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

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 capabili...

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Autores principales: Shapira, Stav, Novack, Lena, Bar-Dayan, Yaron, Aharonson-Daniel, Limor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4784842/
https://www.ncbi.nlm.nih.gov/pubmed/26959647
http://dx.doi.org/10.1371/journal.pone.0151111
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author Shapira, Stav
Novack, Lena
Bar-Dayan, Yaron
Aharonson-Daniel, Limor
author_facet Shapira, Stav
Novack, Lena
Bar-Dayan, Yaron
Aharonson-Daniel, Limor
author_sort Shapira, Stav
collection PubMed
description 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.
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spelling pubmed-47848422016-03-23 An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes Shapira, Stav Novack, Lena Bar-Dayan, Yaron Aharonson-Daniel, Limor PLoS One Research Article 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. Public Library of Science 2016-03-09 /pmc/articles/PMC4784842/ /pubmed/26959647 http://dx.doi.org/10.1371/journal.pone.0151111 Text en © 2016 Shapira et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Shapira, Stav
Novack, Lena
Bar-Dayan, Yaron
Aharonson-Daniel, Limor
An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes
title An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes
title_full An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes
title_fullStr An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes
title_full_unstemmed An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes
title_short An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes
title_sort integrated and interdisciplinary model for predicting the risk of injury and death in future earthquakes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4784842/
https://www.ncbi.nlm.nih.gov/pubmed/26959647
http://dx.doi.org/10.1371/journal.pone.0151111
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