Citation

Carvalhaes TM, Chester MV, Reddy AT, Allenby BR. Int. J. Disaster Risk Reduct. 2021; 57: e102165.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2021.102165

PMID

unavailable

Abstract

Identifying Disaster resilience indices (DRI) for cities and communities remains a common approach for assessing their structural ability and inherent capacity to cope with, recover from, and adapt to disasters. Particularly popular are composite DRI methodologies that are quantitative, top-down, and geographically mappable. DRI have become more comprehensive as the complexity of urban systems is increasingly acknowledged. However, DRI remain criticized as static, reductive, and inadequate when viewed under a complexity paradigm, which views urban systems as Complex Adaptive Systems (CAS), where observed properties (like resilience) emerge from many interactions among heterogenous agents in a network. Literature reviews have covered the state and trends for DRI development. Our objective is to synthesize literature at the nexus of these reviews, CAS, and Socio-ecological Systems (SES) to determine the extent to which commonly adopted indicators relate to widely accepted tenets of CAS.

FINDINGS show that DRI indicators usually relate more closely to temporal snapshots of vulnerability, and alternative framings of current indicators along with interdisciplinary approaches could better capture CAS aspects of urban resilience. Research and development should strive to develop DRI based on underlying principles of CAS and SES, and consider adapting top-down quantitative approaches with thick data, network models, and mixed-method triangulations. Explicitly associating complexity theory with DRI can (i) help researchers in socio-technical and socio-ecological domains develop improved resilience indicators and assessment methods that are clearly differentiated from vulnerability metrics, and (ii) guide policy and decision-makers, amid future uncertainty, to better identify, implement and track capacity-enhancing measures.

Language: en

Keywords

Complex adaptive systems; Disaster index; Indicators; Resilience; Socio-ecological systems; Urban systems