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Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic

BACKGROUND: From March to June 2022, an Omicron BA.2 epidemic occurred in Shanghai. We aimed to better understand the transmission dynamics and identify age-specific transmission characteristics for the epidemic. METHODS: Data on COVID-19 cases were collected from the Shanghai Municipal Health Commi...

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Autores principales: Zhu, Wenlong, Wen, Zexuan, Chen, Yue, Gong, Xiaohuan, Zheng, Bo, Liang, Xueyao, Xu, Ao, Yao, Ye, Wang, Weibing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121427/
https://www.ncbi.nlm.nih.gov/pubmed/37087436
http://dx.doi.org/10.1186/s12889-023-15596-w
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author Zhu, Wenlong
Wen, Zexuan
Chen, Yue
Gong, Xiaohuan
Zheng, Bo
Liang, Xueyao
Xu, Ao
Yao, Ye
Wang, Weibing
author_facet Zhu, Wenlong
Wen, Zexuan
Chen, Yue
Gong, Xiaohuan
Zheng, Bo
Liang, Xueyao
Xu, Ao
Yao, Ye
Wang, Weibing
author_sort Zhu, Wenlong
collection PubMed
description BACKGROUND: From March to June 2022, an Omicron BA.2 epidemic occurred in Shanghai. We aimed to better understand the transmission dynamics and identify age-specific transmission characteristics for the epidemic. METHODS: Data on COVID-19 cases were collected from the Shanghai Municipal Health Commission during the period from 20th February to 1st June. The effective reproductive number (R(t)) and transmission distance between cases were calculated. An age-structured SEIR model with social contact patterns was developed to reconstruct the transmission dynamics and evaluate age-specific transmission characteristics. Least square method was used to calibrate the model. Basic reproduction number (R(0)) was estimated with next generation matrix. RESULTS: R(0) of Omicron variant was 7.9 (95% CI: 7.4 to 8.4). With strict interventions, R(t) had dropped quickly from 3.6 (95% CI: 2.7 to 4.7) on 4th March to below 1 on 18th April. The mean transmission distance of the Omicron epidemic in Shanghai was 13.4 km (95% CI: 11.1 to 15.8 km), which was threefold longer compared with that of epidemic caused by the wild-type virus in Wuhan, China. The model estimated that there would have been a total 870,845 (95% CI: 815,400 to 926,289) cases for the epidemic from 20th February to 15th June, and 27.7% (95% CI: 24.4% to 30.9%) cases would have been unascertained. People aged 50–59 years had the highest transmission risk 0.216 (95% CI: 0.210 to 0.222), and the highest secondary attack rate (47.62%, 95% CI: 38.71% to 56.53%). CONCLUSIONS: The Omicron variant spread more quickly and widely than other variants and resulted in about one third cases unascertained for the recent outbreak in Shanghai. Prioritizing isolation and screening of people aged 40–59 might suppress the epidemic more effectively. Routine surveillance among people aged 40–59 years could also provide insight into the stage of the epidemic and the timely detection of new variants. TRIAL REGISTRATION: We did not involve clinical trial. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15596-w.
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spelling pubmed-101214272023-04-23 Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic Zhu, Wenlong Wen, Zexuan Chen, Yue Gong, Xiaohuan Zheng, Bo Liang, Xueyao Xu, Ao Yao, Ye Wang, Weibing BMC Public Health Research BACKGROUND: From March to June 2022, an Omicron BA.2 epidemic occurred in Shanghai. We aimed to better understand the transmission dynamics and identify age-specific transmission characteristics for the epidemic. METHODS: Data on COVID-19 cases were collected from the Shanghai Municipal Health Commission during the period from 20th February to 1st June. The effective reproductive number (R(t)) and transmission distance between cases were calculated. An age-structured SEIR model with social contact patterns was developed to reconstruct the transmission dynamics and evaluate age-specific transmission characteristics. Least square method was used to calibrate the model. Basic reproduction number (R(0)) was estimated with next generation matrix. RESULTS: R(0) of Omicron variant was 7.9 (95% CI: 7.4 to 8.4). With strict interventions, R(t) had dropped quickly from 3.6 (95% CI: 2.7 to 4.7) on 4th March to below 1 on 18th April. The mean transmission distance of the Omicron epidemic in Shanghai was 13.4 km (95% CI: 11.1 to 15.8 km), which was threefold longer compared with that of epidemic caused by the wild-type virus in Wuhan, China. The model estimated that there would have been a total 870,845 (95% CI: 815,400 to 926,289) cases for the epidemic from 20th February to 15th June, and 27.7% (95% CI: 24.4% to 30.9%) cases would have been unascertained. People aged 50–59 years had the highest transmission risk 0.216 (95% CI: 0.210 to 0.222), and the highest secondary attack rate (47.62%, 95% CI: 38.71% to 56.53%). CONCLUSIONS: The Omicron variant spread more quickly and widely than other variants and resulted in about one third cases unascertained for the recent outbreak in Shanghai. Prioritizing isolation and screening of people aged 40–59 might suppress the epidemic more effectively. Routine surveillance among people aged 40–59 years could also provide insight into the stage of the epidemic and the timely detection of new variants. TRIAL REGISTRATION: We did not involve clinical trial. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15596-w. BioMed Central 2023-04-22 /pmc/articles/PMC10121427/ /pubmed/37087436 http://dx.doi.org/10.1186/s12889-023-15596-w Text en © The Author(s) 2023 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
Zhu, Wenlong
Wen, Zexuan
Chen, Yue
Gong, Xiaohuan
Zheng, Bo
Liang, Xueyao
Xu, Ao
Yao, Ye
Wang, Weibing
Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic
title Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic
title_full Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic
title_fullStr Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic
title_full_unstemmed Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic
title_short Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic
title_sort age-specific transmission dynamics under suppression control measures during sars-cov-2 omicron ba.2 epidemic
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121427/
https://www.ncbi.nlm.nih.gov/pubmed/37087436
http://dx.doi.org/10.1186/s12889-023-15596-w
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