Related papers: Dynamics of homelessness in urban America
Homelessness in American cities is becoming an ever more prominent issue, but its causes remain contested, ranging from mental health and substance abuse to housing affordability and local labor markets. To shed light on this issue, I…
Homelessness in the United States has surged to levels unseen since the Great Depression. However, existing methods for monitoring it, such as point-in-time (PIT) counts, have limitations in terms of frequency, consistency, and spatial…
The growing homelessness crisis in the U.S. presents complex social, economic, and public health challenges, straining shelters, healthcare, and social services while limiting effective interventions. Traditional assessment methods struggle…
The overwhelming majority of homeless individuals are jobless, despite many expressing a willingness to work. While this strong individual-level link between homelessness and unemployment is well-documented, the broader impact of labor…
Current sources of data on rental housing - such as the census or commercial databases that focus on large apartment complexes - do not reflect recent market activity or the full scope of the U.S. rental market. To address this gap, we…
Recent studies suggest social media activity can function as a proxy for measures of state-level public health, detectable through natural language processing. We present results of our efforts to apply this approach to estimate…
The social networks of people experiencing homelessness are an understudied but vital aspect of their lives, offering access to information, support, and safety. In 2023, the U.S. Department of Housing and Urban Development reported 653,100…
Urban house prices are strongly associated with local socioeconomic factors. In literature, house price modeling is based on socioeconomic variables from traditional census, which is not real-time, dynamic and comprehensive. Inspired by the…
AI-powered scarce resource allocation policies rely on predictions to target either specific individuals (e.g., high-risk) or settings (e.g., neighborhoods). Recent research on individual-level targeting demonstrates conflicting results;…
Urban displacement - when a household is forced to relocate due to conditions affecting its home or surroundings - often results from rising housing costs, particularly in wealthy, prosperous cities. However, its dynamics are complex and…
Nowadays, 23% of the world population lives in multi-million cities. In these metropolises, criminal activity is much higher and violent than in either small cities or rural areas. Thus, understanding what factors influence urban crime in…
This paper analyzes the differences in poverty in high wealth communities and low wealth communities. We first discuss methods of measuring poverty and analyze the causes of individual poverty and poverty in the Bay Area. Three cases are…
In many metropolitan areas efforts are made to count the homeless to ensure proper provision of social services. Some areas are very large, which makes spatial sampling a viable alternative to an enumeration of the entire terrain. Counts…
This paper investigates how to best compare algorithms for predicting chronic homelessness for the purpose of identifying good candidates for housing programs. Predictive methods can rapidly refer potentially chronic shelter users to…
Over the past two decades, a variety of methods have been used to count the homeless in large metropolitan areas. In this paper, we report on an effort to count the homeless in Los Angeles County, one that employed the sampling of census…
Within the field of media framing, homelessness has been a historically under-researched topic. Framing theory states that the media's method of presenting information plays a pivotal role in controlling public sentiment toward a topic. The…
Racial residential segregation is interconnected with several other phenomena such as income inequalities, property values inequalities, and racial disparities in health and in education. Furthermore, recent literature suggests the…
Understanding how housing values evolve over time is important to policy makers, consumers and real estate professionals. Existing methods for constructing housing indices are computed at a coarse spatial granularity, such as metropolitan…
Homelessness among US veterans remains a critical public health challenge, yet risk prediction offers a pathway for proactive intervention. In this retrospective prognostic study, we analyzed electronic health record (EHR) data from…
This paper uses privacy preserving methods to link over 235,000 records in the housing and homelessness system of care (HHSC) of a major North American city. Several machine learning pairwise linkage and two clustering algorithms are…