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JUNE 2022
Homeless
Point-in-Time
Count and
Survey
2022
Continuum of Care (CoC) and
Riverside County Department of
Housing and Workforce Solutions
(HWS)
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TABLE OF CONTENTS
EXECUTIVE SUMMARY ....................................................................................................... 3
INTRODUCTION ................................................................................................................. 6 Homeless Point-in-Time Count ................................ ................................ ............................ 6 Riverside County Point-in-Time Count ................................ ................................ ................ 6 I. Sheltered Count ................................ ................................ ................................ .... 7 II. Unsheltered or Street-Based Count ................................ ................................ ....... 7
POINT-IN-TIME COUNT PLANNING .................................................................................... 9 a. Developing an Inclusive PIT Count Plan ................................ ................................ ............... 10 b. More Than a Count Initiative ................................ ................................ ...................... 12 c. Selection of Date and Time ................................ ................................ ......................... 12 d. City Leaders, Deployment Sites, and Orientation ................................ ....................... 12 e. Survey Tools ................................ ................................ ................................ ................ 14 I. Interview Survey................................ ................................ ................................ .. 14 II. Observational Survey ................................ ................................ .......................... 15 f. ESRI Geographical Information System (GIS) ................................ .............................. 16 g. Volunteer Recruitment and Training ................................ ................................ .......... 17 h. Incentives ................................ ................................ ................................ ................... 20 YOUTH POINT-IN-TIME COUNT PLANNING ..................................................................... 21
a. Youth Count Planning and Community Engagement ................................ ................. 21 b. Challenges in Identifying Homeless Youth ................................ ................................ .. 22 c. Youth Count Deployment Sites ................................ ................................ .................. 23 d. Homeless Youth Count Awareness and Promotion ................................ .................... 23 e. Youth Count Volunteer Recruitment ................................ ................................ ......... 23 f. Youth Involvement ................................ ................................ ................................ .... 23 g. Youth Count Incentives ................................ ................................ .............................. 24
METHODOLOGY ................................ ................................ ................................ ........... 25 Unsheltered Count ................................ ................................ ................................ ............ 25 Street-based Count ................................ ................................ ................................ ..... 25 Homeless Youth and Young Adults Count ................................ ................................ .. 27 Service-Based Count ................................ ................................ ................................ ... 29 Unincorporated (non-City) Area Count ................................ ................................ ...... 31 Sheltered Count ................................ ................................ ................................ ................ 32 Homeless Information Management System (HMIS) ................................ ................. 32 Housing Inventory Count (HIC) ................................ ................................ .................. 32
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STRATEGIES AND METHODS ................................ ................................ ......................... 34 Deduplication Process ................................ ................................ ................................ .... 35
RESULTS ................................ ................................ ................................ ...................... 37
Sub-population Reports ................................ ................................ ................................ . 40 Families with Children ................................ ................................ ................................ ....... 40 Youth (18-24) ................................ ................................ ................................ .................... 41 Seniors (60+) ................................ ................................ ................................ ..................... 42 Veterans ................................ ................................ ................................ ........................... 42 First Time Homeless ................................ ................................ ................................ ......... 43 Chronic Homeless ................................ ................................ ................................ ............. 44 Formerly Incarcerated ................................ ................................ ................................ ..... 45 Couch Surfers ................................ ................................ ................................ ................... 45
More Than a Count Outcomes ................................ ................................ ................................ ... 46
CONCLUSION ................................ ................................ ................................ ........... 48
RECOMMENDATIONS ................................ ................................ ................................ 49
LIMITATIONS ................................ ................................ ................................ ............. 52
ACKNOWLEDGMENTS ................................ ................................ ............................... 53
Appendix A: City, Unincorporated Area, Supervisorial District, and Sub-population Summary Tables 63
Appendix B: 2022 PIT Count Survey Instrument Sample 164
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EXECUTIVE SUMMARY
The Department of Housing and Workforce Solutions (HWS), in partnership with the County of Riverside Continuum of Care (CoC), coordinated the 2022 Homeless Point-in-Time Count (PITC). The PITC was planned, coordinated, and implemented by county agencies, city municipalities, non-profit service providers, law enforcement, and volunteers. The unsheltered homeless count included counts in the street, unincorporated areas, and events specific to Transitional Age Youth (TAY). In addition to interviewing unsheltered homeless residents, volunteers also offered linkages to housing and other services through follow up services. The sheltered count consisted of information derived from the countywide Homeless Management Information System (HMIS).
