New PublicationS

An exploratory forward sortation area-level analysis of social vulnerability change and insured disaster losses in Canada

Abstract

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.

Citation: Roosmawati, N., & Goda, K. (2026). An exploratory forward sortation area-level analysis of social vulnerability change and insured disaster losses in Canada. International Journal of Disaster Risk Reduction, 141, Article 106209. https://doi.org/10.1016/j.ijdrr.2026.106209

SoVI Algorithm and MATLAB Implementation Manual: Analysis Using Canada Census 2016 / 2021 Data

We are pleased to announce the public release of the SoVI Algorithm and MATLAB Implementation Manual: Analysis Using Canada Census 2016 / 2021 Data, now openly available on Zenodo.

"This repository presents a Social Vulnerability Index (SoVI) implementation for Canada, providing a practical guide and MATLAB-based workflow for assessing community-level social vulnerability to environmental hazards and disasters. The repository outlines the SoVI algorithm, data requirements, and key methodological considerations, enabling users to analyze and map spatial patterns of social vulnerability.

The analysis uses data from the 2016 and 2021 Canadian Censuses to examine socioeconomic inequality at the Forward Sortation Area (FSA) level. A total of 1,626 FSAs common to both datasets are analyzed. This resource is intended for graduate students, researchers, and practitioners working in social vulnerability analysis, disaster risk reduction, and urban studies."

Access the SoVI/SES manual and MATLAB codes on Zenodo: https://doi.org/10.5281/zenodo.17635568

Citation: Roosmawati, N., & Goda, K. (2025). SoVI Algorithm and MATLAB Implementation Manual: Analysis Using Canada Census 2016 / 2021 Data (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17635568

Risk-based multi-hazard microzonation for earthquakes and tsunamis

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Citation: Goda, K., & Catalan, P. A. (2025). Risk-based Multi-hazard Microzonation for Earthquakes and Tsunamis. Frontiers in Earth Science, 13, 1568069. https://doi.org/10.3389/feart.2025.1568069

You can find the article in Frontiers in Earth Science

List of Publications from the CIRCLE Projects Across Various Study Areas

A Dynamic Bayesian Network Approach to Characterize Multi-Hazard Risks and Resilience in Interconnected Critical Infrastructures

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Citation: Bakhtiari, S., Najafi, M. R., Goda, K., & Peerhossaini, H. (2025). A Dynamic Bayesian Network Approach to Characterize Multi-Hazard Risks and Resilience in Interconnected Critical Infrastructures. Reliability Engineering & System Safety, 1–18. https://doi.org/10.1016/j.ress.2025.110815

You can find the article in Reliability Engineering & System Safety Journal

List of Publications from the CIRCLE Projects Across Various Study Areas

Effect of Calibration Data on Performance of Tsunami Early Warning Model

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Citation: Goda, K., Chamatidis, I., & Istrati, D. (2025). Effect of calibration data on performance of tsunami early warning model. Coastal Engineering Journal, 1–18. https://doi.org/10.1080/21664250.2025.2516324

You can find the article in Coastal Engineering Journal OR request via researchgate.net

List of Publications from the CIRCLE Projects Across Various Study Areas

Quick Loss Estimation Tool (QLET) for Seismic Risk Assessment in Canada

A new peer-reviewed article has been published in GeoHazards titled:

“Rapid Computation of Seismic Loss Curves for Canadian Buildings Using Tail Approximation Method”
Authors: Payam Momeni, Katsuichiro Goda, Navid Sirous, and Sheri Molnar

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QLET is freely available as an open-source repository on GitHub, providing both the MATLAB codes and GUI-based application for users and researchers:
https://github.com/pmomeni/QuickLossEstimationTool_QLET

Read the full article:
https://www.mdpi.com/2624-795X/6/2/26