Regional Profile of Homelessness

Transcription

1 2014 Regional Profile of Homelessness Prepared by United Way of the Midlands, in partnership with the Midlands Area Consortium for the Homeless July, 2014

2 INTRODUCTION Since its founding in 1994, MACH s mission has been to collaborate with local organizations and stakeholders to address homelessness in central South Carolina. United Way of the Midlands (UWM) supports this effort by serving as the lead agency for MACH and has secured over $18 million dollars in federal funding to support homeless service providers. UWM and MACH have always promoted the importance of needs and outcome measurement, and advances in both organizational capacity and technology over the past 20 years have supported improved methods of quantifying homelessness, services and case management. UWM understands that solving homelessness can only be done as a community; as data collection techniques advance, UWM has increased our commitment to report data and use them to inform planning and make changes intended to reduce the number of people experiencing homelessness in our state. This report, prepared by United Way of the Midlands, is offered as the first in an occasional series of reports intended to help the community develop a more complete understanding of the experience of homelessness among residents of the Midlands. Homelessness is most often a temporary circumstance, making it inherently difficult to quantify. To address this, UWM analyzes multiple data sources, each of which provides information on different populations. It is important to understand that each data source is driven and supported by different objectives, funders and methodology, meaning they do not always integrate seamlessly to produce a single picture of homelessness; however, by carefully analyzing each data source, UWM is able to craft an understanding of trends affecting the different groups of people who experience homelessness. DATA SOURCES This report is supported by a range of available data; most of them collected February 1 st 2013-January 31 st, The report notes where the timeframe is different. The Homeless Management Information System (HMIS), established in 2004 and currently operated by UWM, is the most comprehensive and informative data source available to MACH. This web-based client and bed reservation system collects information on clients served at over 45 different programs and agencies in 14 South Carolina counties. In addition to providing counts of individuals and families experiencing homelessness, HMIS collects demographic and biographical information. It also records information relevant to housing stability such as employment, benefit enrollment, and case management notes. HMIS data are collected for those who receive some type of service, thus it cannot provide a profile of people who are homeless who have not requested or received services from any HMIS agency. HMIS data for this report are for the February 1st 2013-January 31st, The Point-in-Time (PIT) Count contributes information to MACH on the unsheltered population of people sleeping outside, in their vehicles, or in other places not meant to serve as residences. Volunteers scan the streets to interview those who are homeless on a single night in January. Because the PIT Count is limited to one night, it is disadvantaged by confounding variables such 1

3 as weather, volunteer participation and political climate that may influence respondents willingness to complete a survey; however, it provides one of the only estimates of the hard-toserve homeless population who do not typically access traditional services. McKinney-Vento School Data provides data about homeless school children. The McKinney- Vento definition of homelessness is less restrictive than the definition used by the U.S. Department of Housing and Urban Development (HUD) and considers children living temporarily with another family or in a hotel or motel, regardless of payment source, to be homeless. McKinney-Vento data do not include information about the students household (parents or younger siblings). The data are collected over the academic (not calendar or fiscal) year. Statistical Projections are useful because homelessness is so difficult to quantify. One common methodology for estimating homelessness is to calculate an annualized estimate based on the current poverty estimates. Literature suggests that people who are homeless represent approximately 6.3% of the persons considered to be living in poverty. Using the Census Bureau's Small Area Income and Poverty Estimates (SAIPE) estimates by county, annualized estimates can be derived by multiplying 6.3% by the Census Bureau's poverty estimate. Survey Data on public attitudes toward homelessness in Richland County are provided in the final section of the report. South Carolina Honor s College and USC Department of Psychology collaborated in 2010 and 2011 to conduct two random-digit dial telephone surveys. Students and staff called over 380 people both years to ask about citizens views of homelessness. The survey report includes the data on the experience of homelessness among the randomly selected sample of local residents. ANNUAL DATA This section of the report offers descriptive analysis from HMIS data of people who experienced homelessness in HUD has defined four broad categories under which individuals and families may qualify as homeless and be eligible to receive HUD-sponsored assistance: 1) those who are literally homeless, meaning they lack a fixed, regular and adequate nighttime residence; 2) those who are at imminent risk of being homeless (i.e. they have received an eviction notice and have no alternative place to live); 3) those who are homeless under other federal statutes such as schoolchildren who qualify for McKinney-Vento services and 4) those who are fleeing or attempting to flee domestic violence. Between January 2013 and January 2014 MACH served 6,034 homeless persons and 618 formerly homeless persons who now reside in HUD permanent supportive housing. Seventy six percent or 4,562 clients were literally homeless, while 1,472 were imminently at risk of becoming homeless. The table below indicates the type of service individuals received, while the corresponding pie chart visually represents the proportion of people receiving each service: 2

