Georgia balance of state Continuum of Care point in time homeless count, 2019 report

Georgia Balance of State Continuum of Care Point In Time Homeless Count 2019 Report
Biannual Report: 2019 1

Overview
This report provides a snapshot of the Georgia Balance of State, Continuum of Care homeless population, homeless bed resources, and resource utilization on a single night
in January 2019. This report further outlines the methodology, analysis, results, and limitations of homeless data collection. The conclusion outlines the focused targets the Balance of State is currently implementing in effort for system improvements based on 2019 data collection. Note the data collected does not represent an absolute depiction of homelessness within the Balance of State jurisdiction; nevertheless, presents a framework
used to assess homeless needs and measure progress annually within controlled parameters.
Acknowledgements
The 2019 Point in Time Count would not have been possible without the efforts and dedication of many. The Balance of State Continuum of Care would like to present a special
thank you to the following individuals and organizations across Georgia:
Brandon Miller, Houston County Human Needs Coalition Cali Hollis, CSB of Middle GA David Blackwell, Albany-Dougherty Homeless Coalition Deborah Anglin, Hearts to Nourish Hope Devon Smyth, William S. Davies Homeless Shelters, Inc. Evan Mills, Advantage Behavioral Health Systems Jennifer Shearin, Dalton-Whitfield Community Development Corp Jessica Mitcham, Good Neighbor Homeless Shelter Jim Lindenmayer, American Legion, Cherokee County Homeless Veteran Program Katie Hagin, Gateway Behavioral Health Services Kristin J Bryant, City of Hinesville Krystal Mason, 90works Mackenzie Harkins Mary K. Collins, Carrollton Housing Authority Matthew Elder, HomeFirst Gwinnett Initiative Melanie Kagan, United Way of Greater Atlanta Michael Fisher, Ninth District Opportunity, Inc. Naomi Ladson, Macon Coalition to End Homelessness Pamela Gabel, American Red Cross Sharon D Edwards, Community Outreach Training Center INC Sondra Hampton, Southwest Georgia Community Action Council, Inc. Tiffany Stewart-Stanley, Douglas County Government Tracey Johnson, Community Service Board of Middle GA Ogeechee Division Vanessa Flucas, City of Valdosta
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Table of Contents

Introduction

4

HUD Housing Status Definitions

Methodology

5

Unsheltered Homelessness

Sheltered Homelessness

Georgia Housing Status Survey

Analysis

9

Unsheltered Homelessness

Sheltered Homelessness

Results

10

Unsheltered Homelessness

Sheltered Homelessness

Gender

Race and Ethnicity

Household Type

Subpopulations

Youth

Discussion

15

Limitations

Conclusion

17

Coordinated Entry

Racial Equity Improvement Framework

Youth Count

References/Contact Us

19

List of Charts and Tables

20

Appendicies

21

Appendix A. 2019 Sheltered Homeless Survey-

Sample Sheet

Appendix B. Georgia Balance of State Point-In-Time

County-Level Data

Appendix C. 2019 PIT Count - Georgia Map

Biannual Report: 2019 3

2019 Georgia Balance of State Continuum of Care Point in Time Homeless Count Report

Introduction

Every other year, the U.S. Department of Housing and Urban Development (HUD) requires communities nationwide to enumerate their homeless populations for the purpose of assessing need and measuring progress. As mandated by the McKinney Vento Act, all homeless service providers conduct a regular homeless census, which must be conducted during the last ten days of January in odd years (HUD, 2001). This is called a Point-in-Time (PIT) count. The PIT count provides the homeless assistance community with data needed to identify the number and understand the characteristics of persons who are experiencing homelessness at one pointin-time. A PIT count consists of counting persons identified as literally homeless by HUD's definition, both unsheltered and sheltered persons experiencing homelessness, on a single night in January. While there are various definitions used to describe housing environments, HUD's housing definitions required for the PIT count are used throughout this report, refer to Table 1.

In addition to the unsheltered PIT count occurring in odd years, a census of persons and families experiencing homelessness in shelters is completed during the last ten days in January annually, in conjunction with a Housing Inventory Count (HIC). The HIC is a point-in-time catalogue of provider programs within communities that provide beds dedicated to serve persons experiencing homelessness. The goal of each HIC is to account for all emergency shelter housing, transitional housing, and permanent housing bed types within the Continuum of Care (CoC) jurisdictions, regardless if the project is funded by state or federal government entities. Each January, the bed type (emergency, transitional, or permanent), bed capacity (total beds), and bed utilization (percentage of total beds occupied during the count) is collected from all service providers. This collection of data informs the homeless assistance community with the community's capacity to provide shelter for persons experiencing homelessness. This collection of data is referred to as the housing inventory count or shelter count.

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Table 1. HUD Housing Status Definitions

Literally Homeless

Sheltered Homeless Persons: Persons residing in an emergency shelter or in transitional/supportive housing for homeless persons designated to provide temporary living arrangements.

Unsheltered Homeless Persons: People with a primary nighttime residence that is a public or private place not designed for or ordinarily used as regular sleeping accommodations for human beings, including a car, park, abandoned building, bus or train station, airport, or camping ground.

