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Differences in the superspreading potentials of COVID-19 across contact settings

BACKGROUND: Superspreading events (SSEs) played a critical role in fueling the COVID-19 outbreaks. Although it is well-known that COVID-19 epidemics exhibited substantial superspreading potential, little is known about the risk of observing SSEs in different contact settings. In this study, we aimed...

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Autores principales: Zhao, Yanji, Zhao, Shi, Guo, Zihao, Yuan, Ziyue, Ran, Jinjun, Wu, Lan, Yu, Lin, Li, Hujiaojiao, Shi, Yu, He, Daihai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744370/
https://www.ncbi.nlm.nih.gov/pubmed/36510138
http://dx.doi.org/10.1186/s12879-022-07928-9
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author Zhao, Yanji
Zhao, Shi
Guo, Zihao
Yuan, Ziyue
Ran, Jinjun
Wu, Lan
Yu, Lin
Li, Hujiaojiao
Shi, Yu
He, Daihai
author_facet Zhao, Yanji
Zhao, Shi
Guo, Zihao
Yuan, Ziyue
Ran, Jinjun
Wu, Lan
Yu, Lin
Li, Hujiaojiao
Shi, Yu
He, Daihai
author_sort Zhao, Yanji
collection PubMed
description BACKGROUND: Superspreading events (SSEs) played a critical role in fueling the COVID-19 outbreaks. Although it is well-known that COVID-19 epidemics exhibited substantial superspreading potential, little is known about the risk of observing SSEs in different contact settings. In this study, we aimed to assess the potential of superspreading in different contact settings in Japan. METHOD: Transmission cluster data from Japan was collected between January and July 2020. Infector-infectee transmission pairs were constructed based on the contact tracing history. We fitted the data to negative binomial models to estimate the effective reproduction number (R) and dispersion parameter (k). Other epidemiological issues relating to the superspreading potential were also calculated. RESULTS: The overall estimated R and k are 0.561 (95% CrI: 0.496, 0.640) and 0.221 (95% CrI: 0.186, 0.262), respectively. The transmission in community, healthcare facilities and school manifest relatively higher superspreading potentials, compared to other contact settings. We inferred that 13.14% (95% CrI: 11.55%, 14.87%) of the most infectious cases generated 80% of the total transmission events. The probabilities of observing superspreading events for entire population and community, household, health care facilities, school, workplace contact settings are 1.75% (95% CrI: 1.57%, 1.99%), 0.49% (95% CrI: 0.22%, 1.18%), 0.07% (95% CrI: 0.06%, 0.08%), 0.67% (95% CrI: 0.31%, 1.21%), 0.33% (95% CrI: 0.13%, 0.94%), 0.32% (95% CrI: 0.21%, 0.60%), respectively. CONCLUSION: The different potentials of superspreading in contact settings highlighted the need to continuously monitoring the transmissibility accompanied with the dispersion parameter, to timely identify high risk settings favoring the occurrence of SSEs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07928-9.
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spelling pubmed-97443702022-12-13 Differences in the superspreading potentials of COVID-19 across contact settings Zhao, Yanji Zhao, Shi Guo, Zihao Yuan, Ziyue Ran, Jinjun Wu, Lan Yu, Lin Li, Hujiaojiao Shi, Yu He, Daihai BMC Infect Dis Research BACKGROUND: Superspreading events (SSEs) played a critical role in fueling the COVID-19 outbreaks. Although it is well-known that COVID-19 epidemics exhibited substantial superspreading potential, little is known about the risk of observing SSEs in different contact settings. In this study, we aimed to assess the potential of superspreading in different contact settings in Japan. METHOD: Transmission cluster data from Japan was collected between January and July 2020. Infector-infectee transmission pairs were constructed based on the contact tracing history. We fitted the data to negative binomial models to estimate the effective reproduction number (R) and dispersion parameter (k). Other epidemiological issues relating to the superspreading potential were also calculated. RESULTS: The overall estimated R and k are 0.561 (95% CrI: 0.496, 0.640) and 0.221 (95% CrI: 0.186, 0.262), respectively. The transmission in community, healthcare facilities and school manifest relatively higher superspreading potentials, compared to other contact settings. We inferred that 13.14% (95% CrI: 11.55%, 14.87%) of the most infectious cases generated 80% of the total transmission events. The probabilities of observing superspreading events for entire population and community, household, health care facilities, school, workplace contact settings are 1.75% (95% CrI: 1.57%, 1.99%), 0.49% (95% CrI: 0.22%, 1.18%), 0.07% (95% CrI: 0.06%, 0.08%), 0.67% (95% CrI: 0.31%, 1.21%), 0.33% (95% CrI: 0.13%, 0.94%), 0.32% (95% CrI: 0.21%, 0.60%), respectively. CONCLUSION: The different potentials of superspreading in contact settings highlighted the need to continuously monitoring the transmissibility accompanied with the dispersion parameter, to timely identify high risk settings favoring the occurrence of SSEs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07928-9. BioMed Central 2022-12-12 /pmc/articles/PMC9744370/ /pubmed/36510138 http://dx.doi.org/10.1186/s12879-022-07928-9 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
Zhao, Yanji
Zhao, Shi
Guo, Zihao
Yuan, Ziyue
Ran, Jinjun
Wu, Lan
Yu, Lin
Li, Hujiaojiao
Shi, Yu
He, Daihai
Differences in the superspreading potentials of COVID-19 across contact settings
title Differences in the superspreading potentials of COVID-19 across contact settings
title_full Differences in the superspreading potentials of COVID-19 across contact settings
title_fullStr Differences in the superspreading potentials of COVID-19 across contact settings
title_full_unstemmed Differences in the superspreading potentials of COVID-19 across contact settings
title_short Differences in the superspreading potentials of COVID-19 across contact settings
title_sort differences in the superspreading potentials of covid-19 across contact settings
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744370/
https://www.ncbi.nlm.nih.gov/pubmed/36510138
http://dx.doi.org/10.1186/s12879-022-07928-9
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