Worldwide Predictions of Earthquake Casualty Rates with Seismic Intensity Measure and Socioeconomic Data: A Fragility-Based Formulation

Yi Victor Wang, Paolo Gardoni, Colleen Murphy, Stéphane Guerrier

Research output: Contribution to journalArticle

Abstract

This paper presents a fragility-based Bayesian formulation to predict earthquake casualty rates for countries worldwide. The earthquake casualty rate of a community is defined as the probability that a person in the community is killed or injured given an intensity measure of the earthquake at the site of the community. Casualty data of 902 earthquakes worldwide from 2013 to 2017, information on population distributions, and the national socioeconomic data are used to calibrate the model. A model based on data from 2013 to 2016 is used to predict casualty rates of earthquakes in 2017. The comparisons of the model predictions with the actual observations show good agreement. With the fragility-based formulation, the proposed model can be fully coupled with seismic hazard maps for risk analysis. An example is shown in this paper to apply the model calibrated with the full data set with reference to a worldwide seismic hazard map to conduct a fully coupled seismic risk analysis and predict the expected casualty rates and counts due to earthquakes in future years for countries worldwide.

Original languageEnglish (US)
Article number04020001
JournalNatural Hazards Review
Volume21
Issue number2
DOIs
StatePublished - May 1 2020

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Keywords

  • Bayesian approach
  • Casualty
  • Earthquake
  • Fragility
  • Prediction
  • Regression
  • Risk analysis
  • Zero-inflated model

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Environmental Science(all)
  • Social Sciences(all)

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