Imminently Homeless Persons facing loss of housing within two weeks, have no subsequent residence identified, and lack the resources or
support networks needed to obtain other permanent housing.

Stably Housed

People who are in a stable housing situation and are not facing imminent loss of housing.

Other

People who are in jail, a hospital, or a detox program, for example.

Methodology
In Georgia, the nine local CoC organizations typically rely on a physical street count or canvassing methodology and service-based method to collect data to produce the PIT total number of unsheltered homelessness; and, utilize the Homeless Management Information System (HMIS) data and provider-level survey data to produce the PIT total number of sheltered homelessness and HIC. In 2019, the Georgia Balance of State (BoS) CoC count was conducted on Monday, January 28 which incorporated methodological changes piloted in the 2018 PIT Count, and a review of the predictive model provided by SimTech Solutions.
Biannual Report: 2019 5

Unsheltered Homelessness. The BoS CoC consists of 152 predominantly rural counties in Georgia, covering approximately 96 percent of Georgia's geography; because of that, the BoS methodological approach to collect PIT data is different than other Georgia CoC organizations. Rural homelessness is often referred to as "hidden homeless" in which many experiencing homelessness in rural areas live in places that are not seen; homeless individuals and families often are sleeping in the woods, campgrounds, cars, abandoned farm buildings, or other places not intended for habitation (HUD, 2010). Since homelessness in rural areas appears different than homelessness in urban areas, simply street canvassing unsheltered homeless will likely undercount the homeless population (HUD, 2010) and will likely contribute to underrepresentation of persons experiencing homelessness in rural areas and within the BoS population. With the level of difficulty of physically canvasing

100 percent of the BoS jurisdiction and with the purpose to capture the most accurate information on all 152 counties, the BoS CoC utilize a statistical street canvassing methodology to produce the total number of unsheltered homelessness. Therefore, rather than attempting to canvass as many counties as possible, the CoC focused PIT count efforts on fewer counties more extensively to ensure the highest level of completeness and accuracy, and used data collected to create a predictive model to estimate unsheltered homelessness.
The BoS solicited and trained individuals to serve as Homeless Count Coordinators and equipped coordinators with resources needed to assembly local volunteers to conduct the local street count and complete unsheltered homeless surveys during the local street count. Training for Count Coordinators consisted of thorough local count planning, street outreach techniques, and correct use of technology.

TABLE 2. COUNTIES AND CLUSTERS CANVASSED IN THE 2019 PIT COUNT

COUNTY CLUSTER COUNTY CLUSTER

Atkinson 12

Coweta

9

Baker

4

Dougherty 6

Bartow

9

Douglas

2

Bibb

6

Early

7

Burke

7

Echols

12

Camden 9

Floyd

9

Carroll

9

Glynn

9

Cherokee 8

Greene

4

Clayton 10 Colquitt 5

Gwinnett

1

Habersham 3

COUNTY CLUSTER

Hall

2

Harris

3

Henry

2

Houston 2

Jones

2

Laurens

11

Liberty

2

Lowndes 2

Madison 5

Paulding 3

COUNTY CLUSTER

Polk

5

Rockdale 2

Stephens 5

Thomas 11

Towns

3

Troup

9

Union

3

White

3

Whitfield 5

Worth

4

6 Biannual Report: 2019

In 2019, the BoS utilized a sophisticated software, Counting Us App from SimTech Solutions, to electronically capture a count of all individuals encountered during the night of the count and collect additional pertinent information using a survey including but not limited to: Location encountered, Personal Identifying Information, PII (Initials and Date of Birth), Household Type (Individual, Family, ChildOnly), Demographic Information (Race, Gender, and Age), and Subpopulation Status (Veteran Status, Youth Status, Domestic Violence Survivor, Mental Illness, and Substance Use). The use of paper surveys that correlate to the app were authorized in circumstances where use of the app was not feasible. The survey allowed for respondents to remain anonymous; however, at the end of the survey if someone wanted to receive assistance to find housing, consents were collected to record contact information used to refer veterans and chronically homeless individuals and families to appropriate service providers for assistance. On January 28, 2019 local count volunteers canvassed approximately 40 counties which included counties within each of the 12 cluster boundaries that comprise all 152 counties in the BoS CoC. Table 2, represents each county canvassed in the 2019 PIT count and the corresponding cluster. Surveys were collected by local count volunteers using the

Counting Us app on the night of the count.
In addition to the street count method, the BoS also utilized the service-based method in which local count volunteers collected surveys for the following seven days at locations where individuals and families experiencing homelessness were seeking services, such as a day centers, food banks, public libraries, and other service providers. Though surveys were collected during the week-long period, questions were focused on a single point-in-time (HUD, 2004). For the 2019 PIT count, surveys were collected from January 28th through February 4th and respondents were asked, "where were you sleeping on the night of "January 28th". The same survey was used during both street canvassing and service-based counting.
The information collected during canvassing or sample data was used to build a regression model that predicts the rate of homelessness in the counties where no count was completed. This predictive model was used to provide the most precise probability of the unsheltered homeless population across the CoC. In 2019, the sample data was also used to build estimations of the unsheltered veteran and unsheltered chronically homeless subpopulations by county.

