Title
Regional multiseverity casualty estimation due to building damage following a Mw 8.8 Earthquake Scenario in Lima, Peru
Date Issued
01 November 2018
Access level
metadata only access
Resource Type
review
Author(s)
Kiremidjian A.
Deierlein G.
Stanford University
Publisher(s)
Earthquake Engineering Research Institute
Abstract
This paper presents the application of a rigorous probabilistic framework that estimates the number, severity, and distribution of casualties over a region. A brief summary of the model is included in this paper. The application is for casualties resulting from a Mw 8.8 earthquake scenario occurring on the subduction fault along the coastline of Lima, Peru. The case study demonstrates an application of the casualty model, including the procedures for acquiring the required information, the selection of model parameters, and a step-by-step explanation of the model-solving algorithms. The model provides an estimate of the joint probability distribution of multiseverity casualties, including spatial and across-severity correlations. This paper also shows how the model can be useful for (1) estimating 90th-percentile casualties, (2) identifying unsafe communities and structural typologies, and (3) providing evidence to support hospital collaboration policies across different districts to increase the patient treatment reliability. Additionally, the results demonstrate that empirical fatality prediction methodologies can underestimate fatality rates in countries with scarce and outdated fatality data.
Start page
1739
End page
1761
Volume
34
Issue
4
Language
English
OCDE Knowledge area
Estadísticas, Probabilidad Meteorología y ciencias atmosféricas
Scopus EID
2-s2.0-85046893766
Source
Earthquake Spectra
ISSN of the container
87552930
Sponsor(s)
This research was partially supported by NSF EAGER Grant Number CMMI-1645335 and the Shah Family Fellowship through the Department of Civil and Environmental Engineering at Stanford University. The authors are grateful for their generous support.*%blankline%*
Sources of information: Directorio de Producción Científica Scopus