Literature DB >> 27066298

A Comparative Analysis of Disaster Risk, Vulnerability and Resilience Composite Indicators.

Benjamin Beccari.   

Abstract

INTRODUCTION: In the past decade significant attention has been given to the development of tools that attempt to measure the vulnerability, risk or resilience of communities to disasters. Particular attention has been given to the development of composite indices to quantify these concepts mirroring their deployment in other fields such as sustainable development. Whilst some authors have published reviews of disaster vulnerability, risk and resilience composite indicator methodologies, these have been of a limited nature. This paper seeks to dramatically expand these efforts by analysing 106 composite indicator methodologies to understand the breadth and depth of practice.
METHODS: An extensive search of the academic and grey literature was undertaken for composite indicator and scorecard methodologies that addressed multiple/all hazards; included social and economic aspects of risk, vulnerability or resilience; were sub-national in scope; explained the method and variables used; focussed on the present-day; and, had been tested or implemented. Information on the index construction, geographic areas of application, variables used and other relevant data was collected and analysed.
RESULTS: Substantial variety in construction practices of composite indicators of risk, vulnerability and resilience were found. Five key approaches were identified in the literature, with the use of hierarchical or deductive indices being the most common. Typically variables were chosen by experts, came from existing statistical datasets and were combined by simple addition with equal weights. A minimum of 2 variables and a maximum of 235 were used, although approximately two thirds of methodologies used less than 40 variables. The 106 methodologies used 2298 unique variables, the most frequently used being common statistical variables such as population density and unemployment rate. Classification of variables found that on average 34% of the variables used in each methodology related to the social environment, 25% to the disaster environment, 20% to the economic environment, 13% to the built environment, 6% to the natural environment and 3% were other indices. However variables specifically measuring action to mitigate or prepare for disasters only comprised 12%, on average, of the total number of variables in each index. Only 19% of methodologies employed any sensitivity or uncertainty analysis and in only a single case was this comprehensive. DISCUSSION: A number of potential limitations of the present state of practice and how these might impact on decision makers are discussed. In particular the limited deployment of sensitivity and uncertainty analysis and the low use of direct measures of disaster risk, vulnerability and resilience could significantly limit the quality and reliability of existing methodologies. Recommendations for improvements to indicator development and use are made, as well as suggested future research directions to enhance the theoretical and empirical knowledge base for composite indicator development.

Entities:  

Year:  2016        PMID: 27066298      PMCID: PMC4807925          DOI: 10.1371/currents.dis.453df025e34b682e9737f95070f9b970

Source DB:  PubMed          Journal:  PLoS Curr        ISSN: 2157-3999


  18 in total

1.  Pinning down vulnerability: from narratives to numbers.

Authors:  Daanish Mustafa; Sara Ahmed; Eva Saroch; Heather Bell
Journal:  Disasters       Date:  2010-08-16

2.  Disaster risk from a macroeconomic perspective: a metric for fiscal vulnerability evaluation.

Authors:  Omar D Cardona; Mario G Ordaz; Mabel C Marulanda; Martha L Carreño; Alex H Barbat
Journal:  Disasters       Date:  2010-10

3.  Targeting attention on local vulnerabilities using an integrated index approach: the example of the climate vulnerability index.

Authors:  C Sullivan; J Meigh
Journal:  Water Sci Technol       Date:  2005       Impact factor: 1.915

4.  A sensitivity analysis of the social vulnerability index.

Authors:  Mathew C Schmidtlein; Roland C Deutsch; Walter W Piegorsch; Susan L Cutter
Journal:  Risk Anal       Date:  2008-07-04       Impact factor: 4.000

5.  Classification of residential areas according to physical vulnerability to natural hazards: a case study of Çanakkale, Turkey.

Authors:  Arzu Başaran-Uysal; Funda Sezen; Süha Ozden; Oznur Karaca
Journal:  Disasters       Date:  2014-01

6.  Conjoint Community Resiliency Assessment Measure-28/10 items (CCRAM28 and CCRAM10): A self-report tool for assessing community resilience.

