Emergency homeless shelter use in the Dublin region 2012–2016: Utilizing acluster analysis of administrative data

Richard Waldron, Bernie O'Donoghue-Hynes, Declan Redmond

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
18 Downloads (Pure)

Abstract

Arising out of a decade of economic recession and austerity, Ireland is currently in the grip of a severe housing crisis marked by weak housing supply, rapidly rising house prices and rents and a dramatic increase in homelessness that is placing severe pressure on the State’s emergency accommodation system. This article utilises data from a national homelessness services database (PASS system), which captures live information on service user interactions for all state funded NGO and local authority homeless services, to examine the patterns of emergency accommodation use by the homeless population in Dublin City. The paper applies a k-means cluster analysis to determine different subgroups of Dublin’s homeless population (n=12,734) and analyses their rate of movement through homeless services between the years 2012 and 2016. A temporary cluster (78%) experienced a small number of homeless episodes for relatively short periods of time, while an episodic cluster (10%) experienced multiple homeless episodes also for a short period of time. The chronic cluster (12%) experienced a small number of homeless episodes but with long stays in emergency shelter. Results for Ireland show patterns similar to those reported in the US, Canada and Denmark, where a small number of chronic users of homeless accommodation account for a disproportionately large share of resources (i.e. 50% of total bed nights). The findings have implications for the operation of emergency homeless accommodation in Ireland and, in particular, the targeting of interventions and the redirecting of resources away from emergency accommodation responses towards a more effective emergency accommodation system for all stakeholders.
Original languageEnglish
Pages (from-to)143-152
Number of pages10
JournalCities
Volume94
Early online date13 Jun 2019
DOIs
Publication statusPublished - Nov 2019

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