We propose a novel data-driven framework for assessing the a-priori epidemic risk of a geographical area and for identifying high-risk areas within a country. Our risk index is evaluated as a function of three different components: the hazard of the disease, the exposure of the area and the vulnerability of its inhabitants. As an application, we discuss the case of COVID-19 outbreak in Italy. We characterize each of the twenty Italian regions by using available historical data on air pollution, human mobility, winter temperature, housing concentration, health care density, population size and age. We find that the epidemic risk is higher in some of the Northern regions with respect to Central and Southern Italy. The corresponding risk index shows correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can help explaining why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto have suffered much more than the rest of the country. Although the COVID-19 outbreak started in both North (Lombardia) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk. Our framework can be extended and tested on other epidemic data, such as those on seasonal flu, and applied to other countries. We also present a policy model connected with our methodology, which might help policy-makers to take informed decisions.

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Transport decision-making problems are typically spatially based and involve a set of feasible alternatives with multiple evaluation criteria. Besides, transport decisions affect citizens’ quality of life, as well as specific interests of general stakeholders (e.g., transport companies), thus needing a participatory approach to decision-making. Geographic Information Systems (GIS) have the ability to visualize spatial data and represent the impact of location based transport alternatives, thus helping experts to conduct robust assessments. Moreover, with the recent diffusion of Volunteered Geographic Information (VGI) and development of Public Participatory GIS (PPGIS) platforms, the process can be enhanced thanks to the collection of a large amount of updated spatial data and the achievement of an active community participation. In this study, we provide an overview based on a structured literature review of the use of VGI and PPGIS in transport studies, exploring the fields of application, role played by GIS, level of public involvement and decision stage at which they are applied. From the overview’s results, we propose a general framework for the evaluation of transport alternatives using GIS from a multiple stakeholder point of view; the main conclusion is the usefulness of the integration between Public Participation, GIS and quantitative evaluation methods, in particular Multi Criteria Decision Analysis, in order to foster technically sound and shared decisions.

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