S hel tere d Homelessness. The BoS distributed an electronic provider-level survey to all federally funded service providers, non-funded HMIS service participants, and as many known and unknown service providers within the BoS jurisdictions that are not funded and are not HMIS service participants. The distribution method is used to comprise a comprehensive sheltered homeless count. Survey questions included some of the same street count questions such as Household Type, Demographic Information, and Subpopulation Status. Refer to Appendix

A for sample survey questions used. For the 2019 PIT count, electronic surveys were collected from January 28th through February 4th however providers were asked, "how many total people were staying in this project on the night of January 28, 2019". Unlike the street count survey, additional questions were asked to collect HIC data such as, "how many total beds does this project have?" and "how many beds in this project are dedicated to serve youth, veterans, or people experiencing chronic homelessness?"

Biannual Report: 2019 7

Georg ia H ousin g Sta tus Survey. During the 2019 PIT Count in the BoS, 1,525 useable surveys and observations were collected. The majority of these surveys (57%) completed were for respondents who were considered to be unsheltered homeless. This is a notable improvement over the 2017 PIT Count, in which 48% of surveys collected were for respondents who were considered stably housed. The BoS believes that this improvement is due to improvements in the count methodology and utilization of the app-based platform for unsheltered surveys. While the information garnered from this survey can be useful for planning purposes, please note that the sample that was surveyed was, in many cases, not a complete nor representative sample because not every person in these populations (imminently homeless, unsheltered homeless, stably housed) was surveyed and no method of randomization was utilized.

TABLE 3: RESPONDENT HOUSING STATUS

UNSHELTERED HOMELESS

866

STABLY HOUSED

339

SHELTERED HOMELESS

195

MISSING

89

OTHER

23

IMMINENTLY HOMELESS

13

Table 3 shows frequencies for each housing status type. Table 4 further breaks down these housing status categories to show the frequencies for the locations of respondents in the night of the count.

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TABLE 4: RESPONDENT LOCATION ON JANUARY 28, 2019

ABANDONED BUILDING

197

BUS OR TRAIN STATION, AIRPORT

6

TREATMENT PROGRAM

10

EMERGENCY SHELTER OR DOMESTIC VIOLENCE SHELTER

123

GROUP HOME

2

HOTEL OR MOTEL PAID FOR BY AGENCY

27

HOTEL OR MOTEL PAID FOR WITH YOUR OWN FUNDS

13

IN A CAR, TRUCK, OR VAN

113

IN THE WOODS OR CAMPSITE

167

IN A PUBLIC PARK

38

JAIL OR PRISON

6

MEDICAL OR PSYCHIATRIC HOSPITAL

3

MISSING/NO RESPONSE

0

MY OWN HOUSE OR APARTMENT

162

ON THE STREET OR SIDEWALK

127

UNDER A BRIDGE OR OVERPASS

40

OTHER

6

PERMANENT SUPPORTIVE HOUSING

0

TRANSITIONAL HOUSING

43

WITH FRIENDS OR FAMILY

175

Analysis
Unsheltered Homeless. During the night of the count, the BoS included all individuals identified as literally homeless in the unsheltered homeless population; however, following data collection, data was reviewed within the SimTech Solutions' database to remove ineligible individuals from the final count. Person duplications were removed using Personal Identification Information (PII) and the screening survey response to, "Have you already completed a count survey," individuals were removed that did not fit the HUD definition of literally homeless based on survey responses to location and sleeping accommodations, and individuals were removed that were encountered outside the BoS jurisdictions. Eligible data was used to build the predictive model and generate estimations on the unsheltered homelessness population and subpopulations provided by SimTech Solutions statisticians. Population estimations provided was then used for CoC analysis purposes.
Sheltered Homeless. Following data collection, all data received was compiled together based on housing type (emergency shelter or transitional housing). Then, data was reviewed and compared to the HMIS system, if applicable, to verify data. Verified data was then used for analysis purposes.

Biannual Report: 2019 9

Results
4,183 people were calculated and reported literally homeless on a single night, January 28, 2019, in the BoS CoC a 13 percent total homeless increase from 2017. Appendix B includes county level point-in-time counts. Of the 4,183 people, 2,262 individuals were calculated and reported as unsheltered homeless and 1,921 individuals were reported as sheltered homeless. Table 5, below, depicts literal homeless population on a single night over the past four point-in-time counts.

TABLE 5: BALANCE OF STATE COC LITERALLY HOMELESS POPULATION: SINGLE NIGHT (POINT IN TIME COUNT)

HOUSING STATUS UNSHELTERED SHELTERED TOTAL CHANGE FROM PREVIOUS COUNT (%)

Number of Individuals per Year

2013 5,317 2,334 7,651 -32

2015 3,518 2,279 5,797 -24

2017 1,843 1,873 3,716 -36

2019 2,262 1,921 4,183 +13

Chart 1, below, is a visual representation of the trend of total homelessness within the BoS PIT counts. This chart demonstrates a negative trend line in homelessness over the years as well as visually demonstrates a 13 percent increase in homelessness in 2019 when compared to 2017.

