EMPIRICAL PREDICTIVE MODELS FOR THE ESTIMATION OF ECONOMICAL LOSSES AFTER SEISMIC EVENTS

Economical loss estimation methodologies are crucial tools for governments and insurance companies to predict the consequences of earthquakes. Moreover, they permit them to proper-ly plan the allocation of resources following seismic events, and to simulate possible losses scenarios at a territorial scale. In this paper empirical probabilistic predictive models to evaluate the repairing costs expected after earthquakes are presented. These probabilistic models can be applied to different building stocks, and they directly relate the seismic intensi-ty to economic losses. Such models are based on data collected after a recent earthquake oc-curred in Central Italy, concerning both ancient churches belonging to cultural heritage and school buildings, which, instead, encompass a wider range of structural typologies. More in detail, the empirical data, required to define the probabilistic models, have been obtained by combining information coming from Shake Maps, provided by the National Institute for Geo-physics and Volcanology (INGV), information on the building properties (e.g. locations, di-mensions, construction typology), provided by both the archdiocese of Camerino and San Severino, two little towns severely stroke by the 2016 Central Italy seismic sequence, and by the Ministry of Education for what concerns schools. For both the dataset analysed, data re-lated to damage suffered and funding for damage repairs have been provided by the Recon-struction Office of the Marche Region. Information related to damage, indeed, constitutes an intermediate albeit necessary step for the definition of the cost models. Finally, proposed models also provide the opportunity to directly derive fragility curves in terms of cost, to make it possible to use the research outcomes in risk frameworks based on a discrete descrip-tion of the losses.