Probabilistic Model for Regional Multiseverity Casualty Estimation due to Building Damage Following an Earthquake

Abstract

This paper introduces a probabilistic formulation for the estimation of the spatial distribution of multiseverity casualties due to earthquakes. The formulation assesses the number, severity, and distribution of injuries in the affected region. The model is an essential component of resilience formulations of health care systems in a community because it represents the demand on the system. Moreover, the model extends the performance-based earthquake engineering (PBEE) framework from single-building analysis to multiple-building analysis. The paper gives a full description of both the underlying statistical interdependencies among the model’s variables and the extension of the formulation of the PBEE integral to a regional context with multiple buildings. Thus, the formulation advances current methodologies that focus only on single casualty types (e.g., Prompt Assessment of Global Earthquakes for Response [PAGER]) or on the mean number of casualties (e.g., Hazus) rather than their joint probability distribution. Two numerical algorithms are presented in this paper to solve for the casualty model: one based on traditional forward Monte Carlo and another based on the central limit theorem (CLT). It is shown that the latter model is highly computationally efficient while providing accurate results.