4 Table 1. Clients Served by Project Type Project Type Project Type Abbreviation Client Count Emergency Shelter ES 1344 Transitional Housing TH 935 Permanent Supportive Housing PSH 618 Services Only Program SSO 3701 Other O 99 Total 6652 The data are striking. While 44% of those served were in short or long term housing, more than half were noted as receiving only services. Some of those reported in the service-only total received financial assistance from organizations like Alston Wilkes Society and Salvation Army to maintain or acquire housing, but most (2,245) received basic services, especially at Transitions Day Center. The Day Center offers homeless individuals relief from extreme outdoor conditions and meets basic needs by providing services like showers, laundry and lunch. The large number of people receiving basic services outside of a housing setting underscores the need for additional affordable housing. WHO RECEIVES HOMELESS SERVICES IN THE MIDLANDS? Analysis of HMIS data over the last several years shows an increase in the number of people receiving services in the Midlands. In 2010, HMIS documented services and shelter stays for 2,652 people compared to the 6,652 people served in The increase in the number served is largely attributable to the 2011 opening of Transitions in downtown Columbia. Transitions opened in 2011 adding 255 new shelter and transitional housing beds, services and a day center to meet basic needs and serve as an alternative to the street during the day. Transitions has served 3,000 unduplicated clients since opening, a figure that correlates to the four year increase in people served by MACH. Prior to Transitions opening, individual adults who were homeless turned to Oliver Gospel Mission (approximately 80 emergency and transitional beds) or, during five months in winter, to the City Winter Shelter ( temporary beds). Analysis of client records for people served by Transitions shows that approximately one third of clients (941 people), had stayed at the city winter shelter or had been identified as unsheltered in a previous Point-in-Time Count (as early as 2009). While it is distressing to note that lack of local capacity appears to have contributed to chronic homelessness among almost 1,000 people, it is affirming to observe that Transitions has filled a gap. HMIS also helps understand other patterns of homelessness: 1,781 Transitions clients reported being homeless for the first time: 2,200 people completed a Transitions program and exited to positive destinations, either moving into a longer-term program at Transitions to continue focusing on skills like job training, or graduating and acquiring their own rental or permanent housing with family. Consistent 3

5 with national data, homelessness is a temporary experience for most people. The number of people experiencing homelessness for the first time, however, suggests that persistent local poverty continues to push people into homelessness. It also emphasizes the urgent need to address prevention. Finally, though an increase in HMIS numbers can be attributed to increased community capacity, increased agency participation in HMIS, and improved data quality, an increase of 250% reflects a very high demand for homeless resources. The total served increased for both individuals and families, but based on HMIS data individual adults constitute the largest group of people experiencing homelessness and receiving services in MACH s region. In , 4,745 of those who received shelter or services (71%) were individual adults. Table 2 illustrates increases by age range. Both the rate of increase and total numbers of people experiencing homelessness after age 45 are concerning. The National Alliance to End Homelessness suggests two primary demographic factors contributing to increasing incidences of homelessness among the elderly: the elderly population is growing nationally, and many older people are in precarious economic positions. Unfortunately, age contributes to vulnerability, particularly for those living on the streets, as they are more likely to experience high-risk health conditions. The 100,000 Homes Campaign s Vulnerability Index identifies seven markers creating heightened risk of mortality, and being age 60 or older is one of these risk factors. Table 2. Homeless Age Demographics: Comparison Between 2010 and 2014 Ages Year 2010 Year 2014 % Increase % % % % % % % % Table 3 compares family homelessness in 2010 and As illustrated by the table, the number of homeless families documented in HMIS has increased by 30.8%, while the number of people in homeless families has increased by 35.7%. Within family types, two parent homeless families increased by 75%, though single female headed households remain the most common type of homeless family. Table 4 contains HUD-defined race categories and the number of people who self-identified in each category. Evident in this table are the racial disparities among South Carolina s homeless population. Almost 70% of those served in 2014 were African American, more than double the proportion of African Americans in the state (28%) but reflective of the higher rate of poverty among African Americans in SC. 4

