | Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis |
title_full | Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis |
title_fullStr | Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis |
title_full_unstemmed | Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis |
title_short | Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis |
title_sort | basic reproduction number of the 2019 novel coronavirus disease in the major endemic areas of china: a latent profile analysis |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476846/ https://www.ncbi.nlm.nih.gov/pubmed/34595146 http://dx.doi.org/10.3389/fpubh.2021.575315 |
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