Abstract
The study of epidemic spread has generally relied on the description of certain number of cases of an infectious diseases like COVID-19 in relation to time occurrence of disease manifestations rather than to the exact place of occurrence. In recent times, computer generated dot maps have facilitated the modeling of the spread of infectious epidemic diseases either with classical statistics approaches or with artificial ``intelligent systems''. When new cases occur in relatively distant locations, it is very difficult to determine whether they constitute a cluster. The identification of the spatial clustering should be the first step when developing effective policies to manage and control any new epidemic.
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