Data collected during the PITC reflects Riverside County’s homeless population at one point-in-time and is required to: continue receiving federal funding for homeless assistance programs, develop strategies to end homelessness, define the specific needs of our communities to improve models of care and wrap around services, and help individuals and families experiencing homelessness who are in need. The 2022 homeless count was of particular importance because it helped determine changes in trends and the impact of COVID-19 on the already vulnerable, at-risk, and homeless population.
The homeless count identified a 15% (+432) increase overall compared to 2020. For the first time in six years, the homeless count revealed a decrease (8%) in the number of persons experiencing unsheltered homelessness. This decrease may be attributed to large investments made to fund homeless street outreach teams which increased referrals to emergency shelters and other housing assistance programs. The unsheltered count also demonstrated changes in sub-populations of interest. Families with children experienced an 50% increase, TAY showed a 7% decrease, Seniors 60+ demonstrated a 14% decrease, and the number of unsheltered veterans declined by 31% compared to the 2020 homeless count. There was an 83% increase in sheltered individuals which can be attributed, in part, to an increase in shelter capacity. Federal response to COVID conditions and increased state funding provided new opportunities for shelter and services between 2020 and 2022. An increase in sheltered count numbers indicates that more individuals are receiving care and are on a path towards permanent housing. Results from the 2022 homeless PITC will support HWS and the CoC’s efforts to develop innovative programs and strategies for resolving homelessness within Riverside County.
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Total Count (3316) of Sub-populations Countywide Compared with 2020 Count o Families with Children – 128 households with 490 persons (adults and children), (4% of total count, 83% increase)
o Youth (18-24) – 312 including youth head of household (9% of total count, 4% decrease) o Seniors (60+) – 323 (10% of total count, 60+ data not collected for 2020 total count) ▪ Seniors (62+) – 243 (7% of total count, 22% increase) o Veterans – 126 (4% of total count, 22% decrease)
o Chronically Homeless – 816 (25% of total count; 26% increase) o Mental Health Issues – 478 (14% of total count, 14% decrease) o Substance Abuse – 476 (14% of total count, 11% decrease)
Unsheltered Count (1980) of Sub-Populations Countywide Compared with 2020 Count o Families with Children - 9 households with 29 persons (adults and children), (50% increase) o Youth (18-24) - 237 unsheltered, 234 unaccompanied and 3 in families (12% of unsheltered count, 7% decrease)
o Seniors (60+) – 150s (8% of unsheltered count, 14% decrease) ▪ Seniors (62+) – 106 (5% of unsheltered count, 12% decrease) o Veterans – 77 unsheltered (4% of unsheltered count, 31% decrease) o Chronically Homeless – 560 (28% of unsheltered count, 8% increase) o Mental Health Issues – 300 (15% of unsheltered count, 20% decrease) o Substance Abuse – 424 (21% of unsheltered count, 6% decrease) o First Time Homeless - 423 (21% unsheltered count, 13% decrease)
Sheltered Count (1336) by Sub-Populations Countywide Compared with 2020 Count o Families with Children – 119 households with 461 persons (adults and children), (9% of sheltered count, 86% increase)
o Youth – 75 (6% of sheltered count, 7% increase)
o Seniors (60+) – 173 (13% of sheltered count, in 2020 60+ data not collected for sheltered count) ▪ Seniors (62+) – 137 (10% of sheltered count, 71% increase) o Veterans – 49 (4% of sheltered count, 2% decrease)
o Chronically Homeless – 256 (19% of sheltered count, 98% increase) o Mental Health Issues -178 (13% of sheltered count, 3% decrease) o Substance Abuse – 52 (4% of sheltered count, 36% decrease) Overall Count Countywide
o
3,316 sheltered and unsheltered (full count, 15% increase overall) o
1,980 unsheltered (60% of total count; 8% decrease in unsheltered) o
1,336 sheltered (40% of total count, 83% increase in sheltered) Page | 5
Supervisorial District Highlights: Unsheltered Count
* In 2022 geographic coordinates were used to accurately attribute the City of Riverside Count to Districts 1 and 2 accordingly.
Note: Sheltered count data not included because supervisorial districts were not divided in 2020.
