# Measuring the Seismic Resilience of Housing Systems in Italy
###### Abstract  
In recent decades, one of the most interesting innovations has undoubtedly been the application of resilience principles to the study and mitigation of seismic risk. However, although new rigorous mathematical models have become available in the context of seismic resilience assessment, their applications to real case studies focus on a local scale, or even single structures. Consequently, new models and procedures are absolutely necessary to adopt resilience measurements in the formulation of mitigation strategies on a national or subnational scale. Given the crucial role of residential buildings in the global resilience of Italian cities against major earthquakes, a new framework for large-scale applications is proposed to roughly measure the seismic resilience of communities through the integration of an empirical recovery function based on the reconstruction process of housing systems in the aftermath of the 2012 Northern Italy Earthquake. As a first attempt, the framework is applied to housing systems in the southern regions of Italy by modelling their physical damage with vulnerability curves defined on the basis of macroseismic approaches. The main results are presented and discussed in terms of average functionality levels over time in order to compare and understand the recovery capacity of the considered housing systems. resilience; risk analysis; residential buildings; risk management; seismic engineering; decision making +
Footnote †: journal: Applied sciences  
0000-0002-4000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-00000-0000-0000-00000-00  
The PEOPLES resilience framework [10; 11; 12] is conceptually derived from [PERSON] et al. [8] and considers seven dimensions (i.e., physical infrastructures, economic development, organized governmental services, population, lifestyle, ecosystem and environment, and social capital) to measure community resilience. Based on the PEOPLES framework, a software was developed by [PERSON] et al. [13] to quantify disaster community resilience. In particular, through a comparison between four different recovery scenarios, this software was tested in Italy on the case study of the 2009 L'Aquila earthquake. A resilience simulation model called ResiUs was implemented and run inside a modelling software to help educate users about the alternative approaches to enhance recovery and resilience [14]. Such a model was built upon the prototype model of [PERSON] and [PERSON] [9]. It defines hazard-related damage and recovery over time of buildings and lifelines using parameters calibrated on the basis of the 1994 Northridge earthquake data. The ResiUs model works with a macro-subdivision of area (i.e., neighborhoods of a broader community) and uses fragility curves and Markov chains to model damage/loss and recovery over time, respectively. Although the modules to model lifeline recovery were not evaluated (more details in this direction are provided by [PERSON] [15]), the recovery model for both households and businesses require some data (i.e., amount of disaster aid per household, savings and structural mitigation of household and business, building year, tenure and building's type of business) to be simulated. To improve the resilience of communities, the National Institute of Standards and Technology (NIST) proposed an approach/methodology that allows local governments a six-step planning process [16]. It helps communities prioritize resilience actions for buildings and infrastructure systems. In this regard, the resilience of infrastructure systems can be measured in terms of time to recover functionality, including the following aspects [17]: ability to recover rapidly, damage and loss of functionality, existing system condition, and hazard intensity. [PERSON] et al. [18] develops the Centerville Virtual Community in order to build an integrated decision-making model capable of interacting with physical and social infrastructure systems.