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Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China
BACKGROUND: Based on differences in populations and prevention and control measures, the spread of new coronary pneumonia in different countries and regions also differs. This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of m...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936873/ https://www.ncbi.nlm.nih.gov/pubmed/33676420 http://dx.doi.org/10.1186/s12879-021-05936-9 |
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author | Zhao, Qinglong Wang, Yao Yang, Meng Li, Meina Zhao, Zeyu Lu, Xinrong Shen, Bo Luan, Bo Zhao, Yifei Cao, Bonan Yao, Laishun Zhao, Benhua Su, Yanhua Chen, Tianmu |
author_facet | Zhao, Qinglong Wang, Yao Yang, Meng Li, Meina Zhao, Zeyu Lu, Xinrong Shen, Bo Luan, Bo Zhao, Yifei Cao, Bonan Yao, Laishun Zhao, Benhua Su, Yanhua Chen, Tianmu |
author_sort | Zhao, Qinglong |
collection | PubMed |
description | BACKGROUND: Based on differences in populations and prevention and control measures, the spread of new coronary pneumonia in different countries and regions also differs. This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of measures to control the disease in Jilin Province, China. METHODS: The data of reported COVID-19 cases were collected, including imported and local cases from Jilin Province as of March 14, 2019. A Susceptible–Exposed–Infectious–Asymptomatic–Recovered/Removed (SEIAR) model was developed to fit the data, and the effective reproduction number (R(eff)) was calculated at different stages in the province. Finally, the effectiveness of the measures was assessed. RESULTS: A total of 97 COVID-19 infections were reported in Jilin Province, among which 45 were imported infections (including one asymptomatic infection) and 52 were local infections (including three asymptomatic infections). The model fit the reported data well (R(2) = 0.593, P < 0.001). The R(eff) of COVID-19 before and after February 1, 2020 was 1.64 and 0.05, respectively. Without the intervention taken on February 1, 2020, the predicted cases would have reached a peak of 177,011 on October 22, 2020 (284 days from the first case). The projected number of cases until the end of the outbreak (on October 9, 2021) would have been 17,129,367, with a total attack rate of 63.66%. Based on the comparison between the predicted incidence of the model and the actual incidence, the comprehensive intervention measures implemented in Jilin Province on February 1 reduced the incidence of cases by 99.99%. Therefore, according to the current measures and implementation efforts, Jilin Province can achieve good control of the virus’s spread. CONCLUSIONS: COVID-19 has a moderate transmissibility in Jilin Province, China. The interventions implemented in the province had proven effective; increasing social distancing and a rapid response by the prevention and control system will help control the spread of the disease. |
format | Online Article Text |
id | pubmed-7936873 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79368732021-03-08 Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China Zhao, Qinglong Wang, Yao Yang, Meng Li, Meina Zhao, Zeyu Lu, Xinrong Shen, Bo Luan, Bo Zhao, Yifei Cao, Bonan Yao, Laishun Zhao, Benhua Su, Yanhua Chen, Tianmu BMC Infect Dis Research Article BACKGROUND: Based on differences in populations and prevention and control measures, the spread of new coronary pneumonia in different countries and regions also differs. This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of measures to control the disease in Jilin Province, China. METHODS: The data of reported COVID-19 cases were collected, including imported and local cases from Jilin Province as of March 14, 2019. A Susceptible–Exposed–Infectious–Asymptomatic–Recovered/Removed (SEIAR) model was developed to fit the data, and the effective reproduction number (R(eff)) was calculated at different stages in the province. Finally, the effectiveness of the measures was assessed. RESULTS: A total of 97 COVID-19 infections were reported in Jilin Province, among which 45 were imported infections (including one asymptomatic infection) and 52 were local infections (including three asymptomatic infections). The model fit the reported data well (R(2) = 0.593, P < 0.001). The R(eff) of COVID-19 before and after February 1, 2020 was 1.64 and 0.05, respectively. Without the intervention taken on February 1, 2020, the predicted cases would have reached a peak of 177,011 on October 22, 2020 (284 days from the first case). The projected number of cases until the end of the outbreak (on October 9, 2021) would have been 17,129,367, with a total attack rate of 63.66%. Based on the comparison between the predicted incidence of the model and the actual incidence, the comprehensive intervention measures implemented in Jilin Province on February 1 reduced the incidence of cases by 99.99%. Therefore, according to the current measures and implementation efforts, Jilin Province can achieve good control of the virus’s spread. CONCLUSIONS: COVID-19 has a moderate transmissibility in Jilin Province, China. The interventions implemented in the province had proven effective; increasing social distancing and a rapid response by the prevention and control system will help control the spread of the disease. BioMed Central 2021-03-06 /pmc/articles/PMC7936873/ /pubmed/33676420 http://dx.doi.org/10.1186/s12879-021-05936-9 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Zhao, Qinglong Wang, Yao Yang, Meng Li, Meina Zhao, Zeyu Lu, Xinrong Shen, Bo Luan, Bo Zhao, Yifei Cao, Bonan Yao, Laishun Zhao, Benhua Su, Yanhua Chen, Tianmu Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China |
title | Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China |
title_full | Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China |
title_fullStr | Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China |
title_full_unstemmed | Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China |
title_short | Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China |
title_sort | evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in jilin province, china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936873/ https://www.ncbi.nlm.nih.gov/pubmed/33676420 http://dx.doi.org/10.1186/s12879-021-05936-9 |
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