District
2022
Unsheltered
2020 vs. 2022
% Increase (+) or
Decrease (-)
Notes
1 373 -15%
• Majority of unsheltered population counted in Riverside* (82%) and Lake Elsinore (9%)
2 460 --9%
• Majority of unsheltered population counted in Riverside* (45%), Corona (24%) and Jurupa Valley (21%)
3 227 -11%
• Majority of unsheltered population counted in Hemet (36%), San Jacinto (25%) and Unincorporated Areas (21%)
4 670 +7%
• Majority of unsheltered population counted in Palm Springs (33%), Indio (16%) and Blythe (12%)
5 250 -24%
• Majority of unsheltered population counted in Moreno
Valley (31%), Perris (34%) and Banning (22%)
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INTRODUCTION
Homeless Point-In-Time (PIT) Count
To receive resources through the Continuum of Care (CoC) program, the U.S. Department of Housing and Urban Development (HUD) requires communities to conduct counts of both sheltered and unsheltered homeless persons, referred to as Point in Time Counts (PITC). HUD identifies a series of data to be reported to the national office and requires local CoCs to submit this data into the HUD Data Exchange (HDX) that can be aggregated into a national summary.
Importance of the Point-in-Time Count
» The count provides a “snapshot” of the number of people experiencing sheltered and unsheltered homelessness on a single night.
» Data collected is used to demonstrate need for federal and state funding, services, and resource planning.
» Locally, the data collected identifies areas of homeless concentration and determines the level of change from one year to another.
» HUD funding is awarded through a
competitive process that requires a PIT
Count and awards points based on the
CoC’s demonstration of a reduction in
homelessness from year to year.
» Data is reported to Congress through the
Annual Homeless Assessment Report
(AHAR) which is used by Congress, HUD,
and other federal departments to
understand the extent of homelessness.
» New programs funding from the State of
California now base awards on PIT Count
data.
Riverside County Homeless Point-in-Time (PIT) Count
In early 2020, Riverside County announced plans to consolidate the county’s homeless services into the Housing and Workforce Solutions (HWS) Department. The consolidation appointed HWS as the lead administrative agency for the CoC. As the appointed CoC lead agency, HWS took on the role of coordinating, in partnership with the CoC, the Homeless Point-in-Time Count.
A homeless PIT Count has been planned and coordinated annually in Riverside County since 2005. Yet, in 2020 the CoC requested an exemption from HUD not to conduct the 2021 unsheltered PIT Count due
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to the COVID-19 pandemic. The importance of conducting a homeless count in 2022 was magnified because there was a need to collect current and comprehensive data about the homeless population to determine the level of change.
The Riverside CoC gathers the data annually to learn how many people are experiencing homelessness, the
characteristics of those persons, who are using shelter and housing resources, who remains unsheltered and in what
communities, and most importantly what services people
need to help end their homelessness. At the local level, the CoC collects additional information that is useful in understanding the nature and trends in homelessness to
plan for services, strategically invest resources in effective interventions, and raise public awareness about homelessness. This additional data is not submitted to HUD but helps inform efforts to resolve or prevent homelessness and provides valuable information in responding to the special needs of various groups experiencing homelessness or at risk of homelessness.
Examples of locally gathered information include:
» identifying pregnant youth (HUD requires information on youth who are parenting)
» “Couch-surfers” who are temporarily housed by staying with others
» homeless pet owners
» services currently needed
» reasons contributing to homelessness as described by homeless persons themselves
Homeless Point-In-Time Count Components
To understand the extent and nature of homelessness, the annual Point-In-Time Count (PITC) must measure both sheltered and unsheltered homeless persons on the same date.
Sheltered Count
For persons who are sheltered on the night of the count, the PITC gathers data from the Homeless Management of Information System (HMIS) and information from shelter providers who do not participate in the HMIS. Interviews with shelter participants are not required because key information (demographic descriptions, shelter location, and household type) can be drawn directly from HMIS.
Unsheltered Count
The Riverside CoC uses a multi-method approach to conduct a complete census and known location count of the incorporated and unincorporated areas of the County. The Riverside PITC is an engaged count that attempts to connect with each person through personal interviews throughout the CoC Riverside County Continuum of Care
The planning body that coordinates county policies,
strategies, and activities toward ending homelessness
throughout Riverside County and its 28 cities. The CoC is a network of representatives from public and private
agencies serving the homeless population, city and
county representatives, law enforcement, faith-based
organizations, food pantries, advocates, school districts, colleges and universities, homeless and formerly
homeless individuals, and other community residents.
