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Preliminary Quantitative Assessment of Earthquake Casualties and Damages

Author

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  • José Badal
  • Miguel Vázquez-prada
  • Álvaro González

Abstract

Prognostic estimations of the expected number of killed or injured people and about the approximate cost associated with the damages caused by earthquakes are made following a suitable methodology of wide-ranging application. For the preliminary assessment of human life losses due to the occurrence of a relatively strong earthquake we use a quantitative model consisting of a correlation between the number of casualties and the earthquake magnitude as a function of population density. The macroseismic intensity field is determined in accordance with an updated anelastic attenuation law, and the number of casualties within areas of different intensity is computed using an application developed in a geographic information system (GIS) environment, taking advantage of the possibilities of such a system for the treatment of space-distributed data. The casualty rate, defined as the number of killed people divided by the number of inhabitants of the affected region, is also computed and we show its variation for some urban concentrations with different population density. For a rough preliminary evaluation of the direct economic cost derived from the damages, equally through a GIS-based tool, we take into account the local social wealth as a function of the gross domestic product of the country. This last step is performed on the basis of the relationship of the macroseismic intensity to the earthquake economic loss in percentage of the wealth. Such an approach to the human casualty and damage levels is carried out for sites near important cities located in a seismically active zone of Spain, thus contributing to an easier taking of decisions in emergency preparedness planning, contemporary earthquake engineering and seismic risk prevention. Copyright Springer 2005

Suggested Citation

  • José Badal & Miguel Vázquez-prada & Álvaro González, 2005. "Preliminary Quantitative Assessment of Earthquake Casualties and Damages," 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. 34(3), pages 353-374, March.
    • Handle: RePEc:spr:nathaz:v:34:y:2005:i:3:p:353-374
    DOI: 10.1007/s11069-004-3656-6
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    Citations

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    Cited by:

    1. Jiajun Wang & Zhichao He & Wenguo Weng, 2020. "A review of the research into the relations between hazards in multi-hazard risk analysis," 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. 104(3), pages 2003-2026, December.
    2. Muhammet Gul & Ali Fuat Guneri, 2016. "An artificial neural network-based earthquake casualty estimation model for Istanbul city," 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. 84(3), pages 2163-2178, December.
    3. Tongyan Zheng & Lei Li & Chong Xu & Yuandong Huang, 2023. "Spatiotemporal Analysis of Earthquake Distribution and Associated Losses in Chinese Mainland from 1949 to 2021," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    4. S. Turkan & G. Özel, 2014. "Modeling destructive earthquake casualties based on a comparative study for Turkey," 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(2), pages 1093-1110, June.
    5. Chaoxu Xia & Gaozhong Nie & Huayue Li & Xiwei Fan & Wenhua Qi, 2023. "A composite database of casualty-inducing earthquakes in mainland 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. 116(3), pages 3321-3351, April.
    6. Jin‐Feng Wang & Lian‐Fa Li, 2008. "Improving Tsunami Warning Systems with Remote Sensing and Geographical Information System Input," Risk Analysis, John Wiley & Sons, vol. 28(6), pages 1653-1668, December.
    7. Stav Shapira & Tsafrir Levi & Yaron Bar-Dayan & Limor Aharonson-Daniel, 2018. "The impact of behavior on the risk of injury and death during an earthquake: a simulation-based study," 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. 91(3), pages 1059-1074, April.
    8. Lizhe Jia & Hui Li & Zhongdong Duan, 2012. "Convex model for gross domestic product-based dynamic earthquake loss assessment method," 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. 60(2), pages 589-604, January.
    9. Xia Chaoxu & Nie Gaozhong & Fan Xiwei & Li Huayue & Zhou Junxue & Zeng Xun, 2022. "A new model for the quantitative assessment of earthquake casualties based on the correction of anti-lethal level," 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. 110(2), pages 1199-1226, January.
    10. 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.
    11. Yingchun Li & Zhongliang Wu & Yizhe Zhao, 2011. "Estimating the number of casualties in earthquakes from early field reports and improving the estimate with time," 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. 56(3), pages 699-708, March.

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