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Abstract
Several mechanisms driving SARS-CoV-2 transmission remain unclear. Based on individual records of 1178 potential SARS-CoV-2 infectors and their 15,648 contacts in Hunan, China, we estimated key transmission parameters. The mean generation time was estimated to be 5.7 (median: 5.5, IQR: 4.5, 6.8) days, with infectiousness peaking 1.8 days before symptom onset, with 95% of transmission events occurring between 8.8 days before and 9.5 days after symptom onset. Most transmission events occurred during the pre-symptomatic phase (59.2%). SARS-CoV-2 susceptibility to infection increases with age, while transmissibility is not significantly different between age groups and between symptomatic and asymptomatic individuals. Contacts in households and exposure to first-generation cases are associated with higher odds of transmission. Our findings support the hypothesis that children can effectively transmit SARS-CoV-2 and highlight how pre-symptomatic and asymptomatic transmission can hinder control efforts.
Detailed knowledge of COVID-19 epidemiology is needed to inform public health responses. Here, the authors use large-scale contact tracing data to provide empirical estimates of key parameters, and show that susceptibility increases with age but transmissibility does not vary significantly.
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1 Hunan Provincial Center for Disease Control and Prevention, Hunan Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Changsha, China (GRID:grid.508374.d)
2 Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443)
3 Indiana University School of Public Health, Department of Epidemiology and Biostatistics, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X); ISI Foundation, Turin, Italy (GRID:grid.418750.f) (ISNI:0000 0004 1759 3658)
4 Sichuan University, West China School of Public Health and West China Fourth Hospital, Chengdu, China (GRID:grid.13291.38) (ISNI:0000 0001 0807 1581)
5 Fogarty International Center, National Institutes of Health, Division of International Epidemiology and Population Studies, Bethesda, USA (GRID:grid.453035.4) (ISNI:0000 0004 0533 8254)
6 ISI Foundation, Turin, Italy (GRID:grid.418750.f) (ISNI:0000 0004 1759 3658); Northeastern University, Laboratory for the Modeling of Biological and Socio-technical Systems, Boston, USA (GRID:grid.261112.7) (ISNI:0000 0001 2173 3359)
7 Indiana University School of Public Health, Department of Epidemiology and Biostatistics, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X); Northeastern University, Laboratory for the Modeling of Biological and Socio-technical Systems, Boston, USA (GRID:grid.261112.7) (ISNI:0000 0001 2173 3359)
8 Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Fudan University, Department of Infectious Diseases, Huashan Hospital, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Shanghai, China (GRID:grid.8547.e); Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443)