BACKGROUND: The 2020 COVID-19 pandemic led to a strict lockdown in France from March 17 to May 11, 2020. After the lockdown, the French strategy to mitigate the impact of SARS-CoV-2 relied partly on investigations of all confirmed cases. Monitoring collective settings is particularly important since SARS-CoV-2 seems prone to superspreading events (SSEs). METHODS: Our study is based on data gathered in Paris from May 11 to December 31, 2020, by the Ile-de-France Regional Health Agency (RHA) to investigate cases occurring in collective and high-risk settings. Specific events in high-risk settings were systematically transmitted to the RHA, and screenings were organized by the facilities, while other settings were reported when three cases were identified within a short period. These settings were more difficult to identify through the surveillance system since no systematic screening was organized by the facility, leaving screenings to rely on the national contact-tracing programme. No official superspreading threshold has been set for SARS-CoV-2. We defined a SSE as an event involving ten cases. RESULTS: We analysed 15,706 events associated with 38,670 cases, representing an average of 2.70 cases per event. Most clusters occurred in educational facilities, workplace environments, social care settings, and healthcare facilities. SSEs represented 3.4% but accounted for 28% of all cases reported. The highest number of SSEs occurred in college settings (12.6%), followed by hospitals and retirement homes. Educational facilities had the lowest number of SSEs, with around 1% in preschools and elementary schools. CONCLUSIONS: We observed different SSE rates in each setting. Preschools and primary schools represented the majority of events but experiencing very few SSEs. Colleges were prone to SSEs and were associated with a high number of secondary cases. These findings provide some insights on contact tracing activities and SARS-CoV-2 transmission in different settings.
Superspreading events of SARS-CoV-2 in Paris: A retrospective analysis of data from the first wave of COVID-19 in 2020