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Indicator-based assessment of capacity development for disaster preparedness in the Indian context

Capacity building and monitoring of response capacity are critical to disaster preparedness. Assessing disaster response capacity is a challenging task in India due to diverse geo-climatic conditions and exposure to different disasters. This paper addresses the absence of a methodological framework...

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Autores principales: George, Shine, Kumar, P. P. Anil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107602/
https://www.ncbi.nlm.nih.gov/pubmed/35602179
http://dx.doi.org/10.1007/s10669-022-09856-0
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author George, Shine
Kumar, P. P. Anil
author_facet George, Shine
Kumar, P. P. Anil
author_sort George, Shine
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description Capacity building and monitoring of response capacity are critical to disaster preparedness. Assessing disaster response capacity is a challenging task in India due to diverse geo-climatic conditions and exposure to different disasters. This paper addresses the absence of a methodological framework to measure multiple aspects of the disaster response capacity of districts in India through indicators. 26 indicators were identified under four factors namely; resources, communication and coordination, budget, and community engagement; anchored on a theoretical framework evolved through literature survey and key informant interviews. Each factor was modelled as a linear function of indicators based on data-sets maintained by district authorities. A Composite Index was constructed as a weighted aggregation of four factors using weightings elicited through Questionnaire Surveys among 151 expert respondents. Weightings were derived through an extension of Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) to balance the variability in perceptions of respondents. As disasters demand quick response, assessment of response capacity with a fewer number of indicators is desirable. Therefore, a reduced set of critical indicators sensitive to the Indian context were derived through model reduction applying probabilistic and statistical methods—[Formula: see text] norm-based sensitivity analysis and coefficient of variation method. Critical indicators are: number of rescue and health service personnel, NGOs, Self-Help-Groups; efficacy of existing SOPs; literacy; and budget options. Robustness of the Composite Index was checked in terms of sensitivity to weightings and model reduction. The critical indicators and the Composite Index would sensitize decision-makers on disaster response capacities across districts.
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spelling pubmed-91076022022-05-16 Indicator-based assessment of capacity development for disaster preparedness in the Indian context George, Shine Kumar, P. P. Anil Environ Syst Decis Article Capacity building and monitoring of response capacity are critical to disaster preparedness. Assessing disaster response capacity is a challenging task in India due to diverse geo-climatic conditions and exposure to different disasters. This paper addresses the absence of a methodological framework to measure multiple aspects of the disaster response capacity of districts in India through indicators. 26 indicators were identified under four factors namely; resources, communication and coordination, budget, and community engagement; anchored on a theoretical framework evolved through literature survey and key informant interviews. Each factor was modelled as a linear function of indicators based on data-sets maintained by district authorities. A Composite Index was constructed as a weighted aggregation of four factors using weightings elicited through Questionnaire Surveys among 151 expert respondents. Weightings were derived through an extension of Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) to balance the variability in perceptions of respondents. As disasters demand quick response, assessment of response capacity with a fewer number of indicators is desirable. Therefore, a reduced set of critical indicators sensitive to the Indian context were derived through model reduction applying probabilistic and statistical methods—[Formula: see text] norm-based sensitivity analysis and coefficient of variation method. Critical indicators are: number of rescue and health service personnel, NGOs, Self-Help-Groups; efficacy of existing SOPs; literacy; and budget options. Robustness of the Composite Index was checked in terms of sensitivity to weightings and model reduction. The critical indicators and the Composite Index would sensitize decision-makers on disaster response capacities across districts. Springer US 2022-05-15 2022 /pmc/articles/PMC9107602/ /pubmed/35602179 http://dx.doi.org/10.1007/s10669-022-09856-0 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
George, Shine
Kumar, P. P. Anil
Indicator-based assessment of capacity development for disaster preparedness in the Indian context
title Indicator-based assessment of capacity development for disaster preparedness in the Indian context
title_full Indicator-based assessment of capacity development for disaster preparedness in the Indian context
title_fullStr Indicator-based assessment of capacity development for disaster preparedness in the Indian context
title_full_unstemmed Indicator-based assessment of capacity development for disaster preparedness in the Indian context
title_short Indicator-based assessment of capacity development for disaster preparedness in the Indian context
title_sort indicator-based assessment of capacity development for disaster preparedness in the indian context
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107602/
https://www.ncbi.nlm.nih.gov/pubmed/35602179
http://dx.doi.org/10.1007/s10669-022-09856-0
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