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Empirical seismic vulnerability curve for mortality: case study of China

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  • Shaohong Wu
  • Jing Jin
  • Tao Pan

Abstract

Most seismic casualty estimations are based on the vulnerability of various categories of structure and facilities in the region concerned. These approaches require detailed inventory database of the structures and facilities in the region. In China, however, the data is not always available, especially for some underdeveloped regions. This motivates the development of empirical models that use historical casualty data for earthquakes and provide a country- or region-specific earthquake death rate as a function of ground shake. However, diminishing divergences in fitting method and obtaining higher accuracy are still a great challenge. Building on the findings of previous research, the present paper employs vulnerability curves to express the relation between seismic intensity and mortality. From data of the death rate by intensity, curves are established for the whole of China and western China. Some methodological improvements are also discussed. To validate the curves, data from four recent strong earthquakes occurred in western China are used, and the best curves for estimation are selected and compared with similar models. Results indicate that the established curves for western China give a better estimation for the four earthquakes and the logistic functions show higher accuracy. They can be used to clarify the magnitude of seismic deaths in western China when structure and facility data are unavailable. Uncertainties and the application of the models are also analyzed and discussed in the conclusion. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Shaohong Wu & Jing Jin & Tao Pan, 2015. "Empirical seismic vulnerability curve for mortality: case study of China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 645-662, June.
  • Handle: RePEc:spr:nathaz:v:77:y:2015:i:2:p:645-662
    DOI: 10.1007/s11069-015-1613-1
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    References listed on IDEAS

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    1. Vladimir Kossobokov, 2013. "Earthquake prediction: 20 years of global experiment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(2), pages 1155-1177, November.
    2. Jacopo Selva, 2013. "Long-term multi-risk assessment: statistical treatment of interaction among risks," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 67(2), pages 701-722, June.
    3. L. Cha, 1998. "Assessment of Global Seismic Loss Based on Macroeconomic Indicators," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 17(3), pages 269-283, May.
    4. Ivan Wong, 2014. "How big, how bad, how often: are extreme events accounted for in modern seismic hazard analyses?," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 72(3), pages 1299-1309, July.
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    Cited by:

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    3. Li, Shuang & Yu, Xiaohui & Zhang, Yanjuan & Zhai, Changhai, 2018. "A numerical simulation strategy on occupant evacuation behaviors and casualty prediction in a building during earthquakes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1238-1250.
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    5. Jiwen An & Xianfu Bai & Jinghai Xu & Gaozhong Nie & Xiuying Wang, 2015. "Prediction of highway blockage caused by earthquake-induced landslides for improving earthquake emergency response," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(1), pages 511-536, October.

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