Analysis of post-event damage data for supporting risk-modelling process

Post-event damage and needs assessment can supply relevant information to feed risk models. Yet, data collected in the aftermath of disasters are usually not suitable for this aim as damage explicative variables (i.e. hazard, exposure, etc.) are missing or are unsuitable referring to different spatial or temporal scales than those used by damage models. Within this context, the present paper proposes a framework to support the development of multi-purposes ex-post scenarios. The paper emphasis how the model allows the rationalization of efforts currently implemented in ex-post damage assessments. Furthermore, it highlights how shared procedure and integrated interpretations are relevant to both obtain improved damage data to feed risk models and more complete picture of a disastrous event.