In this stage 1 registered report, we propose an analysis of the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We will compute weekly Moran index to assess spatial autocorrelation over time and identify clusters of the disease using the "flexibly shaped spatial scan" approach. Finally, different distance models will be compared to select the best suited to predict inter-municipality contagion. This study will help us understand the spread of the epidemic over the Mexican territory and give insights to model and predict the epidemic behavior.
Keywords: COVID-19; Clusters; GIS; SARS-CoV-2 pandemic; Spatial analysis; Spatial autocorrelation; Spatial modeling; Spatial patterns.
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