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Earthquake loss estimation of residential buildings in Pakistan

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Pakistan is an earthquake-prone region due to its tectonic setting resulting in high hazard with moderate-to-strong ground motions and vulnerability of structures and infrastructures, leading to the loss of lives and livelihood, property damage and economic losses. Earthquake-related disaster in Pakistan is a regular and serious threat to the community; however, the country lack tools for earthquake risk reduction through early warning (pre-earthquake planning), rapid response (prompt response at locations of high risk) and pre-financing earthquake risk (property insurance against disaster). This paper presents models for physical damageability assessment and socioeconomic loss estimation of structures in Pakistan for earthquake-induced ground motions, derived using state-of-the-art earthquake loss estimation methodologies. The methodologies are being calibrated with the site-specific materials and structures response, whereas the derived models are tested and validated against recent observed earthquakes in the region. The models can be used to develop damage scenario for earthquakes (assess damaged and collapsed structures, casualties and homeless) and estimate economic losses, i.e., cost of repair and reconstruction (for a single earthquake event as well as all possible earthquakes). The models can provide help on policy- and decision-making toward earthquake risk mitigation and disaster risk reduction in Pakistan. Copyright Springer Science+Business Media Dordrecht 2014

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  • Naveed Ahmad & Qaisar Ali & Helen Crowley & Rui Pinho, 2014. "Earthquake loss estimation of residential buildings in Pakistan," 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. 73(3), pages 1889-1955, September.
  • Handle: RePEc:spr:nathaz:v:73:y:2014:i:3:p:1889-1955
    DOI: 10.1007/s11069-014-1174-8
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    2. Fatma Yerlikaya-Özkurt & Aysegul Askan, 2020. "Prediction of potential seismic damage using classification and regression trees: a case study on earthquake damage databases from 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. 103(3), pages 3163-3180, September.
    3. Mario Salgado-Gálvez & Daniela Zuloaga Romero & César Velásquez & Martha Carreño & Omar-Darío Cardona & Alex Barbat, 2016. "Urban seismic risk index for Medellín, Colombia, based on probabilistic loss and casualties estimations," 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. 80(3), pages 1995-2021, February.
    4. Mario A. Salgado-Gálvez & Daniela Zuloaga Romero & César A. Velásquez & Martha L. Carreño & Omar-Darío Cardona & Alex H. Barbat, 2016. "Urban seismic risk index for Medellín, Colombia, based on probabilistic loss and casualties estimations," 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. 80(3), pages 1995-2021, February.
    5. Mahdi Moudi & Shiyu Yan & Bahador Bahramimianrood & Xiaoping Li & Liming Yao, 2019. "Statistical model for earthquake economic loss estimation using GDP and DPI: a case study from Iran," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(2), pages 583-598, March.

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