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Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China
COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics, including heterogeneity and the emergence of super spreading events (SSEs) where certain individuals infect large numbers of secondary cases, is of vital importance for prediction and intervention of futu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7277812/ https://www.ncbi.nlm.nih.gov/pubmed/32456346 http://dx.doi.org/10.3390/ijerph17103705 |
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author | Zhang, Yunjun Li, Yuying Wang, Lu Li, Mingyuan Zhou, Xiaohua |
author_facet | Zhang, Yunjun Li, Yuying Wang, Lu Li, Mingyuan Zhou, Xiaohua |
author_sort | Zhang, Yunjun |
collection | PubMed |
description | COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics, including heterogeneity and the emergence of super spreading events (SSEs) where certain individuals infect large numbers of secondary cases, is of vital importance for prediction and intervention of future epidemics. Here, we collected information of all infected cases (135 cases) between 21 January and 26 February 2020 from official public sources in Tianjin, a metropolis of China, and grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of four generations. Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k (lower value indicating higher heterogeneity) to be 0.67 (95% CI: 0.54–0.84) and 0.25 (95% CI: 0.13–0.88), respectively. A super-spreader causing six infections was identified in Tianjin. In addition, our simulation allowing for heterogeneity showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since 28 January. Our results highlighted more efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors. |
format | Online Article Text |
id | pubmed-7277812 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72778122020-06-12 Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China Zhang, Yunjun Li, Yuying Wang, Lu Li, Mingyuan Zhou, Xiaohua Int J Environ Res Public Health Article COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics, including heterogeneity and the emergence of super spreading events (SSEs) where certain individuals infect large numbers of secondary cases, is of vital importance for prediction and intervention of future epidemics. Here, we collected information of all infected cases (135 cases) between 21 January and 26 February 2020 from official public sources in Tianjin, a metropolis of China, and grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of four generations. Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k (lower value indicating higher heterogeneity) to be 0.67 (95% CI: 0.54–0.84) and 0.25 (95% CI: 0.13–0.88), respectively. A super-spreader causing six infections was identified in Tianjin. In addition, our simulation allowing for heterogeneity showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since 28 January. Our results highlighted more efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors. MDPI 2020-05-24 2020-05 /pmc/articles/PMC7277812/ /pubmed/32456346 http://dx.doi.org/10.3390/ijerph17103705 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Yunjun Li, Yuying Wang, Lu Li, Mingyuan Zhou, Xiaohua Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China |
title | Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China |
title_full | Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China |
title_fullStr | Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China |
title_full_unstemmed | Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China |
title_short | Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China |
title_sort | evaluating transmission heterogeneity and super-spreading event of covid-19 in a metropolis of china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7277812/ https://www.ncbi.nlm.nih.gov/pubmed/32456346 http://dx.doi.org/10.3390/ijerph17103705 |
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