P116 - Integration of geospatial applications in the study of COVID-19’s distribution in Maroc

The coronavirus disease 2019 (COVID-19) was first detected as an outbreak of respiratory illness in Wuhan, Hubei, China. The WHO declared the COVID-19 outbreak as a public health emergency of international concern on January 30, 2020. In Maroc, the first case of coronavirus was reported on March 2, 2020. During the week of March 9-15, 2020, Maroc has launched measures to limit the spread of the epidemic. This article demonstrates the use of geospatial applications in epidemiological research in Maroc and in particular in the management of the spread of infectious diseases, namely COVID-19. To identify COVID-19 hotspots, we used spatial autocorrelation in ArcGIS 10.3 and Pearson correlation analysis to identify associative environmental factors using R 3.4.1 software. According to the obtained results, the majority of COVID-19 cases were associated with population density and certain environmental covariates. We looked at the total number of people per month with COVID-19 between the years 2020 and 2021 in each administrative region. In 2020, statistically significant outbreaks of COVID-19 (95% confidence) were identified in the urban clusters of the Casablanca-Settat, Tanger-Tétouan-El houceima and Marrakech-Safi regions. The southern regions of Maroc were statistically significant cold spots; regions with low rates of COVID-19. In 2021, there was a drastic increase in COVID-19 cases with a fairly slow rate of contaminations at the end of 2021 and the beginning of 2022. This study identified areas with high and low COVID-19 clusters and hotspots. The maps produced can serve as tools for good management in order to control, effectively eliminate the COVID-19 pandemic and contribute to an investment in epidemiological surveillance programs. Epidemiology; GIS; COVID-19; Distribution Les auteurs n'ont pas précisé leurs éventuels liens d'intérêts