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Spatial and spatiotemporal clustering of the covid-19 pandemic in ecuador

Abstract:

Introduction: In Ecuador, the first COVID-19 case, the disease caused by the SARS-CoV-2 vi-rus, was officially reported on February 29, 2020. As of April 2, the officially confirmed numbers of COVID-19 cases and deaths from it were 3 163 and 120, respectively, that is, a mortality rate of 3.8%. Objective: To identify spatial and spatiotemporal clusters of COVID-19 cases officially confirmed in Ecuador. Materials and methods: Case series study. An analysis of all COVID-19 cases officially confirmed in Ecuador from March 13, 2020 to April 2, 2020 was performed. Relative Risk (RR) of COVID-19 contagion was determined using the discrete Poisson distribution model in the SaTScan software. Clusters were generated using purely spatial and spatiotemporal scan statistics. Significance of each cluster was obtained through 999 iterations using the Monte Carlo simulation, obtaining the most probable random model. Results: As of April 2, spatiotemporal clustering allowed identifying two clusters in Ecuador, a main cluster in the Guayas province (area: 15 430 km2; population: 3.6 million inhabitants; RR: 7.08; p<0.000001; calculated annual incidence 1700 cases / 100 000 people) and a sec-ondary cluster in the Pichincha province (area: 88 904 km2; population: 7.1 million; RR: 0.38; p<0.000001; calculated annual incidence 737 cases / 100 000 people.) Conclusions: The implementation of COVID-19 mitigation strategies should be focused on areas of high transmission risk; therefore, spatial, and spatiotemporal clustering with SaTScan can be extremely useful for the early detection and surveillance of COVID-19 outbreaks.