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Measuring social vulnerability to natural hazards at the district level in Botswana
Social vulnerability to natural hazards has become a topical issue in the face of climate change. For disaster risk reduction strategies to be effective, prior assessments of social vulnerability have to be undertaken. This study applies the household social vulnerability methodology to measure soci...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AOSIS
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6556939/ https://www.ncbi.nlm.nih.gov/pubmed/31205611 http://dx.doi.org/10.4102/jamba.v11i1.447 |
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author | Dintwa, Kakanyo F. Letamo, Gobopamang Navaneetham, Kannan |
author_facet | Dintwa, Kakanyo F. Letamo, Gobopamang Navaneetham, Kannan |
author_sort | Dintwa, Kakanyo F. |
collection | PubMed |
description | Social vulnerability to natural hazards has become a topical issue in the face of climate change. For disaster risk reduction strategies to be effective, prior assessments of social vulnerability have to be undertaken. This study applies the household social vulnerability methodology to measure social vulnerability to natural hazards in Botswana. A total of 11 indicators were used to develop the District Social Vulnerability Index (DSVI). Literature informed the selection of indicators constituting the model. The principal component analysis (PCA) method was used to calculate indicators’ weights. The results of this study reveal that social vulnerability is mainly driven by size of household, disability, level of education, age, people receiving social security, employment status, households status and levels of poverty, in that order. The spatial distribution of DSVI scores shows that Ngamiland West, Kweneng West and Central Tutume are highly socially vulnerable. A correlation analysis was run between DSVI scores and the number of households affected by floods, showing a positive linear correlation. The government, non-governmental organisations and the private sector should appreciate that social vulnerability is differentiated, and intervention programmes should take cognisance of this. |
format | Online Article Text |
id | pubmed-6556939 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | AOSIS |
record_format | MEDLINE/PubMed |
spelling | pubmed-65569392019-06-14 Measuring social vulnerability to natural hazards at the district level in Botswana Dintwa, Kakanyo F. Letamo, Gobopamang Navaneetham, Kannan Jamba Original Research Social vulnerability to natural hazards has become a topical issue in the face of climate change. For disaster risk reduction strategies to be effective, prior assessments of social vulnerability have to be undertaken. This study applies the household social vulnerability methodology to measure social vulnerability to natural hazards in Botswana. A total of 11 indicators were used to develop the District Social Vulnerability Index (DSVI). Literature informed the selection of indicators constituting the model. The principal component analysis (PCA) method was used to calculate indicators’ weights. The results of this study reveal that social vulnerability is mainly driven by size of household, disability, level of education, age, people receiving social security, employment status, households status and levels of poverty, in that order. The spatial distribution of DSVI scores shows that Ngamiland West, Kweneng West and Central Tutume are highly socially vulnerable. A correlation analysis was run between DSVI scores and the number of households affected by floods, showing a positive linear correlation. The government, non-governmental organisations and the private sector should appreciate that social vulnerability is differentiated, and intervention programmes should take cognisance of this. AOSIS 2019-05-06 /pmc/articles/PMC6556939/ /pubmed/31205611 http://dx.doi.org/10.4102/jamba.v11i1.447 Text en © 2019. The Authors https://creativecommons.org/licenses/by/4.0/ Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License. |
spellingShingle | Original Research Dintwa, Kakanyo F. Letamo, Gobopamang Navaneetham, Kannan Measuring social vulnerability to natural hazards at the district level in Botswana |
title | Measuring social vulnerability to natural hazards at the district level in Botswana |
title_full | Measuring social vulnerability to natural hazards at the district level in Botswana |
title_fullStr | Measuring social vulnerability to natural hazards at the district level in Botswana |
title_full_unstemmed | Measuring social vulnerability to natural hazards at the district level in Botswana |
title_short | Measuring social vulnerability to natural hazards at the district level in Botswana |
title_sort | measuring social vulnerability to natural hazards at the district level in botswana |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6556939/ https://www.ncbi.nlm.nih.gov/pubmed/31205611 http://dx.doi.org/10.4102/jamba.v11i1.447 |
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