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Unsheltered Homeless. Chart 2 highlights the trend of unsheltered homelessness within the BoS PIT counts. From 2013 to 2015, there was a 34 percent decrease in the number of unsheltered homeless. This downward trend has continued, and for the 2017 count the BoS experienced a decrease in the number of unsheltered homeless (47 percent). Though 2019 demonstrated an increase (20 percent) in the trend of homelessness, Chart 2 demonstrates a negative trend in unsheltered homelessness as the overall estimated trajectory.
Sheltered Homeless. Sheltered homelessness in the BoS has remained fairly constant over the past seven years; however, there have been some small fluctuations this year. The BoS experienced an 11 percent increase in the number of people staying in emergency shelters on the night of the count and a 33 percent decrease in the number of people staying in transitional housing. This decline in transitional housing stay is largely due to a total of 410 beds closing over the course of the year. Overall, the BoS has experienced a 19 percent decrease in the number of people staying in emergency shelters or transitional housing during the PIT counts from 2017 to 2019 (1,857 and 1,921 respectively).
Biannual Report: 2019 11

Gender. Approximately 57 percent of the total homeless population in the BoS identify as male; however, that percentage differs when broken down by homeless status. Chart 4 demonstrates a higher percentage of men experiencing unsheltered homelessness than sheltered homelessness. The PIT count was inclusive of persons identified as transgender and non-conforming gender; however, this population presented less than 1 percent of the population (N=5 and N=4 respectively).
Race and Ethnicity. Chart 5 illustrates the proportion of race within the BoS homeless population. Black or African American individuals make up the greatest percentage of the racial distribution within the BoS homeless population (50 percent, N=2,080). Six percent (N=257) identify as Hispanic or Latino.
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Household Type. The three household types are Families (households with at least one adult and one child), Individuals (households without children), and Child Only (households with only children). Chart 6 demonstrates a larger proportion of families are sheltered (92 percent) than unsheltered, and a larger proportion of individuals are unsheltered (73 percent) than sheltered. Child Only households represent less than 1 percent of the PIT homeless population and thus, was not included chart 6.
Biannual Report: 2019 13

Sub populations. In addition to analyzing the PIT population data (N=4183), the PIT count reviewed the number of other subpopulation data such as veteran status and chronically homeless status. Chart 7 illustrates the subpopulation data collected indicating six percent of the estimated homeless population identify as veterans and seven percent identify as chronically homeless. Chronically homeless is defined by the presence of a disability and length of homelessness of at least one year or experienced homelessness four times in the past three years. Of the subpopulations, domestic violence victims, mental illness, and substance abuse disorder were among the greatest represented.
Youth. The homeless youth population is viewed in two ways: unaccompanied youth (youth under the age of 24) and parenting youth (youth under the age of 24 with child under the age of 18) and is another subset of the total homeless population (N=4183). Chart 8 demonstrates total youth population of 372 person representing 8 percent of the total homeless population. Also representing the BoS's fourth largest subpopulation.
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Discussion

Note the data collected and results do not represent an absolute depiction of homelessness within the BoS CoC; nevertheless, presents a framework used to assess homeless needs and measure progress annually within controlled parameters of a single point in time. Of all eligible surveys and observations collected on January 28 and the seven subsequent days, the greatest proportion of persons experiencing homelessness are unsheltered (54 percent); and, of the unsheltered population, individuals over the age of 24 years represent the majority (72 percent). Males represent the majority gender (57 percent) and Black or African Americans represent the majority race (50 percent) of the total BoS homeless population.
The methodology to capture the unsheltered population is worthy to discuss and review the potential impacts. The Georgia BoS adjusted its methodology for enumerating unsheltered homelessness this year, as stated above in the methodology section. As in previous years, the final number derived from both physical counts, and the use of a predictive model to determine homelessness in areas that were not physically counted. This year, the CoC focused on physical counts in areas with higher capacity to accurately conduct a count. The CoC also partnered with Simtech Solutions to update its predictive model, which was previously developed by Kennesaw State University. Additionally, the CoC used the app/webbased product to conduct surveys for the first time this year, resulting in higher quality data. These changes provided the CoC with more useable data from physical counts, and what the CoC believes to be a more accurate predictive model. The CoC believes that these changes contributed significantly to the higher unsheltered number, which is reflective of overall national trends. While the unsheltered number has increased from 2017, total homelessness demonstrates an

overall unsheltered decrease of 74 percent since 2011.
According to the 2017 Annual Homeless Assessment Report to Congress, most minority groups make up a larger share of the homeless population than they do of the general population; thus, displaying a disproportionate share of the homeless population. African Americans represent 13 percent of the general national population; however, account for 40 percent of people experiencing homelessness and more than 50 percent of homeless families with children (AHAR, 2018). Correspondingly the state of Georgia demonstrates the same national, racial disparity in which African Americans make up 31 percent of the state's general population and account for 68 percent of those experiencing homelessness and 75 percent of homeless families with children. The BoS likely demonstrates the same trend in which 50 percent of those experiencing homelessness during the single point in time are Black or African American and 56 percent of homeless families with children.
Though the total youth population of 8 percent may seem relatively low, youth are among the most vulnerable population and represent the next generation of our homelessness system. Additionally, unaccompanied unsheltered youth increased from 105 persons in 2017 to 158 persons in 2018. This dataset is based on the extrapolation from sample counties embedded within the predictive model. This year, the sample included more unaccompanied youth than in 2017. The methodology assumes that this is reflected in the overall homeless population. Additionally, one organization performing a physical count focuses on youth as its service population. These factors likely led to identification of more homeless youth in sample counties, which were then

