Predicting fatality rates due to earthquakes accounting for community vulnerability

Yi Wang, Paolo Gardoni, Colleen Murphy, Stephane Guerrier

Research output: Contribution to journalArticlepeer-review


The existing prediction models for earthquake fatalities usually require a detailed building inventory that might not be readily available. In addition, existing models tend to overlook the socioeconomic characteristics of communities of interest as well as zero-fatality data points. This paper presents a methodology that develops a probabilistic zero-inflated beta regression model to predict earthquake fatality rates given the geographic distributions of earthquake intensities with data reflecting community vulnerability. As an illustration, the prediction model is calibrated using fatality data from 61 earthquakes affecting Taiwan from 1999 to 2016, as well as information on the socioeconomic and environmental characteristics of the affected communities. Using a local seismic hazard map, the calibrated prediction model is used in a seismic risk analysis for Taiwan that predicts the expected fatality rates and counts caused by earthquakes in future years.

Original languageEnglish (US)
Pages (from-to)513-536
Number of pages24
JournalEarthquake Spectra
Issue number2
StatePublished - May 2019

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geophysics


Dive into the research topics of 'Predicting fatality rates due to earthquakes accounting for community vulnerability'. Together they form a unique fingerprint.

Cite this