Presenters: Maria Pia Fanti, Fabio Parisi, Valentino Sangiorgio, Walter Ukovich
Title: A Multicriteria Approach for Risk Assessment of Covid-19 in Urban District Lockdown
Duration: 20 min.
Abstract: This contribution proposes a calibrated model able to predict the risk of contagion in urban district in order to support decision of administration and identify the best strategies during and after the lockdown condition. The objective regards the achievement of a Decision Support System (DSS) to predict the risk of contagion in urban districts by considering epidemic, characteristic and social data of the territory. In addition, the DSS is able to provides different scenarios, based on different administrative policies, in order to analyse the related risks. In order to show the potential of the DSS, different administrative policies (after lockdown condition) are hypothesized: 1) limited reopening of some commercial and productive activities and prohibited moves between different urban districts; 2) partial reopening of some commercial and productive activities and people movement control, 3) the reopening of all commercial and productive activities and freedom of people movement.
Biography: Valentino Sangiorgio obtained his PhD in Risk and environmental, territorial and building development (Polytechnic of Bari, Italy). In addition, Dr. Sangiorgio studied the application of emerging technologies of the Industry 4.0 context, including Augmented Reality, Internet of Things and Smart Manufacturing in the Design and Construction Management context thanks to the participation in the European project "Future 4.0". His research activity involves a high level of interdisciplinary collaboration due to the need to reconcile classical civil engineering concepts, novel technologies and performance analysis approaches as confirmed by the research projects he has been involved in to date. He has published 26 papers (10 in international journals) and he collaborated with international universities (Universitat Politècnica de València, the Universidade do Porto and Universidade de Brasília.
Prof. Maria Pia Fanti
Dipartimento di Ingegneria Elettrica e dell’Informazione
Politecnico di Bari, Italy
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