Shapira Stav, Novack Lena, Bar-Dayan Yaron, Aharonson-Daniel Limor
PREPARED-Center for Emergency Response Research, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Department of Emergency Medicine, Leon and Mathilde Recanati School for Community Health Professions, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
PLoS One. 2016 Mar 9;11(3):e0151111. doi: 10.1371/journal.pone.0151111. eCollection 2016.
A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences.
An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel.
the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard.
The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.
一种全面的地震相关伤亡估计技术仍然是一项尚未解决的挑战。本研究旨在整合与暴露人群特征和建筑环境相关的风险因素，以提高社区的准备和应对能力，并减轻未来的后果。
基于广泛使用的损失估计模型（HAZUS）制定了一种创新模型，通过整合通过对流行病学数据进行系统综述和荟萃分析确定的四个人为相关风险因素（年龄、性别、身体残疾和社会经济地位）。计算这些因素的共同效应量，并使用逻辑回归方程将其输入到现有模型的算法中。通过在以色列的一个高脆弱性风险地区进行伤亡估计模拟来进行敏感性分析。
综合模型结果表明，与传统模型的预测相比，伤亡总数有所增加；就特定伤害水平而言，预计死亡人数以及重伤和中度受伤人数有所增加，轻伤人数有所减少。在这方面，高风险率人口较多的城市地区被发现更脆弱。
所提出的模型提供了一种新颖的方法，能够量化人为相关因素和结构因素对地震伤亡建模结果的综合影响。在地震发生前投入精力降低人类脆弱性并增强复原力可能会导致预期伤亡人数的减少。
