Disclaimer: This list of publications is only representative of works published in direct collaboration with our lab and may not represent a complete record of an individual’s scholarly works.

Map of the Philippines showing typhoon mortality

Urban and Rural Patterns of Typhoon Mortality in the Philippines

Storms continue to be the deadliest type of weather-related disasters globally. The Philippines is one of the most at risk countries to disasters, yet there continues to be gaps in understanding where and why people are killed in typhoons – the country’s most prominent natural hazard. This research sought to understand how typhoon mortality varies across the Philippines at the municipal level, focusing on differences in rural and urban municipalities between 2005 and 2015. Generalised linear regression models (GLMs), including Poisson and negative binomial (NB), were used to analyse the relationship between typhoon mortality and level of urbanisation while controlling for social vulnerability and typhoon exposure. Findings indicate that typhoon mortality is disproportionality concentrated in emerging, rather than established, urban centres. Deaths from typhoons were significantly higher per capita in older age groups and amongst men, with drowning accounting for 71% of deaths, although there is uncertainty in these later trends which show the need for investment in national disaster databases. Our results make contributions to understanding of urban-rural patterns of disaster risk and the determinants of typhoon mortality in the Philippines.

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Map of the Philippines showing housing vulnerability

A Census-Based Housing Vulnerability Index for Typhoon Hazards in the Philippines

The Sendai Framework for Disaster Risk Reduction recognises housing as an important element of vulnerability, however, there remains limited understanding of how sub-national housing vulnerability varies spatially. This research sought to develop a municipal-level housing vulnerability index for typhoon hazards, applied at a national scale in the Philippines. We first selected 25 housing vulnerability indicators from the 2015 Philippines census, which were reduced into seven underlying dimensions of typhoon-related housing vulnerability using principal component analysis: housing density, housing quality, crowdedness, tenure security, extreme substandard housing, drinking water source, and structural integrity. These components were then aggregated to create a relative housing vulnerability index. We applied spatial clustering analysis to test for patterns, finding increasing housing vulnerability from north to south, with nuance in municipalities that defy these national trends. Our results offer a more granular view of housing vulnerability which may assist in unpacking how localised housing conditions contribute to disaster risk and assist researchers and government agencies in targeting disaster interventions.

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