6 Table 3. Families Experiencing Homelessness: Comparison between 2010 and 2014 Year 2010 Families (N) People (N) Couple With No Children Female Single Parent Male Single Parent Other 2 6 Two Parent Family Total Year 2014 Couple With No Children Female Single Parent Foster Parent(s) 1 3 Grandparent(s) and Child 8 25 Male Single Parent Non-custodial Caregiver(s) 1 2 Other Two Parent Family Total Table 4. Homeless Clients, Race, Race Client Count % of total % of SC population homeless (2013 Census) American Indian or Alaska Native 41.6%.5% Asian 12.2% 1.5% Black or African-American % 27.9% Don't Know/Refused 27.4% NA Multiple Races 120 2% 1.7% Native Hawaiian or Other Pacific Islander 13.2%.1% White % 68.3% Null 114 2% NA Total 6652 VULNERABLE AND CHRONICALLY HOMELESS HUD considers someone to be chronically homeless if he or she has experienced homelessness four or more times in the past three years or has been homeless for one continuous year or longer. In either circumstance chronically homeless individuals also have disabling medical, physical, mental or addictive conditions. Chronically homeless individuals include the most visible street dwellers who are also among the most vulnerable and often the most difficult to serve. Many have lived on the streets for years and have difficulty transitioning to housing and reconnecting with community. They are predominately 5

7 single, and they are the highest users of emergency rooms, hospital services and other acute care services. In , 878 people (13.2%) were recognized in HMIS as chronically homeless. HUD continues to prioritize housing chronically homeless adults with disabilities, and MACH has used HUD resources to develop housing for this target population, adding 893 beds in the last 10 years. VETERANS Veterans comprised roughly 17% of the adult homeless population documented in HMIS in the Midlands in , with 957 adults self-reporting military service. The majority (83%) of veterans is male, but homelessness among female veterans is increasing: 17% of the homeless veteran population in 2013 was female. Both HUD and MACH believe that no individual who served our country should be without a home, and significant efforts are underway to reduce veteran homelessness. Columbia Housing Authority currently administers 305 Veterans Affairs Supportive Housing (HUD-VASH) vouchers that provide housing to chronically homeless veterans in need of permanent supportive housing. MACH also maintains on ongoing partnership with the local Veterans Affairs office, and a significant outreach campaign is underway to connect Veterans to housing, VA healthcare, job training and counseling for post-traumatic stress disorder (PTSD). CHILDREN HMIS recorded services and shelter stays for 1,132 homeless children in An additional year olds were homeless, an important age group that often includes youth aging out of foster care or other institutional care. The growing number of young homeless adults underscores the need for programs to serve youth who lack the support of families in an American culture where the transition to adulthood is increasingly prolonged. McKinney-Vento school data report three times the number of homeless children and youth than were identified in HMIS. During the academic year, 2,989 children attending school in one of MACH s 14 counties were either homeless by HUD s definition or by the more appropriate criteria precariously housed, which indicates frequent moves, living with one or more other families or other lack of housing stability. The two sets of data are different but complementary. HMIS includes families who have children under 18 and were in short term homeless housing programs. The school data by definition do not include younger siblings of school age children, and homeless families tend to have younger children. Neither data set fully captures the demand for affordable housing that would prevent this instability. A child experiencing homelessness endures a barrage of stressful and traumatic experiences that can profoundly impact his or her development and ability to learn. UWM and MACH are working to build a better safety net for families experiencing a housing crisis through an innovative Coordinated Assessment system designed to improve access to resources and provide better assistance to families in need. 6