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geography and identifies the reason(s) when an interview cannot be conducted. Seven major components of data collection for the Riverside PITC of unsheltered persons include:
I. Unsheltered or Street-Based Count: Often referred
to as simply the street count, this component
focuses on a one-day, unduplicated, physical
count of homeless individuals and families living
on city streets, in vehicles and other places not
meant for human habitation. Hundreds of
volunteers help entire communities’ canvas their
neighborhoods to enumerate homeless persons.
Locations known to be frequented by unsheltered
persons are identified in advance of the count date and are the focus of the street count. The ‘known locations’ count focuses on places where multiple unsheltered persons are found at other times in the year such as encampments, ‘hot spots’ that frequently have larger numbers of unsheltered people clustered together, and service organizations.
II. Interviews: The Riverside PITC is an engaged count that attempts to connect with each person encountered during the designated PITC time periods. Volunteers complete PITC training and are given access the homeless Point-in-Time count survey specifically developed for Riverside County, to be accessed by their smartphones or tablets. The digital survey form simplifies the interview experience by eliminating the need to devote time and effort to determine which questions to ask and avoiding asking people to respond to questions clearly not applicable to their circumstances.
The survey design incorporates logical data sequencing that promotes asking only for relevant information by assessing the information given in response to prior questions.
III. Guided Observations: When conducting a street count, there are situations which make it nearly impossible for enumerators to interview a person in an unsheltered location. Persons may be found in areas visible to the PITC counting team but may be unsafe or impractical to access. It might not be safe to approach someone in an abandoned building or invade the privacy of someone who is sleeping and does not want to be disturbed. An encampment may be in treacherous terrain, not reasonably accessible. In these situations, an observation survey is completed to ensure the person is still counted as unsheltered.
IV. Service-Based Count: Outreach to service locations frequented by homeless persons begins on the day of the unsheltered count. The Service-Based Count may extend beyond the primary hours of the street count to locate and count unsheltered individuals missed during the count.
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Social service providers frequented by homeless individuals are recruited to participate in surveying homeless clients who were missed on the day of the count. The extended
Service-Based Count focuses on locations that were not
available during the established street count hours.
Screening is necessary during Service-Based Count because the service locations may offer mainstream resources to people qualifying as homeless as well as those who do not meet HUD’s definition of homeless.
V. Unincorporated (non-city) Area Count
Over the course of seven days, activities continued to ensure a full count with unsheltered persons in (non-city) unincorporated areas that include “harder-to-reach” sites that require more time to cover.
VI. Youth Count
A dedicated Youth Point-in-Time Count (YPITC) occurs over a 3-day period and identifies homeless youth ages 18-24 living in Riverside County.
VII. Come and Be Connected Events for Youth
Finding homeless youth experiencing homelessness is a challenge many communities face because youth do not access shelters, tend to couch-surf and are considered a hidden population. Come and Be Connected events are intended to connect youth experiencing housing instability or facing homelessness to community resources such as housing, mental health services, support groups, education assistance, and employment services.
POINT-IN-TIME COUNT PLANNING
An unsheltered PITC requires the community to develop approaches and methods to collect valid information from unsheltered persons while respecting the personal rights of persons living in homelessness. Planning involves careful consideration of when, where, how the PITC information is collected, who will conduct the count and how they will be prepared, and how the information will be handled once it is collected.
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Homelessness impacts communities across Riverside County and solutions to address it must be inclusive of community-wide and cross-sectoral partnerships. The 2022 plan incorporated recommendations and feedback from prior counts, HUD Guidance, insight from persons with lived experience, subject matter experts, and evidence-
based data from various sources.
A planning team was created to partner with
community stakeholders and plan and execute the
homeless count. The planning team was comprised of
a PIT Count coordinator, a Youth PITC coordinator
with extensive homeless youth outreach experience,
a Homeless Youth coordinator, and several
Continuum of Care staff with previous PIT Count
experience.
Overview
a. Develop an Inclusive Homeless Point-in-Time Count Plan PIT Count planning for 2022 focused on implementing a full and accurate unsheltered count. The planning team worked to ensure sufficient coordination with city and community leaders and implemented volunteer recruitment strategies to recruit 500 community volunteers. The planning team worked closely with the County Public Health Department to incorporate health and safety protocols. The More Than a Count initiative was the theme for the 2022 PIT count and included a housing and services linkage component that provided client-level data to homeless street outreach teams, in each of the five supervisorial districts, to facilitate follow-up care after the count.
