A study developed a model to analyze housing interventions for unsheltered individuals with serious mental illness in New York City. Using a four-state Markov model, researchers examined the movement of this population into and out of housing, utilizing data from the U.S. Census and the Department of Housing and Urban Development. The model assessed the impact of adding supportive housing and housing retention interventions. Findings indicated that the population at risk for homelessness was divided among those housed, in shelters, and experiencing chronic unsheltered homelessness. By adding around 2,000 supportive housing units, the number of chronically unsheltered individuals decreased by about 1,000. However, retention interventions showed only minor effects. The study highlighted that the rates of transition into and out of chronic unsheltered homelessness, influenced by factors such as institutionalization and death, were critical in determining outcomes. The results suggest that while supportive housing is beneficial, significantly more units may be needed to achieve notable reductions in chronic unsheltered homelessness due to the complex dynamics involved. This complicates policy-making efforts for addressing the needs of unhoused individuals with serious mental illness.