8 INDIVIDUALS WITH DISABILITIES Disability information is most often obtained in HMIS by self-report, but even with this potential for underreporting, nearly 40% of people staying in an emergency shelter, transitional or permanent housing report some type of disabling condition, more than double the amount of people in the general US population who experience a disability. Disabilities can make it difficult to obtain enough work to afford housing, and this challenge is evident in the disproportionate representation of people experiencing homelessness reporting disabilities in Service-only programs are not always able to collect disability information from clients, thus the tables below show the types of disabilities recorded for the 2,897 adults in shelters and HUD-sponsored permanent housing. Table 5 lists types and frequencies of disabling conditions, while Table 6 illustrates the co-occurring nature of disabilities for many people. Table 5. Disabilities among People Experiencing Homelessness Disabling Condition Total % Mental Illness % Alcohol Abuse 208 7% Drug Abuse 237 8% Chronic Health Condition 47 2% HIV/AIDS and Related Diseases 30 1% Developmental Disability 26 1% Physical Disability % *N = 2,897, but people can experience more than one disabling condition and may be counted twice. Table 6. Co-occurring Disabilities Total None Condition Conditions Conditions 173 Condition Unknown 101 Don't Know / Refused 15 TOTAL: POINT-IN-TIME COUNT After months of organization and planning, MACH completed its one-day street count on January 23, This street count, or point-in-time (PIT) count, is conducted by trained volunteers who walk through assigned geographic territory and attempt to survey anyone who is sleeping outside. MACH identifies one or more county coordinators in each of its 14 counties, and these coordinators recruit and train volunteers, create a count schedule that spans multiple days ensuring each area is canvassed more 7

9 than once, and assign volunteers a geographic area to survey. County coordinators also organize service events such as a hot breakfast in order to create additional opportunities to survey people who may have slept outside the night before. After steadily increasing since 2009, MACH s PIT Count identified fewer people in 2014: 693 people spent the night in emergency shelters, 469 people stayed in transitional housing, and 426 people sleeping outside were surveyed. Table 7 displays PIT numbers by county. MACH s decrease followed statewide trends as the three remaining CoCs in SC also reported decreased numbers. Table 8 shows PIT counts by CoC, while Figure 9 visually illustrates the relatively stable proportion of the statewide total contributed by each CoC s Count. MACH has identified several factors contributing to lower count results in The increased capacity to serve people who are homeless in Columbia has already been noted. Transitions and its 25 agency partners offer services such employment training, mental health counseling, legal assistance and general health services that are helping people move from the street into permanent housing. Surveyors also observed that political climate contributed to a higher rate of refusal among people asked to complete the unsheltered survey this year. In general, people are reluctant to provide personal information to strangers regardless of the purpose. Homelessness has also been a politically charged topic in the Midlands this year, particularly in downtown Columbia due to proposed local plans to relocate people from downtown to a rural campus. People were less willing to provide personal or accurate information this year as a result. Table 7. PIT Count by County County Emergency Transitional Unsheltered Total Shelter Housing Aiken Allendale Bamberg Barnwell Calhoun.... Chester Fairfield Kershaw Lancaster Lexington Newberry Orangeburg Richland York

10 Table 8. The Results of the 2013 and 2014 Report for South Carolina Continuums of Care Continuum of Care Figure 9. # of Individuals Reported in 2013 (N = 6032 total) % of Total Count in 2013 Report # of Individuals Counted in 2014 (N = 5040 total) % of Total Count in 2014 Report ECHO % % Lowcountry % % MACH % % Upstate % % 2013 Report % of Total Homeless Individuals Counted in Each Continuum of Care 2014 Report % of Total Homeless Individuals Counted in Each Continuum of Care 32% N = % N = % N = % N = 650 ECHO Lowcountry MACH Upstate 33% N = % N = % N = % N = 513 ECHO Lowcountry MACH Upstate POVERTY IN SOUTH CAROLINA According to 2012 US Census Data, 18% of South Carolina residents live in poverty. Table 10 lists poverty estimates for each of the 14 MACH counties. Researchers estimate that approximately 6.3% of people living below the poverty line are homeless, and by multiplying this number by the 242,308 people living in poverty in MACH s 14 counties, we can estimate that 15,625 people experienced homelessness in 2012, nearly 3 times the amount of people who have received services from HMIS-participating agencies. 9

