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

机译:在博茨瓦纳地区一级衡量社会对自然灾害的脆弱性

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摘要

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.
机译:面对气候变化,社会对自然灾害的脆弱性已成为一个热门话题。为了使减少灾害风险战略有效,必须事先评估社会脆弱性。这项研究运用家庭社会脆弱性方法来衡量博茨瓦纳对自然灾害的社会脆弱性。总共使用了11个指标来制定地区社会脆弱性指数(DSVI)。文献提供了构成模型的指标的选择。主成分分析(PCA)方法用于计算指标的权重。这项研究的结果表明,社会脆弱性主要由家庭规模,残疾,教育程度,年龄,领取社会保障的人,就业状况,家庭状况和贫困程度依次驱动。 DSVI分数的空间分布表明,Ngamiland West,Kweneng West和Central Tutume在社会上非常脆弱。在DSVI得分和受洪水影响的家庭数量之间进行了相关分析,显示出正线性相关。政府,非政府组织和私营部门应认识到社会脆弱性有所不同,干预计划应意识到这一点。

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