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Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China
OBJECTIVES: To forecast the development trend of current outbreak in Dalian, mainly to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China, the results can be used to provide a scientific reference for timely adjustment of prevention and control strategies. METHODS: Durin...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9736721/ https://www.ncbi.nlm.nih.gov/pubmed/36496364 http://dx.doi.org/10.1186/s12879-022-07911-4 |
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author | An, Qingyu Wu, Jun Bai, Jin jian Li, Xiaofeng |
author_facet | An, Qingyu Wu, Jun Bai, Jin jian Li, Xiaofeng |
author_sort | An, Qingyu |
collection | PubMed |
description | OBJECTIVES: To forecast the development trend of current outbreak in Dalian, mainly to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China, the results can be used to provide a scientific reference for timely adjustment of prevention and control strategies. METHODS: During the outbreak, Bayesian framework was used to calculated the time-dependent reproduction number ([Formula: see text] ), and then above acquired [Formula: see text] and exponential trend equation were used to establish the prediction model, through the model, predict the [Formula: see text] value of following data and know when [Formula: see text] smaller than 1. RESULTS: From July 22 to August 5, 2020, and from March 14 to April 2, 2022, 92 and 632 confirmed cases and asymptomatic infected cases of COVID-19 were reported (324 males and 400 females) in Dalian. The R square for exponential trend equation were 0.982 and 0.980, respectively which fit the [Formula: see text] with illness onset between July 19 to July 28, 2020 and between March 5 to March 17, 2022. According to the result of prediction, under the current strength of prevention and control, the [Formula: see text] of COVID-19 will drop below 1 till August 2, 2020 and March 26, 2022, respectively in Dalian, one day earlier or later than the actual date. That is, the turning point of the COVID-19 outbreak in Dalian, Liaoning province, China will occur on August 2, 2020 and March 26, 2022. CONCLUSIONS: Using time-dependent reproduction number values to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China was effective and reliable on the whole, and the results can be used to establish a sensitive early warning mechanism to guide the timely adjustment of COVID-19 prevention and control strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07911-4. |
format | Online Article Text |
id | pubmed-9736721 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-97367212022-12-11 Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China An, Qingyu Wu, Jun Bai, Jin jian Li, Xiaofeng BMC Infect Dis Research OBJECTIVES: To forecast the development trend of current outbreak in Dalian, mainly to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China, the results can be used to provide a scientific reference for timely adjustment of prevention and control strategies. METHODS: During the outbreak, Bayesian framework was used to calculated the time-dependent reproduction number ([Formula: see text] ), and then above acquired [Formula: see text] and exponential trend equation were used to establish the prediction model, through the model, predict the [Formula: see text] value of following data and know when [Formula: see text] smaller than 1. RESULTS: From July 22 to August 5, 2020, and from March 14 to April 2, 2022, 92 and 632 confirmed cases and asymptomatic infected cases of COVID-19 were reported (324 males and 400 females) in Dalian. The R square for exponential trend equation were 0.982 and 0.980, respectively which fit the [Formula: see text] with illness onset between July 19 to July 28, 2020 and between March 5 to March 17, 2022. According to the result of prediction, under the current strength of prevention and control, the [Formula: see text] of COVID-19 will drop below 1 till August 2, 2020 and March 26, 2022, respectively in Dalian, one day earlier or later than the actual date. That is, the turning point of the COVID-19 outbreak in Dalian, Liaoning province, China will occur on August 2, 2020 and March 26, 2022. CONCLUSIONS: Using time-dependent reproduction number values to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China was effective and reliable on the whole, and the results can be used to establish a sensitive early warning mechanism to guide the timely adjustment of COVID-19 prevention and control strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07911-4. BioMed Central 2022-12-10 /pmc/articles/PMC9736721/ /pubmed/36496364 http://dx.doi.org/10.1186/s12879-022-07911-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 An, Qingyu Wu, Jun Bai, Jin jian Li, Xiaofeng Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China |
title | Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China |
title_full | Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China |
title_fullStr | Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China |
title_full_unstemmed | Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China |
title_short | Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China |
title_sort | using time-dependent reproduction number to predict turning points of covid-19 outbreak in dalian, liaoning province, china |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9736721/ https://www.ncbi.nlm.nih.gov/pubmed/36496364 http://dx.doi.org/10.1186/s12879-022-07911-4 |
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