TY - JOUR
T1 - Regional multiseverity casualty estimation due to building damage following a Mw 8.8 Earthquake Scenario in Lima, Peru
AU - Ceferino, Luis
AU - Kiremidjian, Anne
AU - Deierlein, Gregory
N1 - Publisher Copyright:
© 2018, Earthquake Engineering Research Institute.
PY - 2018/11
Y1 - 2018/11
N2 - 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that empirical fatality prediction methodologies can underestimate fatality rates in countries with scarce and outdated fatality data.
AB - 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.
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U2 - 10.1193/080617EQS154M
DO - 10.1193/080617EQS154M
M3 - Review article
AN - SCOPUS:85046893766
SN - 8755-2930
VL - 34
SP - 1739
EP - 1761
JO - Earthquake Spectra
JF - Earthquake Spectra
IS - 4
ER -