The plan and methods used for the Riverside County PITC, and its cities was developed through community involvement in a series of meetings held over a period of six months. The community planning meetings that convened key leaders and stakeholders, service providers, law enforcement, youth service providers, and non-profit agencies were launched in September 2021. Six monthly planning meetings with an average of 80 community partners in attendance were facilitated in preparation for the homeless count. The virtual community planning meetings were recorded and available to community partners unable to attend.
Purpose of the Planning Meetings:
▪ Ensure an effective and accurate PIT Count
▪ Enhance the implementation process
▪ Facilitate discussions to address 2020 PIT Count challenges ▪ Facilitate collaborative discussions on priorities, outreach and engagement strategies, location mapping, mobile survey development and identification of deployment sites in each city ▪ Discuss community concerns about implementing an unsheltered count during the pandemic
o More Than a Count Initiative (New)
o Housing and Services Linkages (New)
o Dedicated Youth and General Point-in-Time
Count Webpage (New)
o Volunteer Registration Portal (New)
o Expedited Path to Immediate Services for
Seniors and Young Adults
o Community Planning Meetings
o Marketing Toolkit
o County Coordinator Assigned to Assist at
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▪ Develop public health considerations (e.g., provide personal protective equipment (PPE) and other recommendations) to minimize risk for county and community volunteers and unsheltered residents
▪ Mobilize community partners to promote and participate in the homeless count
To view recordings of the 2022 Point-in-Time Count community planning meetings go to:
https://harivco.org/ContinuumofCareDivision/HomelessPointInTime(PIT)Count/tabid/268/Default.aspx
COMMUNITY PLANNING MEETINGS
COMMITTEE GOALS AND TASKS
Before Count
Activities
▪ Develop a publicity and awareness campaign
▪ Create volunteer recruitment strategies
▪ Discuss volunteer training
Tools and Methods ▪ Review 2020 data collection tool and discuss the addition of possible new questions
▪ Review survey to ensure compliance with HUD M ethodology ▪ Discuss data analysis
▪ Discuss results reporting
Management ▪ Identify deployment sites
▪ Review day of count process
▪ Ensure appropriate volunteer management
▪ Coordinate Soft Count to identify hot spots prior to the count ▪ Create area coverage maps
▪ Address COVID -19 related
safety concerns
Planning Specialty
Counts
▪ Develop protocol for supporting seniors and
youth/unaccompanied minors identified during the count
▪ Plan the Service -based Count
▪ Plan the Unincorporated Area Count
Youth Count
Planning
▪ Design the Youth PIT count methodology
▪ Identify key partners to support and promote the youth count ▪ Partner with youth service providers to secure deployment site ▪ Develop plan for Come and Be Connected (magnet ) events for youth
▪ Offer t rainings and increase community awareness
▪ Increase number of cities canvassed during the count
▪ Develop strong college and university and community
partnerships
.
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b. More Than a Count Initiative
While collecting data is a central purpose for the PITC, the Riverside County CoC recognized the mandated PITC as an opportunity to do more than simply count homeless people. The PITC is a chance to connect with a people who are unsheltered. The approach to the 2022 PITC was one of engagement and service. The goal of the More Than a Count initiative was to maximize county-wide bed availability on the day of the count for immediate referrals. Transporting individuals to an assessment site was a critical element of the plan, but COVID-19 restrictions posed challenges and limitations which resulted in not being able to integrate this plan in 2022.
The planning committee developed a strategy using the mobile application to collect client-level data and work with street-based homeless outreach teams to coordinate a post count response.
Information collected allowed outreach teams to facilitate after care services, inclusive of housing and other social services, to individuals who requested follow-up.
