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Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China

Objectives: Waves of epidemics associated with Omicron variant of Coronavirus Disease 2019 (COVID-19) in major cities in China this year have been controlled. It is of great importance to study the transmission characteristics of these cases to support further interventions. Methods: We simulate the...

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Autores principales: Zheng, Yangcheng, Wang, Yunpeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668860/
https://www.ncbi.nlm.nih.gov/pubmed/36405530
http://dx.doi.org/10.3389/ijph.2022.1605177
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author Zheng, Yangcheng
Wang, Yunpeng
author_facet Zheng, Yangcheng
Wang, Yunpeng
author_sort Zheng, Yangcheng
collection PubMed
description Objectives: Waves of epidemics associated with Omicron variant of Coronavirus Disease 2019 (COVID-19) in major cities in China this year have been controlled. It is of great importance to study the transmission characteristics of these cases to support further interventions. Methods: We simulate the transmission trajectory and analyze the intervention influences of waves associated with Omicron variant in major cities in China using the Suspected-Exposed-Infectious-Removed (SEIR) model. In addition, we propose a model using a function between the maximum daily infections and the duration of the epidemic, calibrated with data from Chinese cities. Results: An infection period of 5 days and basic reproduction number R(0) between 2 and 8.72 are most appropriate for most cases in China. Control measures show a significant impact on reducing R(0), and the earlier control measures are implemented, the shorter the epidemic will last. Our proposed model performs well in predicting the duration of the epidemic with an average error of 2.49 days. Conclusion: Our results show great potential in epidemic model simulation and predicting the end date of the Omicron epidemic effectively and efficiently.
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spelling pubmed-96688602022-11-18 Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China Zheng, Yangcheng Wang, Yunpeng Int J Public Health Public Health Archive Objectives: Waves of epidemics associated with Omicron variant of Coronavirus Disease 2019 (COVID-19) in major cities in China this year have been controlled. It is of great importance to study the transmission characteristics of these cases to support further interventions. Methods: We simulate the transmission trajectory and analyze the intervention influences of waves associated with Omicron variant in major cities in China using the Suspected-Exposed-Infectious-Removed (SEIR) model. In addition, we propose a model using a function between the maximum daily infections and the duration of the epidemic, calibrated with data from Chinese cities. Results: An infection period of 5 days and basic reproduction number R(0) between 2 and 8.72 are most appropriate for most cases in China. Control measures show a significant impact on reducing R(0), and the earlier control measures are implemented, the shorter the epidemic will last. Our proposed model performs well in predicting the duration of the epidemic with an average error of 2.49 days. Conclusion: Our results show great potential in epidemic model simulation and predicting the end date of the Omicron epidemic effectively and efficiently. Frontiers Media S.A. 2022-11-03 /pmc/articles/PMC9668860/ /pubmed/36405530 http://dx.doi.org/10.3389/ijph.2022.1605177 Text en Copyright © 2022 Zheng and Wang. 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 Archive
Zheng, Yangcheng
Wang, Yunpeng
Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China
title Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China
title_full Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China
title_fullStr Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China
title_full_unstemmed Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China
title_short Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China
title_sort transmission characteristics and predictive model for recent epidemic waves of covid-19 associated with omicron variant in major cities in china
topic Public Health Archive
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668860/
https://www.ncbi.nlm.nih.gov/pubmed/36405530
http://dx.doi.org/10.3389/ijph.2022.1605177
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