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Scientific Paper

A Systematic Review of Integrated Frameworks for Resilience and Sustainability Assessments for Critical Infrastructures

, (Prof.) , (Dr) , (Prof.) , (Dr) & (Dr)
Pages 266-280 | Published online: 26 Oct 2023
 

Abstract

There is a growing tendency to assess resilience and sustainability of critical infrastructures (CI), given the significant increment in high-impact natural hazard events affecting socio-economic welfare. Historically, these assessments have been conducted separately due to the independent evolution of each concept. However, recent contributions tend to integrate them. This paper provides a state-of-the-art review of integrated assessments for resilience and sustainability in CI, examining concepts, indicators, frameworks, and methodologies. Additionally, a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis was performed to gain further insights into the prospects of integrated assessments. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, eligibility criteria were established, leading to the selection of twelve studies. These works were compared based on five dimensions (economic, environmental, social, technical, and governance) to highlight the differences in the indicators used. While all studies considered the social, environmental, and economic dimensions, some did not further analyze sufficient indicators to evaluate environmental and social effects, with governance often neglected. This study emphasizes the relevance of establishing common metrics for a convergent frame for the resilience and sustainability assessment. The findings presented suggest that integrated assessments lead to a more strategic use of resources toward more resilient CI.

Declaration and Statements

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Acknowledgements

This work was work supported by IABSE TG5.8 Resilience of existing structures and was partly financed by the Portuguese Foundation for Science and Technology (FCT) through grant number PD/2020.07208.BD, and by FEDER funds through the Competitivity Factors Operational Programme—COMPETE and by national funds through FCT (Foundation for Science and Technology) within the scope of the project POCI-01-0247-FEDER-039555. It was also partly financed by FCT / MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB / 04029/2020, and under the Associate Laboratory Advanced Production and Intelligent Systems ARISE under reference LA/P/0112/202.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Fundação para a Ciência e a Tecnologia [grant number PD/2020.07208.BD].

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