Dynamic space-time diffusion simulator in a GIS environment to tackle the Covid-19 emergency. Testing a geotechnological application in Rome

In this paper, we start from a contextualization about the measures used to contain the COVID-19 diffusion and the need to promote geotechnological proposals, data sharing and homogenous centralised systems for data collection and analysis. Successively, we present the “Dynamic SpaceTime Diffusion Simulator in a GIS Environment to Tackle the COVID-19 Emergency” that we have elaborated on the basis of the data provided by the UOC Hygiene and Public Health Service – Local Health Unit Rome 1. Particularly, after describing the main technical process able to predispose the dynamic simulator, we underline the possible added value that it can provide in terms of infection surveillance and monitoring, precision preparedness, support to decision making and territorial screening. For this demonstrative application, we have extracted from the simulator some groups of four digital screenshots which are able to show synoptic photographs in temporal perspective concerning the total number of cases of COVID-19 in Rome (Italy) for the period February 25th - September 26th. Specifically we have selected: - four screenshots for the period February 25th - June 11th, to provide significant evidence about the first three months and a half; - four screenshots for the period March 1st – March 29th, to add an insight into the geographically and statistically meaningful month of March; - four screenshots for the period June 12th - September 26th, to supply an efficacious geovisualisation of the last three months and a half available; - four screenshots for the period February 25th - September 26th, to show a cumulative elaboration aimed at geolocating all the cases recorded in the seven months examined; - four screenshots for the period March 26th - September 26th, with a distinction about the first and second data sets, for a detailed (cumulative) zoom. This simulator, elaborated for the COVID-19 emergency, can be replicated in any circumstance for which specific data and information are available for the scientific community, shared and progressively updated in order to provide a productive contribution to the identification of serious infectious disease clusters, patterns and trends, and quickly respond to specific needs.