Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China
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Open Access
- 24 May 2020
- journal article
- research article
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 17 (10), 3705
- https://doi.org/10.3390/ijerph17103705
Abstract
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.Funding Information
- National Natural Science Foundation of China (82041023)
This publication has 21 references indexed in Scilit:
- Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected PneumoniaThe New England Journal of Medicine, 2020
- Spatial and temporal dynamics of superspreading events in the 2014–2015 West Africa Ebola epidemicProceedings of the National Academy of Sciences of the United States of America, 2017
- MERS, SARS, and Ebola: The Role of Super-Spreaders in Infectious DiseaseCell Host & Microbe, 2015
- The role of superspreading in Middle East respiratory syndrome coronavirus (MERS-CoV) transmissionEurosurveillance, 2015
- Chains of transmission and control of Ebola virus disease in Conakry, Guinea, in 2014: an observational studyThe Lancet Infectious Diseases, 2015
- Inference of R0 and Transmission Heterogeneity from the Size Distribution of Stuttering ChainsPLoS Computational Biology, 2013
- Super-spreaders in infectious diseasesInternational Journal of Infectious Diseases, 2011
- Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious DiseasesPLOS ONE, 2007
- Superspreading and the effect of individual variation on disease emergenceNature, 2005
- Factors that make an infectious disease outbreak controllableProceedings of the National Academy of Sciences of the United States of America, 2004