Literature DB >> 33914344

Determinants of Risk Disparity Due to Infrastructure Service Losses in Disasters: A Household Service Gap Model.

Amir Esmalian1, Shangjia Dong2, Natalie Coleman1, Ali Mostafavi1.   

Abstract

The objective of this article is to systematically assess and identify factors affecting risk disparity due to infrastructure service disruptions in extreme weather events. We propose a household service gap model that characterizes societal risks at the household level by examining service disruptions as threats, level of tolerance of households to disruptions as susceptibility, and experienced hardship as an indicator for the realized impacts of risk. The concept of "zone of tolerance" for the service disruptions was encapsulated to account for different capabilities of the households to endure the adverse impacts. The model was tested and validated in the context of power outages through survey data from the residents of Harris County in the aftermath of Hurricane Harvey in 2017. The results show that households' need for utility service, preparedness level, the existence of substitutes, possession of social capital, previous experience with disasters, and risk communication affect the zone of tolerance within which households cope with service outages. In addition, sociodemographic characteristics, such as race and residence type, are shown to influence the zone of tolerance, and hence the level of hardship experienced by the affected households. The results reveal that population subgroups show variations in the tolerance level of service disruptions. The findings highlight the importance of integrating social dimensions into the resilience planning of infrastructure systems. The proposed model and results enable human-centric hazards mitigation and resilience planning to effectively reduce the risk disparity of vulnerable populations to service disruptions in disasters.
© 2021 Society for Risk Analysis.

Entities:  

Keywords:  Community resilience; equitable resilience; infrastructure systems; risk disparity; service gap model; societal risks

Mesh:

Year:  2021        PMID: 33914344     DOI: 10.1111/risa.13738

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  2 in total

1.  Quantifying community resilience based on fluctuations in visits to points-of-interest derived from digital trace data.

Authors:  Cristian Podesta; Natalie Coleman; Amir Esmalian; Faxi Yuan; Ali Mostafavi
Journal:  J R Soc Interface       Date:  2021-04-28       Impact factor: 4.118

2.  Location intelligence reveals the extent, timing, and spatial variation of hurricane preparedness.

Authors:  Bo Li; Ali Mostafavi
Journal:  Sci Rep       Date:  2022-09-27       Impact factor: 4.996

  2 in total

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