Come and Be Connected Events for Youth
The Youth Point-in-Time Count (YPITC) planning team designed events to ensure the Youth Count accurately reflected the number of unaccompanied youth and Transitional Aged Youth (TAY) experiencing homelessness. These events were designed to be welcoming, safe, and to entice homeless youth to convene in one location and participate in the Youth PIT Count. Youth Opportunity Centers (YOC) were identified as appropriate locations for the Come and Be Connected events because they are dedicated to serving youth. To ensure these events were accessible to youth, who typically struggle with transportation, all five County of Riverside Supervisorial Districts hosted a Come and Be Connected event. The goal was not only to survey youth about their homelessness experience, but to provide an opportunity to address their needs.
c. Selection of a Date and Time
Per HUD requirement, the date and time of the 2022 Point-in-Time Count should fall within the last 10 calendar days of January to ensure consistency across the U.S. and allow for trends to be monitored appropriately. During the colder months, homeless individuals are more likely to access emergency shelters making it easier to count them than when they are unsheltered and moving around. In Riverside County, selection of the PIT date also takes into consideration the PIT Count dates of neighboring counties to avoid two counts taking place on the same day and potentially overwhelming shared resources.
d. City Leaders, Deployment Sites, and Orientation
Homelessness impacts communities across Riverside County and the planning team’s goal was to be inclusive of community-wide and cross-sectoral partnerships. As in previous years, the
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planning team depended on the collaboration and participation of city leaders to ensure county- wide coverage for the unsheltered PIT Count. Mayors and city managers were invited to designate a point of contact from their city to ensure maximum participation during planning and to help facilitate a count in each city. The city appointed individuals took on the role of leads during the count. The Riverside Sheriff’s Office (RSO) Homeless Outreach Team (HOT) was engaged early to lead and guide planning for the Unincorporated Area Count.
Site leads were selected because of their
familiarity of local homelessness, where homeless
individuals live, where they spend their time and
where they access services in their community.
Additionally, site leads were familiar with city
resources, local volunteer programs, and faith-
based organizations allowing them to leverage
resources, including volunteers, to assist on the
day of the count. Leads worked closely with the
planning team to share their knowledge about
homelessness in their city, obtain guidance and
training about implementing HUD’s definition of
homeless during the count, accurately coordinate
the count, create volunteer counting teams, and
identify incentives and materials/supplies needs at
their site.
County Coordinators
County coordinators were assigned to work with the site leads and provide support on the day of the unsheltered count. The planning team worked with site leads to determine the level of support each deployment site needed. Coordinators played an important role in the success of the deployment site where they were assigned. Their primary role was to work alongside the site leader and follow the day of count agenda, ensure volunteers followed procedures, and conducted a concise and accurate count. Coordinators assisted with volunteer check-in, distribution of volunteer materials and provided technical support related to the survey app.
Most coordinators were paid county staff with previous PIT Count experience.
Deployment Site Leader and County Coordinator Orientation All county coordinators and deployment site leaders, especially new site leaders, were asked to attend a How to Implement the Point-in-Time Count Orientation weeks prior to the count. The orientation was facilitated virtually and included information about how to prepare for the day of the count, a step-by-step review of the day of the count agenda, how to conduct the volunteer check-in process, and prepare site for volunteers. Orientation sessions were attended by deployment site leads, city staff, county coordinators and law enforcement. The orientation
Deployment Site Leaders worked to
implement a comprehensive count by:
o Identifying a deployment site to be
used on the day of the count
o Collaborating with local law
enforcement
o Identifying encampments and other
locations where homeless persons
live/sleep/hangout
o Identifying places where homeless
persons access services and other
assistance in their city
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was recorded, and all city deployment site leads, and county coordinators received a link to access the recording to view and access as needed.
e. Survey Tools
Interview and Observational Surveys
The Point-in-Time Count is so important because it gives communities an opportunity to increase their understanding of the homeless population and to learn more about the characteristics of its homeless residents. The ideal way to collect this information is to engage individuals and interview them. The goal of the PITC is to interview as many unsheltered individuals as possible.
Interview Survey
The 2022 PIT Count survey tool used was a slightly modified version of the 2020 survey. Survey modifications were based on revisions targeting data quality and improvement, community partner input, and revisions to align the survey with HUD model survey and definitions. The 2022 survey expanded on questions related to recently being release from jail or prison and couch surfing. Both were a result of partner input during the monthly community planning meetings.
A sample of the questions included in the 2022 PITC survey can be found in Appendix B. 2022 GENERAL INTERVIEW SURVEY
Question Additions or Edits
Surveyor full name and
phone number
Useful when clarification about a survey completed by the surveyor is needed.
