Shared hazards, unequal outcomes: income-driven inequities in disaster risk
Abstract Climate-induced hazards exert uneven impacts on communities. However, conventional risk models rarely consider these disparities, which are critical for informing risk reduction decisions. Instead, they quantify risk solely based on the value of assets at risk, without accounting for how communities are differentially exposed and vulnerable to particular hazards. This has significant consequences for low-income populations, who tend to suffer most from disasters. Our study introduces an equity-sensitive framework that considers inequities in exposure and vulnerability, demonstrating how these inequities compound into well-being risks. We apply this framework in a large-scale study of coastal flooding and sea-level rise risk in the Philippines, highlighting both quantitative and spatial variations in asset and well-being risks. Findings indicate that accounting for income-driven inequities yields a more comprehensive understanding of coastal flood risks across groups. This framework is adaptable for other hazards and contexts, and aims to promote more equitable disaster risk reduction outcomes.
Authors
- Perrine Hamel (ORCID: https://orcid.org/0000-0002-3083-8205)
- Maricar Rabonza (ORCID: https://orcid.org/0000-0001-7428-4788)
- Jeanette Choong
- Adam D. Switzer (ORCID: https://orcid.org/0000-0002-4352-7852)
- David Lallemant (ORCID: https://orcid.org/0000-0001-5759-9972)
- Dennis Wagenaar (ORCID: https://orcid.org/0000-0001-5215-6435)
Institutions
- Nanyang Technological University (SG)
- Earth Observatory of Singapore (SG)
Publication Details
- Journal
- npj natural hazards.
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1038/s44304-025-00087-2
- Citations
- 7
- Primary Topic
- Disaster Management and Resilience
- Type
- article
- Field-Weighted Citation Impact
- 29.41
Funders
- National Research Foundation
- National Research Foundation Singapore
- Ministry of Education - Singapore
- Ministry of Education, India
- National Supercomputing Centre Singapore