Year: 2022
Type: article
Study design: Observational Study
Abstract: Introduction SARS-CoV-2, which causes COVID-19, has spread rapidly across the world. A dedicated surveillance system was implemented in France in January 2020 to improve early detection of cases and their contacts and limit secondary transmission. Our objective was to use contact-tracing data collected during this initial phase of the epidemic to better characterize SARS-CoV-2 transmission. Methods We analysed data collected during contact tracing and retrospective epidemiological investigations in France from 24 January to 30 March 2020. We assessed the secondary clinical attack rate and characterized the risk of a contact becoming a case. We described chains of transmission and estimated key parameters of spread. Results Over the study period, 6,082 contacts of 735 confirmed cases were traced. The overall secondary clinical attack rate was 4.1% (95%CI 3.6-4.6) and increased with age of the index case and of the contact. Family contacts were at higher risk of becoming cases (adjusted odds ratio 2.1 (95%CI 1.4-3.0)) while nosocomial contacts were at lower risk (adjusted odds ratio 0.3 (95%CI 0.1-0.7)), compared to coworkers/friends. We identified 328 infector/infectee pairs, 49% of which were family members. The distribution of secondary cases was highly over-dispersed with 80% of secondary cases being caused by 10% of cases. The mean serial interval was 5.1 days (interquartile range 2-8 days) in contact-tracing pairs where late transmission events may be censored, and 6.8 (3-8) days in pairs investigated retrospectively. Conclusion This study contributes to improving our knowledge of SARS-CoV-2 transmission, such as the importance of superspreading events. Contact-tracing data are challenging to collect but are key to better understand emerging pathogens. Funding statement This work was supported by the LabEx “Integrative Biology of Emerging Infectious Diseases (IBEID)” (Grant Number ANR-10-LABX-62-IBEID), Santé Publique France, the INCEPTION project (PIA/ANR-16-CONV-0005), and the European Union’s Horizon 2020 research and innovation program under grants 101003589 (RECOVER) and 874735 (VEO).
Source: Eurosurveillance
Authors: Juliette Paireau, Alexandra Mailles, Catherine Eisenauher, Franck de Laval, François Delon, Paolo Bosetti, Henrik Salje, Valérie Pontiès, Simon Cauchemez
Institutions: Centre National de la Recherche Scientifique, Institut Pasteur, Santé Publique France, Génomique évolutive, modélisation et santé, Inserm, Aix-Marseille Université, Service de Santé des Armées, Economic & Social Sciences, Health Systems & Medical Informatics, Institut de Recherche pour le Développement, University of Cambridge
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
Awards: Viral dynamics at the individual and population levels: impact for antiviral treatment optimization, G1979782309, Versatile Emerging infectious disease Observatory, G282427092, G434337789, Rapid European SARS-CoV-2 Emergency research Response, Institut Convergences pour l’étude de l’Emergence des Pathologies au Travers des Individus et des populatiONs, G6122222817, G7240651115, Integrative Biology of Emerging Infectious Diseases, G8670608220
OpenAlex ID: W4211086680