a total of 622 cases of SARS-CoV-2 infection compatible with the Omicron variant (BA.1/B.1.1.529) (1) were studied by the Contact Tracing Programe in Cantabria, Spain. A total of 1,420 close contacts (household, social, and occupational) were identified; 455 secondary cases were identified. We report the main epidemiologic characteristics of these cases, such as secondary attack rate (SAR), transmission period, incubation period, and serial interval, and compared these characteristics with those for Delta variant cases.

SARS-CoV-2 Omicron variant (BA.1/B.1.1.529) quickly spread during December 2021 in Cantabria, a northern region of Spain. In total 622 cases were studied, and 1.420 close contacted were individually contact-traced and followed up. Secondary Attack Rates (SAR) and Transmission, Incubation and Serial Interval periods were estimated and compared with Delta cases. Greater transmission was found (Omicron SAR 39% vs 26%) with an increased tendency to asymptomatic or early infectiousness.

Background On June 21st de-escalation measures and state-of-alarm ended in Spain after the COVID-19 first wave. New surveillance and control strategy was set up to detect emerging outbreaks. Aim To detect and describe the evolution of COVID-19 clusters and cases during the 2020 summer in Spain. Methods A near-real time surveillance system to detect active clusters of COVID-19 was developed based on Kulldorf’s prospective space-time scan statistic (STSS) to detect daily emerging active clusters. Results Analyses were performed daily during the summer 2020 (June 21st – August 31st) in Spain, showing an increase of active clusters and municipalities affected. Spread happened in the study period from a few, low-cases, regional-located clusters in June to a nationwide distribution of bigger clusters encompassing a higher average number of municipalities and total cases by end-August. Conclusion STSS-based surveillance of COVID-19 can be of utility in a low-incidence scenario to help tackle emerging outbreaks that could potentially drive a widespread transmission. If that happens, spatial trends and disease distribution can be followed with this method. Finally, cluster aggregation in space and time, as observed in our results, could suggest the occurrence of community transmission.