11 Table 10. Poverty Estimate by County Year Name Poverty Number 90% Confidence Percent 90% Universe Interval Confidence Interval 2012 Aiken County 160,465 27,465 23,622 to 31, to Allendale County 8,676 3,562 2,800 to 4, to Bamberg County 14,787 4,325 3,437 to 5, to Barnwell County 21,917 6,304 5,385 to 7, to Calhoun County 14,784 2,977 2,406 to 3, to Chester County 32,288 8,019 6,911 to 9, to Fairfield County 23,014 5,537 4,561 to 6, to Kershaw County 61,780 9,961 8,197 to 11, to Lancaster County 76,942 15,295 13,414 to 17, to Lexington County 267,854 39,034 34,662 to 43, to Newberry County 36,388 6,361 5,189 to 7, to Orangeburg 88,130 22,196 19,398 to 24, to 28.4 County 2012 Richland County 362,342 61,197 54,753 to 67, to York County 230,497 30,075 26,521 to 33, to 14.5 *Confidence intervals offer a range to represent a greater amount of certainty about estimates. DISCUSSION As long as housing remains expensive and income inequality grows, people will experience economic setbacks that may ultimately cause them to lose their homes. UWM and MACH s mission is to continue to create a safety net for people in an economic crisis and improve coordination among services and providers in order to build an efficient system of care. UWM also recognizes that a substantial number of people in the Midlands are chronically homeless, and it is our belief that we must do everything in our power to help people experiencing long-term homelessness secure homes of their own. MACH is implementing major changes as a continuum of care to better serve those who are both newly and chronically homeless. In 2013, MACH completed integration of its HMIS with ECHO, the CoC representing counties in eastern SC and with 2-1-1, an emergency helpline serving all of SC. The Lowcountry and Upstate CoCs will merge in 2014 resulting in a statewide database linked to s resources, enabling service providers to document more complete client histories and to make higher quality referrals based on real-time shelter availability and eligibility requirements. MACH is developing community measures for this newly integrated system that will identify strengths and weaknesses within the community of care. For example, MACH is beginning to monitor recidivism in order to understand how many people become homeless again after successfully exiting to permanent 10

12 housing. MACH also plans to implement a prioritization list for permanent supportive housing as a means of targeting outreach to those who are unable to work or maintain housing without assistance, with the goal of moving them from the streets to a permanent home of their own. Finally, MACH is beginning research to observe correlations between homeless experiences and their relationship to life elements such as health and healthcare, education, and criminal involvement. By continuing to analyze the data available to us, however imperfect they may be, MACH intends to offer informed, high quality services and will continue to improve countless lives. 11

13 Attitudes about Homelessness in Richland County: A report from the South Carolina Honor s College and USC Department of Psychology Bret Kloos, Ph.D. Travis Byrd The South Carolina Honor s College and USC Department of Psychology collaborated on a student research project investigating public attitudes about homelessness in Richland County. In 2010 and 2011, two random-digit dial telephone surveys were conducted in Richland County, South Carolina. Students and staff called over 380 people both years to ask about citizen s views of homelessness. This is a brief summary of student s research of public attitudes toward homelessness. The summary describes the personal characteristics of the telephone survey sample compared to demographics for Richland County. Participants shared their personal experiences with homelessness, their views about how important of a problem they consider homelessness to be for Richland County, and whether they believe that homelessness can be addressed successfully. Method Telephone surveys of Richland County residents over 18 years old were conducted with the assistance of the Survey Research Lab at the USC Institute for Public Service and Policy Research. Students were trained to conduct the random-digit-dial surveys of home residences in Richland County, SC. Data were collected in 2010 (n=415) and 2011(n=383). The survey took between minutes to complete. Demographics As is shown in Table 1 below, the demographic characteristics for the 2011 survey closely mirror those of the residents of Richland County. The 2010 survey had more female respondents, more White respondents, and an older average age than Richland County. The age of survey respondents was older than the median age reported for the Richland County census; this was expected because census data included residents younger than 18 years of age. Overall, the 2011 Survey sample appears to be representative for Richland County. 12

