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Authors: Ferreira, Monica Amaral* 
Falsaperla, Susanna* 
Oliveira, Carlos Sousa* 
Zonno, Gaetano* 
Title: Layman's Report of the European Project UPStrat-MAFA
Issue Date: Jul-2014
Keywords: Seismic impact
Disruption index
Urban system
Risk measures
Seismic hazard
Disaster prevention
Information strategies
Information strategies
UPStrat-MAFA European project
Subject Classification04. Solid Earth::04.06. Seismology::04.06.11. Seismic risk 
Abstract: Earthquakes have been the cause of the deadliest natural disasters over the past century, with the first decade of the 21st century as one of the most devastating periods. Due to the high number of factors that contribute to earthquake occurrence, their prediction is extremely difficult. At the moment, large efforts are being lavished by the international community in scientific and economic terms, in studies for the probabilistic short-term and long-term earthquake forecasting and for simulation aspects of the generation process in order to reduce the risk and to mitigate the damage and its impact. The project aims at the implementation of innovative prevention approaches to consistently link prevention measures to preparedness and response needs. To support the decisionmaking, several projects have already been developed, like seismic scenario simulators, vulnerability assessment of buildings, non-structural components, critical assets, lifeline (critical) infrastructures, and others. Despite these many efforts, neither functional interdependencies (propagation effects) nor intervention strategies or priorities have been incorporated as final tools in the support of decisions for riskreduction policies. In this project, tools that are specifically devoted to the identification of priorities have been delivered. First, a new concept of global disruption measures is introduced, with the objective to provide a systematic way to measure earthquake impact in urban areas. Then, a framework is provided where urbanized areas are seen as a complex network where nodal points have roles as sources and sinks, interacting together in an interdependent fashion. Here, each player (urban functions and physical assets) has its unique dependencies and interaction behavior. These properties are then used to identify which nodes are likely to introduce major disruption in the whole urban system, and also which one of them suggests greater risk reduction if intervention takes place.
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