Bayesian framework for updating seismic loss functions with limited observational data in low-to-moderate seismicity regions

In low-to-moderate seismicity regions, seismic loss functions (SLFs) are barely established due to limited observational data, making it difficult to derive decision-making on disaster prevention and management. Herein, a Bayesian framework is developed to update the SLFs with limited observational data. The proposed point-based Bayesian method updates local probability density function parameters for damage ratios at each seismic intensity, which helps to avoid an unrealistic underestimation of damage ratios in the low-to-moderate range of seismic intensities. The feasibility of the developed framework in a low-to-moderate seismicity region is verified by the comparison between the updated SLF and post-event data.