Understanding how social vulnerability evolves over time is essential for assessing broad patterns of societal exposure to hazards. This study develops and compares Social Vulnerability Index (SoVI) scores for Canadian Forward Sortation Areas (FSAs) using the 2016 and 2021 Census data, providing a national-level, spatially explicit exploratory assessment of temporal changes in vulnerability and their spatial correspondence with insured disaster losses across Canada. Principal component analysis (PCA) is applied to derive underlying socioeconomic dimensions, and both SoVI and a standardized socioeconomic status (SES) index are constructed using consistent methodologies to enable cross-year comparison. Spatial patterns are examined using global and local Moran’s I and Getis–Ord Gi* statistics to identify clustering, including hot spots and cold spots of vulnerability. Relative comparisons suggest that from 2016 to 2021, Canadian FSAs experienced modest increases in SoVI alongside general declines in SES, being consistent with broader national-scale patterns of higher vulnerability and lower socioeconomic conditions. Both indicators exhibit significant spatial clustering, with high–high clusters most prevalent in parts of Alberta, Saskatchewan, and Manitoba. Local Moran’s I results align with Getis–Ord Gi* hotspot analysis, indicating regionally concentrated vulnerability patterns. A spatial comparison of socio-economic vulnerability (SoVI and SES) and cumulative insured disaster losses reveals both areas of alignment and divergence across FSAs. Insured loss captures an important dimension of disaster impact shaped by exposure, asset values, and insurance coverage, providing a valuable lens for examining national-scale patterns. Framed as an exploratory, national-scale screening exercise, the study leverages FSAs to enable consistent linkage with insured-loss data across Canada, while acknowledging that casuality of these spatial relationships cannot be concluded and finer-scale heterogeneity lies beyond its scope. The results offer a broad benchmarking perspective on the relationship between social vulnerability and insured losses, helping to guide and prioritize more detailed future analyses. • •Principal component analysis of census data identifies major contributing factors to social vulnerability in Canada, including demographic characteristics, socioeconomic conditions, and access to resources. • •Social vulnerability exhibits spatial clustering at the Forward Sortation Area (FSA) level, with persistent hot spot and cold spot patterns indicating broad regional disparities. • A spatial comparison between social vulnerability and insured disaster losses highlights areas of co-occurrence and divergence, reflecting the complex relationship between socioeconomic conditions and insured economic impacts.
Roosmawati et al. (Fri,) studied this question.