Biannual Report: 2019 15

extrapolated across the entire CoC. Researchers have acknowledged the difficulty in accurately counting the hidden, transient nature of homeless youth and have further stated methods commonly used for counting sheltered adult homeless persons do not accurately capture youth in which youth commonly are mobile and transient, couch hopping, and are hiding (Raleigh-DuRoff,

2004). Even with the difficult nature of an accurate count, the National Alliance to End Homeless (2019) estimates in 2018 51 percent of homeless youth are unsheltered and over the course of a year, approximately 550,000 unaccompanied youth and young adults up to the age 24 experience homeless episodes of longer than one week. More than half are under the age of 18.

Limitations

There are certainly limitations to be conscious of when utilizing this dataset. Specifically, for unsheltered homeless data collection, data was collected by agencies with varying levels of experience executing PIT counts and varying levels of community coverage. Although all agencies received the same PIT count training from DCA staff, each agency was responsible for organizing the count in the best way for their respective community. No two PIT counts looked identical, leading to possible inconsistencies in the administration of surveys, the target locations for data collection, and populations surveyed; hence the above likely factors of an increased number of youths.
Another limitation is the dataset does not represent an absolute depiction of homelessness in which 100 percent coverage for all 152 counties of the BoS was not completed and a statistical calculation was used to comprise the estimated total of unsheltered homelessness. Estimation techniques based on count data collected in a sample of counties are used. Beginning in 2008, the CoC has used sampling methodology and predictive models. In 2019, the data used for the model came from survey counts conducted in approximately 40 counties. A limitation to note here is that these sample counties were a convenience sample. The counties had a service provider able to participate in the coordination of the PIT count in their area; this may or may not lead to an accurate representation of the unsheltered

homeless population in other counties that do not have such service providers. Additionally, during the night of the count surveys were collected in places where persons experiencing homelessness were known to congregate and stay; and during the subsequent seven days, surveys were collected at locations where people receive services. However, as mentioned previously in the methodology section, only a small percentage of the surveys collected were representative of the total unsheltered homeless population, and not all counties covered were able to obtain a complete census of their total unsheltered homeless population, which has the potential to exclude individuals experiencing homelessness within the final calculated estimation of total homelessness.
Another factor that contributes significantly to the prediction model itself is how confident a count coordinator is that he or she was able to survey 100 percent of the unsheltered homeless population in the county or coverage area. After the conclusion of the PIT count survey week, count coordinators submitted a debriefing survey regarding the respective counts and how counts were conducted. Within the debriefing survey, each count coordinator submitted a confidence score based on if he or she covered the entire county thoroughly; the data was then used to build the prediction model and consequently insufficient confidence risk exclusion from the predictive model.

16 Biannual Report: 2019

The coordinators completed this survey before knowing the results of their count, which prevents a certain degree of bias; however, there is a possibility that although the count coordinator was confident, he or she still may not have covered the county well enough and missed part of the sample population. Logically, the predictive model structure excluded data based on if a count coordinator could state a substantial belief that the entire unsheltered homeless population for that county was surveyed, which prevents the likeliness of extrapolating inac-

curate data. Also, there likely are count coordinators who stated substantial confidence that all unsheltered homeless was surveyed; however, after data was compiled together, there were no unsheltered homeless individuals or families presented in that county. Traditionally, DCA has not included zeros in the prediction model because it is far better to overestimate homelessness than to underestimate. However, this year, the BoS included reported data within the prediction model based on the level of confidence.

Conclusion

In conclusion to another successful and exhaustive review of the 2019 PIT count and in collaboration with the annual HIC, the BoS has recognized areas of assessment and implementation toward system improvements. As a result of the PIT analysis, here are a few preliminary homelessness targets the BoS would like to further investigate:
Coordinated Entry. Through the continued expansion of Coordinated Entry, the BoS has been afforded the opportunity to reach more of the homeless population than in previous years. Through the evaluation of this reach, the BoS would also have the opportunity to further investigate priority toward sheltered families and resources targeted for unsheltered individuals over age 24. Coordinated Entry is continuously expanding reach to all individuals experiencing unsheltered homelessness and would warrant inclusion of all individuals.

Racial Equity Improvement Framework. With the guidance of HUD, the BoS has completed the preliminary analysis racial disparity. As a result of the preliminary analysis completed the BoS has recognized the overestimation of certain racial populations currently experiencing homelessness; thus, the BoS has commenced the development of a detailed framework to analyze and act upon racial disparities in the current homeless system. This plan will continue to be implemented over the next year and will be a continued topic of interest as. It is essential to understand efforts to end homelessness must address the range of issues that have resulted from racial inequity; thus, an effective plan is necessary to resolve the disproportionate share of the homeless population.