14 Table 1: Comparison of Demographic Data for Survey Samples and Census Data for Richland County 2010 Survey of Richland Co Survey of Richland Co. Richland County 2010 Census Male Female 32.8% 67.2% 48.7% 51.3% 48.6% 51.4% White African American Other 54.4% 41.0% 3.1% 49.1% 50.8% 0.1% 48.9% 46.3% 4.8% Average Age = 53 Median Age = 54 Average Age = 45 Median Age = 42 Median Age = 33.2 = years of college = years of college 89.6% with HS 36.2% with BA or higher $40-45,000 $40-45,000 $48,420 Age Education Median Income Experiences with Homelessness Richland County residents reported a larger than expected amount of personal experience with homelessness. In the 2011 survey, 8% of persons survey respondents had been homeless in the past (30 of 375) and 26% reported having to stay at someone else s home when they did not have a place to live (98 of 375). As noted above, the 2011 survey had a sample that was more representative of Richland County. The less representative 2010 survey reported lower rates of homeless but still surprisingly high: 5.1% had been homeless and 19.5% had to stay at someone else s home when they did not have a place to stay. Furthermore, the majority of Richland County survey respondents report interacting with someone who was homeless and getting involved in some way to address homelessness. As shown in Table 3, the surveys suggest that the majority of Richland County residents know someone who has been homeless and had a conversation with someone who they thought was homeless. About one-half of respondents reported that they had volunteered to address homelessness, more than 80% had given money to someone on the street and slightly more than half have given money to an agency that addresses homelessness. 13

15 Table 3: Personal Involvement Addressing Homelessness 2010 Survey 2011 Survey % Yes % Yes Ever Known Someone Who Has Been Homeless 57.2% 59.4% Ever Had a Conversation with Someone Who Was Homeless 77.0% 84.5% Ever Done Volunteer Work Involving Homelessness 47.2% 50.1% Ever Given Money to a Homeless Person on the Street 73.1% 82.5% Ever Given Money to an Agency that Addresses Homelessness 67.8% 60.9% Summary of Experiences with Homelessness: The survey results suggest that the majority of Richland County residents have known someone who is homeless and have been involved in addressing homelessness. Perhaps most surprising, a substantial number reported that they had themselves experienced homelessness (5-8%) or had to stay at someone else s home when they did not have a place to live (19-26%). Clearly, homelessness is an issue that touches the lives of Richland County residents and warrants attention as a pressing public policy matter. Views on Importance of Addressing Homelessness in Richland County Given the personal experience and involvement reported by survey participants, it is not surprising that the overwhelming majority viewed homelessness as an important issue for Richland County. In both the 2010 and 2011 surveys, the vast majority of randomly contacted survey respondents (89% or more) agreed that homelessness is a big problem for Richland County. Furthermore more than 94% of reported that they had compassion for those who were homeless. Nearly two thirds of respondents in both surveys (64.5 in 2010 and 65.3% in 2011) reported that they thought it was possible to end homelessness in Richland County. Table 4: Views on the Importance of Homelessness for Richland County Do you agree or disagree with these statements? 2010 Survey 2011 Survey Homelessness to be a big problem in Richland County. I feel compassion for anyone who is homeless 89.9% AGREE 11.1% DISAGREE 94.7% AGREE 5.3% DISAGREE 89% AGREE 11% DISAGREE 96% AGREE 4% DISAGREE 14

16 It is possible to end homelessness in Richland County 64.5% AGREE 35.5% DISAGREE 65.3% AGREE 34.7% DISAGREE Conclusions Homeless is an issue that touches a large number of residents of Richland County. Contrary to stereotypes, a substantial number of Richland County residents appear to have personal experience with homelessness. More than 25% of persons responding to the survey in 2011 reported that they did not have a place to stay and needed to stay at someone else s home at least once during their lives. This experience meets definitions of doubled-up homelessness used by some policy makers in tracking homelessness. Furthermore, 5-8% of survey respondents reported that they had been homeless at some point during their lives. Also contrary to some stereotypes, most people in Richland County appear to want to address homelessness and have already taken personal action to do so. Nearly all survey respondents agreed that homelessness was a big problem in Richland County and reported that they had compassion for those who were homeless. About half of the respondents report that they have volunteered to address homelessness and even more have made contributions to agencies addressing homelessness. Given the public attitudes reported in these findings, there appears to be substantial support among Richland County residents for initiatives to address homelessness as an important priority. Given the rate of persons who have personally experienced homelessness, it can be viewed as a responsibility of local government, businesses, service providers, and citizens of Columbia to find ways to better address homelessness. 15