Seismic insurance model for the Italian residential building stock

Asprone, Domenico; Jalayer, Fatemeh; Simonelli, Saverio; Acconcia, Antonio; Prota, Andrea; Manfredi, Gaetano

doi:10.1016/j.strusafe.2013.06.001

Cited by 33 publications

(45 citation statements)

References 10 publications

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“…The field of probabilistic hazard assessment is well established (Foote 2003;Criscimagna 2005;Stamatelatos 2000;NUREG 2012;Renn 1998;Azzaro et al 2013) and has a considerable history, due to the interest of insurance companies in the topic, see for example Asprone et al (2013). An elementary frame relying on probability is as follows.…”

Section: Probabilistic Framework: Computing Hazard and Damage Probabimentioning

confidence: 99%

“…A risk map is a geographical representation of the local probabilities of harmful events, for example seismic event of specified magnitude. Risk maps and risk profiles are needed in establishing probabilities (Keane et al 2010;Vastveit et al 2014;Asprone et al 2013;NERA 2012;SHARE 2014;Frazier et al 2013) for resilience computation. Risk maps are produced by national agencies and by some insurance companies.…”

Section: Introductionmentioning

confidence: 99%

“…The quantitative risk analysis is concerned with the determination of threats, their probabilities, the probabilities that the threats produce specified detrimental effects, and computation of the probabilities of losses under combined threats (Asprone et al 2013;Criscimagna 2005). Qualitative risk analysis and resilience study are both concerned with identifying threats and their potential effects, and possible ways of reducing threats and their effects.…”

Section: Introductionmentioning

confidence: 99%

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Defining resilience using probabilistic event trees

Teodorescu

2015

Environ Syst Decis

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The concept of resilience and various aspects related to resilience enhancement and resilience calculus are addressed in the context of the broader theme of reliability and disaster mitigation. A definition of resilience is proposed, based on the assessment of event trees and the statistical determination of risks. Essentially, we apply standard probabilistic models with conditional probabilities, event trees and fault trees, where faults are not limited to technological ones, but cover lack of personnel as well, to define the resilience in a systematic manner. An essential aspect of the approach is the estimation of the probability of recovery in a specified time frame. The time to recovery and the level of recovery play key roles in the definition. The main assumptions underlying the calculations are discussed. A synthetic resilience indicator is introduced to offer a short, easy to grasp clue on the resilience level, with the aim to facilitate planning for resilience. An analysis methodology is suggested under general conditions, and several examples of applications are given.

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Section: Probabilistic Framework: Computing Hazard and Damage Probabimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Defining resilience using probabilistic event trees

Teodorescu

2015

Environ Syst Decis

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“…In this paper, a discrete version of the Performance-based Earthquake Engineering (PBEE) framework equation (e.g., [9]) is used (see Asprone et al (2013) for more details):…”

Section: Loss Estimation Modelmentioning

confidence: 99%

“…Furthermore, according to the scenario analysis by Asprone et al (2013), the reconstruction/restoration costs for residential buildings are assumed to have a linear trend against the limit states, i, as in the following:…”

Section: Loss Estimation Modelmentioning

confidence: 99%