Biannual Report: 2019 17

Youth Count. The CoC has made homeless youth a focus over the past two years and will continue efforts to implement best practices of counting this "hidden" population and discover best practices to effectively serve this population. The BoS has created effective collaboration with other state agencies such as Child Welfare, Workforce, Juvenile Justice, Early Childcare and Learning and TANF to organize mainstream benefits in a way that supports systemic change for youth experiencing homelessness in rural Georgia. The CoC is collaborating with youth who have lived experience to organize data collection efforts to identify gaps and risk factors to provide an accurate count of homeless youth population. The BoS has also developed a Youth Advisory Board and work-

group used to build operative programs tailored specifically to youth around youth rapid re-housing bed capacity and utilization. The BoS will continue efforts to serve this population as well as build diversion and prevention into the coordinated entry system.
In addition to investigating these above targets, it is always of interest of the CoC to strive for continued improvements within the homeless system and contribute a direct impact on making homelessness rare, brief, and one-time. The CoC will continue focusing on veteran homeless and families to sustain successful declination of the total homeless population and other subpopulations as well as provide resources needed to serve these populations.

18 Biannual Report: 2019

References
National Alliance to End Homelessness, NAEH. (2019).Youth and Young Adults. Retrieved from https://endhomelessness.org/homelessness-in-america/who-experienceshomelessness/youth/
Raleigh-DuRoff, C. (2004). Factors that Influence Adolescents to Leave or Stay Living on the Street. Child and Adolescent Social Work Journal 21(6): 56172.
U.S. Census Bureau. (2015). American Community Survey (ACS). Retrieved from https:// www.census.gov/programs-surveys/acs/
U.S. Department of Housing and Urban Development, HUD. (2001). Office of Community Planning and Development. Report to Congress: HUD's Strategy for Homeless Data Collection, Analysis and Reporting. Retrieved from https://archives.hud.gov/offices/cpd/ homeless/hmis/strategy/congressreport.pdf
U.S. Department of Housing and Urban Development, HUD. (2004) Office of Community Planning and Development. A Guide to Counting Unsheltered Homeless People. Retrieved from https://www.hudexchange.info/onecpd/assets/File/Guide-for-CountingUnsheltered-Homeless-Persons.pdf
U.S. Department of Housing and Urban Development, HUD. (2010) Office of Community Planning and Development. A Guide to Counting Unsheltered Homeless People. Retrieved from https://www.hudexchange.info/onecpd/assets/File/Guide-for-CountingUnsheltered-Homeless-Persons.pdf
U.S. Department of Housing and Urban Development. (2017). The 2016 Annual Homeless Assessment Report to Congress: Part 2--Estimates of Homelessness in the United States. Retrieved from https://files.hudexchange.info/resources/documents/2016-AHARPart-2.pdf
U.S. Department of Housing and Urban Development. (2018). The 2018 Annual Homeless Assessment Report to Congress: Part 1--Point In Time Estimates of Homelessness. Retrieved from https://files.hudexchange.info/resources/documents/2018-AHAR-Part-1. pdf
Contact Us
PITcount@dca.ga.gov
Biannual Report: 2019 19

List of Charts and Tables
CHART 1. BALANCE OF STATE COC PIT COUNT TREND: 2011 THROUGH 2019 CHART 2. BALANCE OF STATE COC UNSHELTERED HOMELESS PIT TREND: 2011
THROUGH 2019 CHART 3. BALANCE OF STATE COC SHELTERED HOMELESS PIT TREND: 2011
THROUGH 2019 CHART 4. BALANCE OF STATE COC PIT HOMELESS STATUS BY GENDER CHART 5. BALANCE OF STATE COC PIT HOMELESS STATUS BY RACE CHART 6. BALANCE OF STATE COC PIT HOMELESS STATUS BY HOUSEHOLD TYPE CHART 7. BALANCE OF STATE COC PIT HOMELESS STATUS BY SUBPOPULATIONS CHART 8. BALANCE OF STATE COC PIT HOMELESS STATUS BY YOUTH POPULATION TABLE 1. HUD HOUSING STATUS DEFINITIONS TABLE 2. COUNTIES AND CLUSTERS CANVASSED IN THE 2019 PIT COUNT TABLE 3. RESPONDENT HOUSING STATUS TABLE 4. RESPONDENT LOCATION ON JANUARY 28, 2019 TABLE 5. BALANCE OF STATE COC LITERALLY HOMELESS POPULATION:
SINGLE NIGHT (POINT IN TIME COUNT)

20 Biannual Report: 2019

Annual Report: 2018 20

Appendicies
Appendix A. 2019 Sheltered Homeless Survey- Sample Sheet
Biannual Report: 2019 21

Appendix B. Georgia Balance of State Point-In-Time County-Level Data

County

UHP

UV

UC SHP

Appling

0

0

Atkinson

0

0

Bacon

0

0

Baker

0

0

Baldwin

17

1

Banks

0

0

Barrow

14

1

Bartow

62

7

Ben Hill

4

0

Berrien

1

0

Bibb

194 15

Bleckley

0

0

Brantley

0

0

Brooks

0

0

Bryan

4

0

Bulloch

7

0

Burke

0

0

Butts

5

0

Calhoun

0

0

Camden

0

0

Candler

0

0

Carroll

42

0

Catoosa

29

2

Charlton

0

0

Chattahoochee 0

0

Chattooga

6

0

Cherokee

20

8

Clay

0

0

0

0

0

0

0

0

0

0

2

0

0

0

1

43

10 42

00

00

16 0

00

00

00

00

0 13

00

00

00

05

00

9 49

30

00

00

00

0 183

00

Total Homeless 0 0 0 0 17 0
57 104 4 1 194 0 0 0 4 20 0 5 0 5 0 91 29 0 0 6 203 0

