The scarcity of detailed claims data for building contents (Coverage C) from historical earthquake events poses a significant challenge for property insurance catastrophe models to reliably estimate the losses associated to building contents. To develop content vulnerability functions empirically, one would need to have access to data from a multitude of historical events; however, loss disaggregation by coverage is rarely reported even when claims data become available from recent significant events such as Maule (2010) and Tohoku (2011). While damage to the building structure (Coverage A) can be estimated analytically using simulation-based fragility functions to amend sparse historical observations, the adoption of analytical approaches for other coverages is limited in the current generation of catastrophe models. In the absence of analytical methods, content loss estimation often relies on a combination of expert opinion and abstract reasoning on top of precious-little available data which is often limited to residential properties. In this paper, the authors employ FEMA P-58’s component-based methodology to develop a framework for simulation-based derivation of content vulnerability functions. Following a review of published literature and the types of content components in FEMA P-58’s PACT library, the authors present the simulation-driven vulnerability function for a four-story office building in Los Angeles, and compare the results against respective functions for office buildings from commercial models. Moreover, this paper discusses the need for new content component types in offices and professional service occupancy. Through this study, the authors demonstrate the possibility of improving content loss estimates in catastrophe models by adopting approaches similar to those involved in the development of structural vulnerability functions.
Rokneddin, Keivan; Safiey, Amir; Javanbarg, Mohammad; Manghnani, Vijay; and Pang, Weichiang, "Analytical Content Vulnerability Assessment Methodology for Earthquake Catastrophe Models" (2017). Publications. 23.