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Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China
China reported a major outbreak of a novel coronavirus, SARS-CoV2, from mid-January till mid-March 2020. We review the epidemic virus growth and decline curves in China using a phenomenological logistic growth model to summarize the outbreak dynamics using three parameters that characterize the epid...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323941/ https://www.ncbi.nlm.nih.gov/pubmed/32598342 http://dx.doi.org/10.1371/journal.pone.0235247 |
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author | Zou, Yi Pan, Stephen Zhao, Peng Han, Lei Wang, Xiaoxiang Hemerik, Lia Knops, Johannes van der Werf, Wopke |
author_facet | Zou, Yi Pan, Stephen Zhao, Peng Han, Lei Wang, Xiaoxiang Hemerik, Lia Knops, Johannes van der Werf, Wopke |
author_sort | Zou, Yi |
collection | PubMed |
description | China reported a major outbreak of a novel coronavirus, SARS-CoV2, from mid-January till mid-March 2020. We review the epidemic virus growth and decline curves in China using a phenomenological logistic growth model to summarize the outbreak dynamics using three parameters that characterize the epidemic’s timing, rate and peak. During the initial phase, the number of virus cases doubled every 2.7 days (range 2.2–4.4 across provinces). The rate of increase in the number of reported cases peaked approximately 10 days after suppression measures were started on 23–25 January 2020. The peak in the number of reported sick cases occurred on average 18 days after the start of suppression measures. From the time of starting measures till the peak, the number of cases increased by a factor 39 in the province Hubei, and by a factor 9.5 for all of China (range: 6.2–20.4 in the other provinces). Complete suppression took up to 2 months (range: 23-57d.), during which period severe restrictions, social distancing measures, testing and isolation of cases were in place. The suppression of the disease in China has been successful, demonstrating that suppression is a viable strategy to contain SARS-CoV2. |
format | Online Article Text |
id | pubmed-7323941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73239412020-07-08 Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China Zou, Yi Pan, Stephen Zhao, Peng Han, Lei Wang, Xiaoxiang Hemerik, Lia Knops, Johannes van der Werf, Wopke PLoS One Research Article China reported a major outbreak of a novel coronavirus, SARS-CoV2, from mid-January till mid-March 2020. We review the epidemic virus growth and decline curves in China using a phenomenological logistic growth model to summarize the outbreak dynamics using three parameters that characterize the epidemic’s timing, rate and peak. During the initial phase, the number of virus cases doubled every 2.7 days (range 2.2–4.4 across provinces). The rate of increase in the number of reported cases peaked approximately 10 days after suppression measures were started on 23–25 January 2020. The peak in the number of reported sick cases occurred on average 18 days after the start of suppression measures. From the time of starting measures till the peak, the number of cases increased by a factor 39 in the province Hubei, and by a factor 9.5 for all of China (range: 6.2–20.4 in the other provinces). Complete suppression took up to 2 months (range: 23-57d.), during which period severe restrictions, social distancing measures, testing and isolation of cases were in place. The suppression of the disease in China has been successful, demonstrating that suppression is a viable strategy to contain SARS-CoV2. Public Library of Science 2020-06-29 /pmc/articles/PMC7323941/ /pubmed/32598342 http://dx.doi.org/10.1371/journal.pone.0235247 Text en © 2020 Zou et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zou, Yi Pan, Stephen Zhao, Peng Han, Lei Wang, Xiaoxiang Hemerik, Lia Knops, Johannes van der Werf, Wopke Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China |
title | Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China |
title_full | Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China |
title_fullStr | Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China |
title_full_unstemmed | Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China |
title_short | Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China |
title_sort | outbreak analysis with a logistic growth model shows covid-19 suppression dynamics in china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323941/ https://www.ncbi.nlm.nih.gov/pubmed/32598342 http://dx.doi.org/10.1371/journal.pone.0235247 |
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