A comprehensive spatial analysis of social vulnerability to natural hazards in Zimbabwe: Driving factors and policy implications

The impact of hazards on population groups has always been different, depending on the social and environmental factors of the impacted people. An enhanced understanding of what influences people?s susceptibility to hazards, how and why, is a prerequisite for designing mitigation plans, prioritizing resources for preparedness and formulating an appropriate adaptation strategy. This study therefore, assessed the geographic variation of social vulnerability to natural hazards in Zimbabwe. It used data acquired from the national statistics agency on 24 variables that reflected a wide range of social vulnerability indicators. The variables were carefully selected considering their relevance in increasing social vulnerability in Zimbabwe. Then, the study used a principal component analysis and a factor analysis technique in a GIS environment to quantify social vulnerability and model its underlying drivers respectively. The analyses revealed that 68% of the country has above moderate values of social vulnerability. Very high social vulnerability is in poor rural districts of western and southern Zimbabwe. This coincided with agro-ecological regions with low potential for food production, while the lowest vulnerability scores were in small towns. Poverty, informal employment, household heads, birth rate and the special needs population, which explained 82.065% of the total cumulative variance, drive social vulnerability. The geographic variation of social vulnerability provides policy-makers a scientific basis for resource allocation to vulnerability hotspots or key factors.

Automated summary

This study investigated the geographic variation of social vulnerability to natural hazards in Zimbabwe, finding that rural poverty-stricken areas in the western and southern regions exhibited the highest levels of social vulnerability. Factors such as poverty, informal employment, household heads, birth rate, and special needs population were identified as drivers of social vulnerability, explaining a significant portion of the total cumulative variance.