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An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes

Overview
Journal PLoS One
Date 2016 Mar 10
PMID 26959647
Citations 2
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Abstract

Background: A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences.

Methods: An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel.

Results: the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard.

Conclusion: The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

Citing Articles

3 edizione Giornate della ricerca scientifica e delle esperienze professionali dei giovani: Società Italiana di Igiene, Medicina Preventiva e Sanità Pubblica (SItI) 25-26 marzo 2022.

J Prev Med Hyg. 2022; 63(1 Suppl 1):E1-E57.

PMID: 36017074 PMC: 9364697. DOI: 10.15167/2421-4248/jpmh2022.63.1s1.


Predicting the cumulative number of disaster deaths during the early stage of earthquakes.

Fujimoto M, Nishiura H Ann Transl Med. 2021; 9(3):241.

PMID: 33708868 PMC: 7940899. DOI: 10.21037/atm-20-5784.

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