Total Beds Available 0 0 0 0 0 0
55 54 0 0 0 0 0 0 0 21 0 0 0 18 0 60 0 0 0 0 193 0

PIT Utilization 0% 0% 0% 0% 0% 0%
79% 56% 0% 0% 0% 0% 0% 0% 0% 62% 0% 0% 0% 28% 0% 78% 0% 0% 0% 0% 65% 0%

KEY UHP: Unsheltered Homeless Persons (Counts and Predictive Model) UV: Unsheltered Veterans (Count & Extrapolations) UC: Unsheltered Chronic (Count & Extrapolations) SHP: Sheltered Homeless Persons (Emergency & Transitional Housing) Total Homeless: Total Homeless Persons (Unsheltered & Sheltered Persons) Total Beds Available: Total Emergency & Transitional Beds Available PIT Utilization: Percent of Available Beds
22 Biannual Report: 2019

Appendix B. Georgia Balance of State Point-In-Time County-Level Data

County
Clayton Clinch Coffee Colquitt Columbia Cook Coweta Crawford Crisp Dade Dawson Decatur Dodge Dooly Dougherty Douglas Early Echols Effingham Elbert Emanuel Evans Fannin Fayette Floyd Forsyth Franklin Gilmer

UHP

UV

UC SHP

10

1

0

0

18

1

32

4

30

12

1

0

33

2

0

0

1

0

5

0

4

0

5

0

4

0

0

0

94

7

44

3

4

0

0

0

25

0

1

0

1

0

0

0

3

0

16

6

156 0

7

3

9

1

15

1

1

80

0

0

2

0

12

26

0

0

0

0

2

0

00

00

00

00

1

0

00

00

8 50

3 120

00

00

00

00

00

00

0 16

0 23

5 56

0 16

1

0

1

0

Total Homeless 90 0 18 58 30 1 33
0 1 5 4 5 4 0 144 164 4 0 25 1 1 0 19 39 212 23 9 15

Total Beds Available 163 0 0 34 0 0 0
0 0 0 0 0 0 0 88 137 0 0 0 0 0 0 16 23 69 33 0 0

PIT Utilization 64% 0% 0% 78% 0% 0% 0%
0% 0% 0% 0% 0% 0% 0% 64% 89% 0% 0% 0% 0% 0% 0% 100% 100% 0% 42% 0% 0%

KEY UHP: Unsheltered Homeless Persons (Counts and Predictive Model) UV: Unsheltered Veterans (Count & Extrapolations) UC: Unsheltered Chronic (Count & Extrapolations) SHP: Sheltered Homeless Persons (Emergency & Transitional Housing) Total Homeless: Total Homeless Persons (Unsheltered & Sheltered Persons) Total Beds Available: Total Emergency & Transitional Beds Available PIT Utilization: Percent of Available Beds
Biannual Report: 2019 23

Appendix B. Georgia Balance of State Point-In-Time County-Level Data

County
Glascock Glynn Gordon Grady Greene Gwinnett Habersham Hall Hancock Haralson Harris Hart Heard Henry Houston Irwin Jackson Jasper Jeff Jefferson Jenkins Johnson Jones Lamar Lanier Laurens Lee Liberty

UHP

UV

UC SHP

0

0

00

283

36

26

41

25

2

2

6

7

1

1

0

8

0

0

3

118

11

3

164

72

0

1

46

57

5

5 92

1

0

00

12

1

1

0

15

0

00

0

0

07

0

0

00

0

0

0 39

69

3

4 22

0

0

00

27

2

2

0

0

0

00

2

0

00

4

0

00

0

0

00

0

0

00

14

0

00

5

0

00

0

0

00

19

1

2

17

4

0

00

3

0

2

21

Total Homeless
0
324 31 7 11 282 118
149 1 12 15 7 0 39 91 0 27 0 2 4 0 0 14 5 0 36 4 24

Total Beds Available
0
67 8 0 12 164 47
137 0 0 0 12 0 48 42 0 0 0 0 0 0 0 0 0 0 33 0 38

PIT Utilization
0%
55% 75% 0% 25% 100% 98%
70% 0% 0% 0% 58% 0% 81% 56% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 51% 0% 64%

KEY UHP: Unsheltered Homeless Persons (Counts and Predictive Model) UV: Unsheltered Veterans (Count & Extrapolations) UC: Unsheltered Chronic (Count & Extrapolations) SHP: Sheltered Homeless Persons (Emergency & Transitional Housing) Total Homeless: Total Homeless Persons (Unsheltered & Sheltered Persons) Total Beds Available: Total Emergency & Transitional Beds Available PIT Utilization: Percent of Available Beds
24 Biannual Report: 2019

