Using Markov Modeling to Understand the Dynamics of Unhoused Populations Experiencing Serious Mental Illness

Modest transition rates into and out of chronic unsheltered homelessness meant that, although provision of supportive housing helped vulnerable people, achieving a given absolute reduction in the chronic unsheltered census required substantially more housing units than the size of the steady-state reduction. The dynamics of homeless populations complicate policy making regarding unhoused people experiencing serious mental illness.

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Publication Details

Journal
Psychiatric Services
Published
2025-11-14
DOI
https://doi.org/10.1176/appi.ps.20240450
Citations
1
Primary Topic
Homelessness and Social Issues
Type
article
Field-Weighted Citation Impact
2.82
Controls
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article

Using Markov Modeling to Understand the Dynamics of Unhoused Populations Experiencing Serious Mental Illness

Rachel Smith, Sherry Glied
1 citations
Psychiatric Services
Homelessness and Social Issues
2.82
article

Using Markov Modeling to Understand the Dynamics of Unhoused Populations Experiencing Serious Mental Illness

Rachel Smith, Sherry Glied
article en
1 citations

Abstract

Modest transition rates into and out of chronic unsheltered homelessness meant that, although provision of supportive housing helped vulnerable people, achieving a given absolute reduction in the chronic unsheltered census required substantially more housing units than the size of the steady-state reduction. The dynamics of homeless populations complicate policy making regarding unhoused people experiencing serious mental illness.

Psychiatric ServicesVol. 77(1)
Wagner College (US), New York University (US), University of Maryland, College Park (US)
Openalex Percentile: Top 7%
Homelessness and Social Issues
2.82
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