In current practice, most earthquake risk models adopt a “declustered” view of seismicity, that is, they disregard foreshock, aftershock, and triggered earthquakes and model seismicity as a series of independent mainshock events, whose occurrence (typically) conforms to a Poisson process. This practice is certainly disputable but has been justified by the false notion that earthquakes of smaller magnitude than the mainshock cannot induce further damage than what was caused by the latter. A companion paper makes use of the epidemic-type aftershock sequence (ETAS) model fitted to Central Italy seismicity data to describe the full earthquake occurrence process, including “dependent” earthquakes. Herein, loss estimates for the region of Umbria in Central Italy are derived using stochastic event catalogs generated by means of the ETAS model and damage-dependent fragility functions to track damage accumulation. The results are then compared with estimates obtained with a conventional Poisson-based model. The potential gains of utilizing a model capable of capturing the spatiotemporal clustering features of seismicity are illustrated along with a discussion on the various details and challenges of such considerations.

在当前的实践中，大多数地震风险模型采用“减震”的地震活动性观点，即它们忽略了前震，余震和触发地震，并将地震活动性模型为一系列独立的主震事件，其发生（通常）符合泊松过程。这种作法无疑是有争议的，但已被错误的观念所证明，即，震级小于主震的地震所造成的破坏不会比主震造成的破坏更大。随附的论文使用了与意大利中部地震活动数据拟合的流行型余震序列（ETAS）模型来描述整个地震发生过程，包括“从属”地震。在这里 意大利中部翁布里亚地区的损失估计是通过使用ETAS模型生成的随机事件目录和依赖于损害的脆弱性函数来跟踪损害累积而得出的。然后将结果与使用常规基于泊松模型的估计值进行比较。举例说明了利用能够捕获地震活动的时空聚类特征的模型的潜在收益，并讨论了这些考虑因素的各种细节和挑战。