Census to sense: Decoding spatio-temporal dynamics of social vulnerability to disasters in Nepal

Shrestha, A., Láng-Ritter, J., Chapagain, D., Taka, M., & Varis, O. (2026). Census to sense: Decoding spatio-temporal dynamics of social vulnerability to disasters in Nepal. International Journal of Disaster Risk Reduction 143 e106306. 10.1016/j.ijdrr.2026.106306.

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Abstract

Climate change and socio-economic transitions are intensifying disaster risks, calling for integrated, cross-disciplinary mitigation strategies. The complex dynamics of disaster vulnerability pose challenges for risk management, particularly in resource-constrained countries. Existing assessments often focus on composite vulnerability scores and obscure the multifaceted dynamics of vulnerability and its components, limiting their relevance for risk management. Addressing this gap, our study analyses spatio-temporal changes in social vulnerability and its components – sensitivity and adaptive capacity – across Nepal by applying Principal Component Analysis to municipal census data from 2011 to 2021. We (i) map vulnerability into five classes for both years, (ii) quantify decadal changes in social vulnerability and its components, and (iii) identify distinct social vulnerability transition pathways. National social vulnerability declined by 35% by 2021, as a 63% adaptive capacity gain outweighed a 28% rise in sensitivity, with spatially heterogeneous patterns. We reveal notable structural changes in dominant indicators: Sensitivity reflects persistent demographic pressures alongside growing influences of urbanization and population mobility. Adaptive capacity reflects stable contributions from critical services and asset ownership, augmented by improvements in housing quality and connectivity. Furthermore, by investigating the interaction between the shifts in sensitivity and adaptive capacity, we identify three social vulnerability transition pathways (escalating sensitivity, adaptive balance, and resilience transition) that yield actionable and spatially explicit insights for prioritising disaster risk reduction. Our refined component-focused approach offers nuanced insights beyond conventional social vulnerability assessments, is transferable to any country with census data, and is valuable in data-scarce settings.

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