Project Overview
The public health crisis engendered by the COVID-19 pandemic has fueled unprecedented efforts to address the risk of infection and transmission among vulnerable populations, including provision of non-congregate housing to people experiencing homelessness. The expedited implementation of housing services also addresses one of the oldest and most entrenched contributors to health disparities—lack of safe and stable housing.
In this unique moment, we have the opportunity to examine whether swift provision of housing at the community level mitigates the impact of COVID-19, as well as how doing so may affect the individual, social, and structural factors that contribute to consequences of COVID-19.
This project uses a mixed-methods study of Operation Safer Ground (OSG), a community-level intervention deployed to stem COVID-19 infection among people experiencing homelessness in Alameda County, CA. Initiated in April 2020, OSG provides long-term housing to homeless people who are vulnerable to COVID-19 infection because of age (>65 years) or chronic illness. To date, more than 1,000 people, roughly 10% of the county’s homeless population, have entered OSG.
By pursuing this unique opportunity, we will gain valuable knowledge to help improve the long-term response to the pandemic and prepare more effectively to protect the health of vulnerable populations in future public health crises.
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Research Aims
This study is a “natural experiment.” In Aim 1, we will use document reviews and qualitative interviews with OSG participants, staff, and local public health officials to describe the development and implementation of the program, define its operational characteristics, and investigate contextual factors that influence outcomes for program participants. We will use the Consolidated Framework for Implementation Research (CFIR) to structure this inquiry.
In Aims 2 and 3, we will compare individual-level outcomes over time among the intervention group (OSG clients) with outcomes among similar non-clients in a carefully constructed comparison group, which we will create using propensity score weighting methods. We will incorporate mediation and moderation analyses to examine mechanisms and interactions that help explain outcomes. Data will be drawn from a county-level database called the Social Health Information Exchange (SHIE), a centralized system that coordinates health care, housing, and social service use by county Medicaid consumers with complex health and social needs. Approximately 8,000 homeless consumers, including all OSG participants, are represented in the SHIE.