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Article

Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China

by 1,†, 1,†, 2, 3 and 1,2,4,*
1
Department of Biostatistics, School of Public Health, Peking University, Xueyuan Road, Beijing 100191, China
2
Beijing International Center for Mathematical Research, Peking University, Yiheyuan Road, Beijing 100871, China
3
School of Mathematical Sciences, Peking University, Peking University, Yiheyuan Road, Beijing 100871, China
4
Center for Statistical Science, Peking University, Yiheyuan Road, Beijing 100871, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2020, 17(10), 3705; https://doi.org/10.3390/ijerph17103705
Received: 29 April 2020 / Revised: 14 May 2020 / Accepted: 21 May 2020 / Published: 24 May 2020
(This article belongs to the Special Issue Transmission Dynamics of Novel Coronavirus Disease 2019 (COVID-19))
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. View Full-Text
Keywords: COVID-19; super spreading; transmission heterogeneity COVID-19; super spreading; transmission heterogeneity
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MDPI and ACS Style

Zhang, Y.; Li, Y.; Wang, L.; Li, M.; Zhou, X. Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China. Int. J. Environ. Res. Public Health 2020, 17, 3705. https://doi.org/10.3390/ijerph17103705

AMA Style

Zhang Y, Li Y, Wang L, Li M, Zhou X. Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China. International Journal of Environmental Research and Public Health. 2020; 17(10):3705. https://doi.org/10.3390/ijerph17103705

Chicago/Turabian Style

Zhang, Yunjun, Yuying Li, Lu Wang, Mingyuan Li, and Xiaohua Zhou. 2020. "Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China" International Journal of Environmental Research and Public Health 17, no. 10: 3705. https://doi.org/10.3390/ijerph17103705

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