Transitions between Housing States among Urban Homeless Adults: a Bayesian Markov Model

Abstract

The purpose of this study is to explore how marginalization, substance abuse, and service utilization influence the transitions between streets, shelters, and housed states over the course of 2 years in a population of urban homeless adults. Survey responses from three yearly interviews of 400 homeless adults were matched with administrative services data collected from regional health, mental health, and housing service providers. To estimate the rates of transition between housed, street, and shelter status, a multi-state Markov model was developed within a Bayesian framework. These transition rates were then regressed on a set of independent variables measuring demographics, marginalization, substance abuse, and service utilization. Transitions from housing to shelters or streets were associated with not being from the local area, not having friends or family to count on, and unemployment. Pending charges and a recent history of being robbed were associated with the shelters-to-streets transition. Remaining on the streets was uniquely associated with engagement in “shadow work” and, surprisingly, a high use of routine services. These findings paint a picture of unique and separate processes for different types of housing transitions. These results reinforce the importance of focusing interventions on the needs of these unique housing transitions, paying particular attention to prior housing patterns, substance abuse, and the different ways that homeless adults are marginalized in our society.