After the 2009 L’Aquila earthquake, a procedure was developed for assigning reconstruction grants to buildings with usability ratings of B, C, or E following the outcome of the post-earthquake usability assessment (AeDES forms). Although the procedure is complex due to the need to account for various scenarios, the calculation of reconstruction costs depends on two main factors: the observed damage and the assessed vulnerability level. For masonry buildings, which make up more than 90% of structures in smaller centres, vulnerability is determined by combining nine contributions that represent key factors influencing the overall vulnerability assessment. This work investigates whether a classification model with satisfactory performance metrics can be developed to predict cost classes using only synthetic vulnerability data. The goal is to calibrate a model that can reasonably estimate reconstruction costs using only vulnerability features, which can be assessed even without damage information following a seismic event. Such models are crucial for calculating earthquake insurance premiums, which are expected to depend on a building’s vulnerability.

Predicting post-earthquake reconstruction costs of masonry buildings from seismic vulnerability features / Di Battista, Nicola; Aloisio, Angelo; D'Alfonso, Tiziana; Fico, Raffaello. - In: PROCEDIA STRUCTURAL INTEGRITY. - ISSN 2452-3216. - 78:(2026), pp. 412-417. [10.1016/j.prostr.2025.12.053]

Predicting post-earthquake reconstruction costs of masonry buildings from seismic vulnerability features

Di Battista, Nicola;D'Alfonso, Tiziana;
2026

Abstract

After the 2009 L’Aquila earthquake, a procedure was developed for assigning reconstruction grants to buildings with usability ratings of B, C, or E following the outcome of the post-earthquake usability assessment (AeDES forms). Although the procedure is complex due to the need to account for various scenarios, the calculation of reconstruction costs depends on two main factors: the observed damage and the assessed vulnerability level. For masonry buildings, which make up more than 90% of structures in smaller centres, vulnerability is determined by combining nine contributions that represent key factors influencing the overall vulnerability assessment. This work investigates whether a classification model with satisfactory performance metrics can be developed to predict cost classes using only synthetic vulnerability data. The goal is to calibrate a model that can reasonably estimate reconstruction costs using only vulnerability features, which can be assessed even without damage information following a seismic event. Such models are crucial for calculating earthquake insurance premiums, which are expected to depend on a building’s vulnerability.
2026
Machine learning; Masonry building; Post-earthquake reconstruction costs; Post-earthquake usability class
01 Pubblicazione su rivista::01a Articolo in rivista
Predicting post-earthquake reconstruction costs of masonry buildings from seismic vulnerability features / Di Battista, Nicola; Aloisio, Angelo; D'Alfonso, Tiziana; Fico, Raffaello. - In: PROCEDIA STRUCTURAL INTEGRITY. - ISSN 2452-3216. - 78:(2026), pp. 412-417. [10.1016/j.prostr.2025.12.053]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1764862
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