BACKGROUND: one of the most affected European countries by the COVID-19 epidemic is Italy; data show the strong geographical heterogeneity of the epidemic .
OBJECTIVES: to propose an analysis strategy to ascertain the non-random nature of the spatial spread of COVID-19 cases infection and identify any territorial aggregations, in order to enhance contact tracing activities in specific areas of the Lazio Region (Central Italy) and a large urban area as Rome .
METHODS: all cases of COVID-19 of the Lazio Region notified to the Regional Service for Epidemiology, Surveillance, and Control of Infectious Diseases (Seresmi) with daily updates from the beginning of the epidemic to April 27, 2020 were considered . The analyses were carried out considering two periods (the first from the beginning of the epidemic to April 6 and the second from the beginning of the epidemic to April 27) and two different levels of spatial aggregation: the entire Lazio region excluding the Municipality of Rome, where the 377 municipalities represent the area units, and the Municipality of Rome, where the area units under study are the 155 urban areas (ZUR). The Scan statistic of Kulldorff was used to ascertain the non-random nature of the spatial spread of infected cases and to identify any territorial aggregations of cases of COVID-19 infection, using a retrospective spatial analysis in two overlapping periods .
RESULTS: analysis was conducted at regional level in the two survey periods and revealed the presence of 7 localized clusters . In the Municipality of Rome, a single cluster (Historic Centre) was identified in the first period which includes 7 urban areas, while in the second period two distinct clusters (Omo and Farnesina) were observed .
CONCLUSIONS: Scan statistics are an important surveillance tool for monitoring disease outbreaks during the active phase of the epidemic and a useful contribution to epidemiological surveillance during the COVID-19 epidemic in a specific territory.