Abstract

PROJECT SUMMARY

Homelessness increased by 45% from 2020 to 2021, largely from economic hardship caused by the COVID-19 pandemic and has reached all-time highs across the US. More than 1.25 million people experience homelessness in the US at some point in a year, with underserved racial and ethnic groups being disproportionately affected. Denver and San Francisco are two cities in which homelessness is at crisis levels. Homelessness increased by more than 30% since 2022 in Denver and San Francisco has the highest prevalence of homelessness in the US. In both cities, Black individuals comprise between one-quarter and one-third of the homeless population despite representing only 5% of the general population. Homelessness can lead to and is associated with profound health effects. People who experience homelessness die on average 30 years earlier than other Americans and have increased risk of substance use disorders and incident HIV than people who are stably housed. It is critical that we develop feasible, effective, and cost- effective tailored approaches to improve health and decrease racial disparities in life expectancy, overdose, and HIV. Yet, while effective, evidence-based solutions that improve health outcomes exist, they are far from ubiquitously implemented. Homelessness and the health issues among people experiencing it are heterogeneous, driven by locale-specific factors. Thus, locale-specific solutions are needed urgently. Simulation models can quickly fill knowledge gaps by serving as laboratories for testing hypotheses in real- time. Models that simulate the housing continuum can be critical in augmenting randomized trials that provide evidence on system innovations, projecting the impact on health and costs. Our goal is to provide an evidence base for the prioritization and optimization of strategies and structural interventions to improve health of people experiencing homelessness and decrease racial/ethnic health disparities in HIV, overdose, and life expectancy. In Aim 1, we will employ a Group Model Building (GMB) approach to engage community stakeholders in the scientific process and inform the development of agent-based models that simulate health outcomes and racial/ethnic disparities along the housing and homelessness continuum of care. In Aim 2, we will develop agent-based models simulating the dynamic processes contributing to overdoses, HIV, and life expectancy among people along the housing continuum of care in Denver and San Francisco. In Aim 3, we will simulate and compare HIV and substance use service delivery programs implemented along the housing continuum versus housing-centered programs. We will assess changes in HIV and overdose rates among the general population experiencing homelessness. We will also examine the potential of these programs to reduce racial/ethnic disparities in these health outcomes. Through this proposal, we will develop a national resource that generates the scientific knowledge needed to improve health among people experiencing homelessness, reduce disparities, decrease overdose, and End the HIV Epidemic.

PROJECT NARRATIVE

The improving Health and Housing Outcomes through a Simulation and Economic (iHOUSE) Model is an agent-based model simulating the dynamic processes contributing to HIV incidence, overdose , and life expectancy among people along the housing and homelessness continuum of care in Denver, CO and San Francisco, CA. The project will use a Group Model Building process to engage community stakeholders in the scientific process and inform the structure of the model. The iHOUSE Model will be used to investigate potential combinations of HIV and substance use service delivery programs that are most beneficial for improving health outcomes at various steps in the housing continuum, how those compare to a housing- centered strategies, and their effectiveness at reducing racial/ethnic health disparities.

Funding

NIDA/NIH: 1R01DA061228-01

Publications

Coming soon.