Understanding the interacting factors that influence social vulnerability: a case study of the 2016 central Italy earthquake. Frigerio, I.; Zanini, F.; Mattavelli, M.; and Amicis, M. D. Disasters, 43(4):867–890, 2019.
Understanding the interacting factors that influence social vulnerability: a case study of the 2016 central Italy earthquake [link]Paper  doi  abstract   bibtex   
This paper seeks to identify those areas that proved socially vulnerable to the earthquake that struck central Italy on 24 August 2016. The study involved four key steps. First, six relevant social vulnerability indicators were selected, based on previous conclusions in the literature. Second, the indicators were mapped using the inverse distance weighted interpolation method. Third, social vulnerability was assessed according to a spatial combination of the indicators. Fourth, in order to build a heterogeneity map, another approach was employed to represent the spatial variability of social vulnerability and to provide additional information on the synergistic contributions of the indicators. The results indicate that age and accessibility indicators affect the entire region under review, with highly vulnerable zones being close to small historical centres. These findings will be useful to governments, policymakers, and stakeholders with regard to implementing vulnerability mitigation strategies in Italian territories that are highly susceptible to earthquake hazards.
@article{frigerio_understanding_2019,
	title = {Understanding the interacting factors that influence social vulnerability: a case study of the 2016 central {Italy} earthquake},
	volume = {43},
	copyright = {© 2019 The Authors Disasters © 2019 Overseas Development Institute},
	issn = {1467-7717},
	shorttitle = {Understanding the interacting factors that influence social vulnerability},
	url = {http://onlinelibrary.wiley.com/doi/abs/10.1111/disa.12403},
	doi = {10.1111/disa.12403},
	abstract = {This paper seeks to identify those areas that proved socially vulnerable to the earthquake that struck central Italy on 24 August 2016. The study involved four key steps. First, six relevant social vulnerability indicators were selected, based on previous conclusions in the literature. Second, the indicators were mapped using the inverse distance weighted interpolation method. Third, social vulnerability was assessed according to a spatial combination of the indicators. Fourth, in order to build a heterogeneity map, another approach was employed to represent the spatial variability of social vulnerability and to provide additional information on the synergistic contributions of the indicators. The results indicate that age and accessibility indicators affect the entire region under review, with highly vulnerable zones being close to small historical centres. These findings will be useful to governments, policymakers, and stakeholders with regard to implementing vulnerability mitigation strategies in Italian territories that are highly susceptible to earthquake hazards.},
	language = {en},
	number = {4},
	urldate = {2019-09-22},
	journal = {Disasters},
	author = {Frigerio, Ivan and Zanini, Francesca and Mattavelli, Matteo and Amicis, Mattia De},
	year = {2019},
	keywords = {Italy, disaster, earthquake, indicators, risk assessment, social vulnerability},
	pages = {867--890}
}
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