Reconstruction of Transmission Pairs for Novel Coronavirus Disease 2019 (COVID-19) in Mainland China: Estimation of Superspreading Events, Serial Interval, and Hazard of Infection

Author:

Xu Xiao-Ke1,Liu Xiao Fan2,Wu Ye34,Ali Sheikh Taslim5,Du Zhanwei6,Bosetti Paolo7,Lau Eric H Y5,Cowling Benjamin J5,Wang Lin78ORCID

Affiliation:

1. College of Information and Communication Engineering, Dalian Minzu University, Dalian, China

2. Web Mining Laboratory, Department of Media and Communication, City University of Hong Kong, Hong Kong Special Administrative Region, China

3. Computational Communication Research Center, Beijing Normal University, Zhuhai, China

4. School of Journalism and Communication, Beijing Normal University, Beijing, China

5. World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China

6. Department of Integrative Biology, University of Texas at Austin, Austin, Texas, USA

7. Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Centre National de la Recherche Scientifique (CNRS), Paris, France

8. Department of Genetics, University of Cambridge, Cambridge, United Kingdom

Abstract

AbstractBackgroundKnowledge on the epidemiological features and transmission patterns of novel coronavirus disease (COVID-19) is accumulating. Detailed line-list data with household settings can advance the understanding of COVID-19 transmission dynamics.MethodsA unique database with detailed demographic characteristics, travel history, social relationships, and epidemiological timelines for 1407 transmission pairs that formed 643 transmission clusters in mainland China was reconstructed from 9120 COVID-19 confirmed cases reported during 15 January–29 February 2020. Statistical model fittings were used to identify the superspreading events and estimate serial interval distributions. Age- and sex-stratified hazards of infection were estimated for household vs nonhousehold transmissions.ResultsThere were 34 primary cases identified as superspreaders, with 5 superspreading events occurred within households. Mean and standard deviation of serial intervals were estimated as 5.0 (95% credible interval [CrI], 4.4–5.5) days and 5.2 (95% CrI, 4.9–5.7) days for household transmissions and 5.2 (95% CrI, 4.6–5.8) and 5.3 (95% CrI, 4.9–5.7) days for nonhousehold transmissions, respectively. The hazard of being infected outside of households is higher for people aged 18–64 years, whereas hazard of being infected within households is higher for young and old people.ConclusionsNonnegligible frequency of superspreading events, short serial intervals, and a higher risk of being infected outside of households for male people of working age indicate a significant barrier to the identification and management of COVID-19 cases, which requires enhanced nonpharmaceutical interventions to mitigate this pandemic.

Funder

Investissement d’Avenir program, Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases

European Union

European Research Council

National Institutes of Health

Key Laboratory of Urban Land Resources Monitoring and Simulation

Ministry of Land and Resources of China

National Natural Science Foundation of China

National Social Science Fund of China

Health and Medical Research Fund

Food and Health Bureau

Government of the Hong Kong Special Administrative Region, China

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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