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

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.

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Publication Details

Journal
Scientific Data
Published
2024-08-31
DOI
https://doi.org/10.1038/s41597-024-03771-6
Citations
1
Primary Topic
Health disparities and outcomes
Type
article
Field-Weighted Citation Impact
0.53
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article

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

Philippe Apparicio, Jérémy Gelb, Hamzeh Alizadeh
1 citations
Scientific Data
Health disparities and outcomes
0.53
article

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

Philippe Apparicio, Jérémy Gelb, Hamzeh Alizadeh
article en
1 citations

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.

Scientific DataVol. 11(1)
Transport Canada (CA), Université de Sherbrooke (CA)
Sustainable cities and communities
Openalex Percentile: Top 31%
Health disparities and outcomes
0.53
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A synthetic vulnerable population dataset for fine scale geographical equity analysis and urban planning — Philippe Apparicio, Jérémy Gelb, et al. · Scientific Data (2024) | TGRS Research Map | TGRS