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