Real time surveillance of COVID-19 space and time clusters during the summer 2020 in Spain

Rosillo, Nicols; Del-guila-Meja, Javier; Rojas-Benedicto, Ayeln; Guerrero-Vadillo, Mara; Peuelas, Marina; Mazagatos, Clara; Seg-Tell, Jordi; Ramis, Rebeca; Gmez-Barroso, Diana

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 Kulldorfs 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.