A synthetic vulnerable population dataset for fine scale geographical equity analysis and urban planning

Abstract

Abstract Assessing the social and economic vulnerability of populations within a given area is essential for conducting environmental equity evaluations and devising effective public policies to mitigate disparities. However, prevailing indicators used to measure socio-economic vulnerability exhibit several shortcomings. Primarily relying on factor analysis, these indicators face challenges in terms of comparability over time, lack of standardized scales, and inherent limitations associated with composite indicators. To address these shortcomings, we propose a novel approach that estimates the number of potentially vulnerable individuals by constructing a synthetic population. Our methodology, developed using open tools and datasets, offers a scalable solution applicable to the entire Canadian context. The resulting percentage of potentially vulnerable populations demonstrates strong correlations with traditional vulnerability indicators commonly used in Canada, while overcoming their inherent limitations. The generated dataset holds significant potential and serves as a valuable resource for both researchers and governmental organizations. It provides a robust foundation for conducting equity analyses, assessments, and policy evaluations, thereby facilitating evidence-based decision-making processes aimed at promoting social and economic inclusivity.