Original Research

Measuring social vulnerability to natural hazards at the district level in Botswana

Kakanyo F. Dintwa, Gobopamang Letamo, Kennan Navaneetham
Jàmbá: Journal of Disaster Risk Studies | Vol 11, No 1 | a447 | DOI: https://doi.org/10.4102/jamba.v11i1.447 | © 2019 Kakanyo F. Dintwa, Gobopamang Letamo, Kannan Navaneetham | This work is licensed under CC Attribution 4.0
Submitted: 21 February 2017 | Published: 06 May 2019

About the author(s)

Kakanyo F. Dintwa, Environment Statistics Unit, Statistics Botswana, Gaborone, Botswana; and, Department of Population Studies, University of Botswana, Gaborone, Botswana
Gobopamang Letamo, Department of Population Studies, University of Botswana, Gaborone, Botswana
Kennan Navaneetham, Department of Population Studies, University of Botswana, Gaborone, Botswana


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Abstract

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.

Keywords

Botswana; District Social Vulnerability; place vulnerability; natural hazards; principal component analysis

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