Authors:  Dmitry Leykin; Mooli Lahad; Odeya Cohen; Avishay Goldberg; Limor Aharonson-Daniel
Journal:  Am J Community Psychol       Date:  2013-12

7.  The Communities Advancing Resilience Toolkit (CART): development of a survey instrument to assess community resilience.

Authors:  Rose L Pfefferbaum; Barbara R Neas; Betty Pfefferbaum; Fran H Norris; Richard L Van Horn
Journal:  Int J Emerg Ment Health       Date:  2013

8.  Estimating least-developed countries' vulnerability to climate-related extreme events over the next 50 years.

Authors:  Anthony G Patt; Mark Tadross; Patrick Nussbaumer; Kwabena Asante; Marc Metzger; Jose Rafael; Anne Goujon; Geoff Brundrit
Journal:  Proc Natl Acad Sci U S A       Date:  2010-01-05       Impact factor: 11.205

9.  Measuring vulnerability to natural hazards: a macro framework.

Authors:  Jacquleen Joseph
Journal:  Disasters       Date:  2012-12-27

10.  The adoption of a climate disaster resilience index in Chennai, India.

Authors:  Jonas Joerin; Rajib Shaw; Yukiko Takeuchi; Ramasamy Krishnamurthy
Journal:  Disasters       Date:  2014-07
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  9 in total

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Authors:  Sahar Derakhshan; Christopher T Emrich; Susan L Cutter
Journal:  PLoS One       Date:  2022-10-20       Impact factor: 3.752

2.  The COPEWELL Rubric: A Self-Assessment Toolkit to Strengthen Community Resilience to Disasters.

Authors:  Monica Schoch-Spana; Kimberly Gill; Divya Hosangadi; Cathy Slemp; Robert Burhans; Janet Zeis; Eric G Carbone; Jonathan Links
Journal:  Int J Environ Res Public Health       Date:  2019-07-04       Impact factor: 3.390

3.  Vulnerability indicators for natural hazards: an innovative selection and weighting approach.

Authors:  Maria Papathoma-Köhle; Matthias Schlögl; Sven Fuchs
Journal:  Sci Rep       Date:  2019-10-21       Impact factor: 4.379

4.  Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina.

Authors:  Qian Huang; Sarah Jackson; Sahar Derakhshan; Logan Lee; Erika Pham; Amber Jackson; Susan L Cutter
Journal:  PLoS One       Date:  2021-02-03       Impact factor: 3.240

5.  Advanced Operationalization Framework for Climate-Resilient Urban Public Health Care Services: Composite Indicators-Based Scenario Assessment of Khon Kaen City, Thailand.

Authors:  Wiriya Puntub; Stefan Greiving
Journal:  Int J Environ Res Public Health       Date:  2022-01-24       Impact factor: 3.390

6.  A wildfire vulnerability index for buildings.

Authors:  M Papathoma-Köhle; M Schlögl; C Garlichs; M Diakakis; S Mavroulis; S Fuchs
Journal:  Sci Rep       Date:  2022-04-16       Impact factor: 4.996

7.  Constructing a comprehensive disaster resilience index: The case of Italy.

Authors:  Sepehr Marzi; Jaroslav Mysiak; Arthur H Essenfelder; Mattia Amadio; Silvio Giove; Alexander Fekete
Journal:  PLoS One       Date:  2019-09-16       Impact factor: 3.240

8.  Climate Variability, Vulnerability, and Natural Disasters: A Case Study of Zika Virus in Manabi, Ecuador Following the 2016 Earthquake.

Authors:  Cecilia J Sorensen; Mercy J Borbor-Cordova; Emilie Calvello-Hynes; Avriel Diaz; Jay Lemery; Anna M Stewart-Ibarra
Journal:  Geohealth       Date:  2017-10-14

9.  Methodological challenges to confirmatory latent variable models of social vulnerability.

Authors:  Zachary T Goodman; Caitlin A Stamatis; Justin Stoler; Christopher T Emrich; Maria M Llabre
Journal:  Nat Hazards (Dordr)       Date:  2021-02-13
  9 in total

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