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A new model for the quantitative assessment of earthquake casualties based on the correction of anti-lethal level

Author

Listed:
  • Xia Chaoxu

    (China Earthquake Administration
    China Earthquake Administration)

  • Nie Gaozhong

    (China Earthquake Administration
    China Earthquake Administration)

  • Fan Xiwei

    (China Earthquake Administration
    China Earthquake Administration)

  • Li Huayue

    (China Earthquake Administration
    China Earthquake Administration
    China Earthquake Networks Center)

  • Zhou Junxue

    (China Earthquake Administration
    China Earthquake Administration
    Earthquake Administration of Guangxi Zhuang Autonomous Region)

  • Zeng Xun

    (China Earthquake Administration
    China Earthquake Administration)

Abstract

The timely and accurate assessment of casualties is the key for and basis of emergency rescue work after an earthquake. In this paper, through exponential fitting of historical seismic data, an evaluation model of death based on the building destruction ratio is proposed. Through the analysis of historical seismic data, we propose the concept of an anti-lethal level and construct the corresponding coefficient. We use factors such as earthquake magnitude, intensity, and occurrence time, the population density, and the anti-lethal level in the region as correction factors for the predicted number of casualties and build a model for evaluating the number of casualties based on coefficient correction. The evaluation results are relatively accurate; the R2 index of the proposed model is 0.8768, whereas the R2 of the two comparison models selected in this paper is 0.619 and 0.4603, respectively. The accuracy of the proposed model results is much higher than that of the other models, which illustrates the effectiveness of the model presented in this paper. It also indicates that the model proposed in this paper can provide a scientific basis and data support for earthquake emergency rescue work.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:nathaz:v:110:y:2022:i:2:d:10.1007_s11069-021-04988-z
    DOI: 10.1007/s11069-021-04988-z
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    References listed on IDEAS

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    1. Stav Shapira & Limor Aharonson-Daniel & Igal Shohet & Corinne Peek-Asa & Yaron Bar-Dayan, 2015. "Integrating epidemiological and engineering approaches in the assessment of human casualties in earthquakes," 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. 78(2), pages 1447-1462, September.
    2. Jong-Hwa Park & Myoungsu Shin & Gi-Hyoug Cho, 2016. "A dynamic estimation of casualties from an earthquake based on a time-use survey: applying HAZUS-MH software to Ulsan, Korea," 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. 81(1), pages 289-306, March.
    3. Rahman, Muhammad Habibur, 2018. "Earthquakes don’t kill, built environment does: Evidence from cross-country data," Economic Modelling, Elsevier, vol. 70(C), pages 458-468.
    4. Jong-Hwa Park & Myoungsu Shin & Gi-Hyoug Cho, 2016. "A dynamic estimation of casualties from an earthquake based on a time-use survey: applying HAZUS-MH software to Ulsan, Korea," 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. 81(1), pages 289-306, March.
    5. 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.
    6. 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.
    7. 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.
    8. Xing Huang & Huidong Jin, 2018. "An earthquake casualty prediction model based on modified partial Gaussian curve," 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. 94(3), pages 999-1021, December.
    9. 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.
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