Appendix B. Georgia Balance of State Point-In-Time County-Level Data

County
Lincoln Long Lowndes Lumpkin Macon Madison Marion McDuffie McIntosh Meriwether Miller Mitchell Monroe Montgomery Morgan Murray Newton Oconee Oglethorpe Paulding Peach Pickens Pierce Pike Polk Pulaski Putnam Quitman

UHP

UV

0

0

0

0

68

33

9

0

0

0

7

1

0

0

4

0

0

0

2

0

0

0

4

0

8

0

0

0

7

1

7

1

29

2

18

7

0

0

12

0

9

0

9

1

0

0

0

0

8

1

0

0

5

0

0

0

UC SHP

00

0

0

5

76

0

12

0

167

1

0

0

0

00

00

00

00

00

00

00

1

0

40

3 55

00

00

0 10

00

1

0

00

00

46

00

00

00

Total Homeless
0
0 144 21 167 7 0
4 0 2 0 4 8 0 7 7 84 18 0 22 9 9 0 0 14 0 5 0

Total Beds Available
0
0 83 12 172 0 0
0 0 0 0 0 0 0 0 0 65 0 0 25 0 0 0 0 14 0 0 0

PIT Utilization
0%
0% 92% 100% 69% 0% 0%
0% 0% 0% 0% 0% 0% 0% 0% 0% 85% 0% 0% 37% 0% 0% 0% 0% 43% 0% 0% 0%

KEY UHP: Unsheltered Homeless Persons (Counts and Predictive Model) UV: Unsheltered Veterans (Count & Extrapolations) UC: Unsheltered Chronic (Count & Extrapolations) SHP: Sheltered Homeless Persons (Emergency & Transitional Housing) Total Homeless: Total Homeless Persons (Unsheltered & Sheltered Persons) Total Beds Available: Total Emergency & Transitional Beds Available PIT Utilization: Percent of Available Beds
Biannual Report: 2019 25

Appendix B. Georgia Balance of State Point-In-Time County-Level Data

County
Rabun Randolph Rockdale Schley Screven Seminole Spalding Stephens Stewart Sumter Talbot Taliaferro Tattnall Taylor Telfair Terrell Thomas Tift Toombs Towns Treutlen Troup Turner Twiggs Union Upson Walker Walton

UHP

UV

UC SHP

2

0

0 14

0

0

0

0

20

1

1

52

0

0

0

0

1

0

0

0

0

0

0

0

16

1

2

14

10

0

09

0

0

00

12

0

1

0

0

0

00

0

0

00

10

1

1

0

0

0

00

1

0

1

0

0

0

00

64

3

7

16

0

0

0 37

9

0

0 14

11

0

00

0

0

00

69

5

6 109

0

0

00

0

0

00

7

0

0 16

15

1

2

0

29

2

3 20

18

1

2

0

Total Homeless
16
0 72 0 1 0 30
19 0 12 0 0 10 0 1 0 80 37 23 11 0 178 0 0 23 15 49 18

Total Beds Available
14
0 65 0 0 0 32
9 0 0 0 0 0 0 0 0 23 63 29 0 0 127 0 0 16 0 24 0

PIT Utilization
100%
0% 72% 0% 0% 0% 44%
100% 0% 0% 0% 0% 0% 0% 0% 0% 65% 68% 48% 0% 0% 77% 0% 0% 100% 0% 83% 0%

KEY UHP: Unsheltered Homeless Persons (Counts and Predictive Model) UV: Unsheltered Veterans (Count & Extrapolations) UC: Unsheltered Chronic (Count & Extrapolations) SHP: Sheltered Homeless Persons (Emergency & Transitional Housing) Total Homeless: Total Homeless Persons (Unsheltered & Sheltered Persons) Total Beds Available: Total Emergency & Transitional Beds Available PIT Utilization: Percent of Available Beds
26 Biannual Report: 2019

Appendix B. Georgia Balance of State Point-In-Time County-Level Data

County
Ware Warren Washington Wayne Webster Wheeler White Whitfield Wilcox Wilkes Wilkinson Worth
TOTAL

UHP

UV

UC SHP

15
0 6 10 0 0 35
22 0 0 0 6
2262

1
0 0 1 0 0 0
2 0 0 0 1
207

2
0 0 1 0 0 0
11 0 0 0 1
189

13
0 0 4 0 0 0
97 0 0 0 0
1921

Total Homeless
28
0 6 14 0 0 35
119 0 0 0 6
4183

Total Beds Available
14
0 0 12 0 0 0
136 0 0 0 0
2507

PIT Utilization
93%
0% 0% 33% 0% 0% 0%
80% 0% 0% 0% 0%
70%

KEY UHP: Unsheltered Homeless Persons (Counts and Predictive Model) UV: Unsheltered Veterans (Count & Extrapolations) UC: Unsheltered Chronic (Count & Extrapolations) SHP: Sheltered Homeless Persons (Emergency & Transitional Housing) Total Homeless: Total Homeless Persons (Unsheltered & Sheltered Persons) Total Beds Available: Total Emergency & Transitional Beds Available PIT Utilization: Percent of Available Beds

Biannual Report: 2019 27

Appendix C. 2019 PIT Count - Georgia Map 28 Biannual Report: 2019