Ricerc@Sapienza

The importance of GIS-models to monitor the spread of infectious diseases and support emergency response has been underlined by a large body of literature and strengthened with the Covid-19 pandemic to identify possible geotechnological solutions able to recognise clusters and patterns, evaluate the presence of speed up factors and define specific actions. Many international projects and invitation to tender have represented a stimulus to test trained automatic algorithms, GIS and AI models, Earth observations and smart apps to tackle emergencies and move towards precision preparedness, also through big data digital mapping and analysis, programming and platform management, simulations and dashboard creation, cloud and webMap services. Many works have evidenced the crucial role of GIS applications to identify risk factors, optimal geolocalizations of life-saving devices and suggested ways of reaching them. In order to implement the state of the art with innovative elements, this project has been devised by considering some main objectives involved in the geography of safety, where GIS can provide notable added values to elaborate revealing models, both to monitor the spread of communicable diseases and support strategical first aid measures, that is in the case of cardiac arrest. The first aim of the project is to elaborate GIS models able to understand the spread of Covid-19 in some study areas relating the geocalizations of the cases with some variables and the presence of vulnerable facilities. The second aim is to program a system of auto-implementation in Python able to auto-update and auto-upgrade on the basis of new data. The third aim is to find optimal geolocalizations of new AEDs in unequipped areas to speed up access to community defibrillators and increase survival from cardiac arrest. The fourth aim is to develop some 3D models of buildings able to support indoor space management and decision-making in the case of ordinary and extraordinary situations.