Where person slept the
night before the count
Added Locations:
• Tent/shed
• Tiny home without access to water, kitchen, restroom, utilities
• Tiny home with access to water, kitchen, restroom, utilities • Emergency shelter (or motel/hotel paid for by a non-profit or government entity)
• House or apartment (not couch surfing)
Couch surfing Expanded question:
• What do you have to exchange to stay there?
• Can you remain there for at least another 14 days?
Ethnicity Are you Hispanic/Latin(o), (a), (x)?
Race • American Indian, Alaskan Native, or Indigenous
• Asian or Asian American
• Black, African American, or African
• Multiple-Races
Gender • Questioning
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Text highlighted in blue identifies edits made in 2022
Observational Survey
When a counter is unable to access a person who is clearly homeless or when the person contacted refuses the request to be interviewed, the counting team uses observation to assess the likely characteristics of a person. The survey instrument includes questions to guide the observer in recording some characteristics that can be observed by the enumerator. For example, it may be possible to determine a person’s gender, but not his or her chronic homeless status. When recording observations, the enumerator records as much information as practicable about the physical location where the person is observed (e.g., the street name, any landmarks), as well as the person’s physical description (e.g., clothes, personal belongings, traveling with a pet). This information assists with deduplication and facilitates further outreach to the person after the PITC. HUD guidelines allow this observational technique in the following circumstances:
• Barriers to entering the site where homeless individual is located • Site is unsafe to enter
• Individual refuses to participate
• Individual is sleeping and does not want to be disturbed • Language barriers exists
• Individual is unable to respond (e.g., mental issues, intoxication)
Text highlighted in blue identifies edits made in 2022
Reason for
homelessness
• Family Disruption (death in the family, divorce, child removal, or violence)
• Substance Abuse
Jail or prison Expanded question:
• Have you faced barriers in accessing housing because of your or your family members’ arrest or conviction record?
GENERAL OBSERVATIONAL SURVEY
Question 2022 Edits
Reason for using observational
survey
• You cannot physically get to the location (unable to see individual(s)
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Youth Point-in-Time Count (YPITC) Survey Tool
The 2022 Youth PIT Count interview survey incorporated all demographic questions included on the general PIT Count survey and if a respondent was between the ages of 18 and 24 years old, they were asked youth-specific questions.
YOUTH SURVEY
Question Additions or Edits
Are you currently enrolled
in school?
Revised question:
What is your school experience?
• Trade School
The Youth PIT Count observational survey was identical to the general PIT Count observational survey.
More Than a Count initiative - housing and services linkages survey questions To the greatest extent feasible, each person who appeared to be homeless was invited to complete an interview and provide their contact information for follow-up services. The survey asked about the types of services needed. The following are the options provided:
o Animal services (veterinary services, pet food, etc.) o Applying for Calfresh, Cashaid or general assistance
o Behavioral/mental health services
o Food pantries in the community
o Foster youth services
o Health care/medical services
o Help if you are couch-surfing, unstably house or at risk for homelessness in the next 14 days o Housing services (emergency shelter, transitional housing, permanent housing, etc.) o In-home supportive services or other caregiver services o Legal aid services (unlawful eviction, tenant rights, child custody, child support, record expungement, etc.)
o Obtain documentation (CA ID card, social security card, birth certificate, etc.) o Substance use services
o Other
f. ESRI Geographical Information System (GIS) Mobile PIT Count All data for the 2022 Homeless Point-in-Time Count was collected using the Survey 123 app on mobile devices. The benefit of conducting the homeless count using a digital survey, besides increased accuracy, and speed for recording surveys, is the use of geolocation. This feature enables the county to report results at city and district levels and coordinate outreach by informing service and outreach agencies about the exact location of difficult to reach Page | 17
subpopulations like youth and veterans. Geolocation can also identify geographical patterns and trends when comparing data from year to year.
g. Volunteer Recruitment and Training
The homeless count is a county-wide
undertaking that requires community
volunteers to take part and survey as many
unsheltered individuals as possible. It would
be incredibly difficult to conduct the
unsheltered count without volunteers to cover
the entire geographic area.
Volunteer Recruitment Plan:
▪ Led by public information specialist from the Department of Public Social Services (DPSS) ▪ Promote participation and stakeholder support
▪ Conduct individual meetings with cities leads as needed ▪ Create a website specific to general and youth homeless counts to include a volunteer registration link
▪ Implement volunteer management software:
» Provide access to volunteer training
» Facilitate communication between volunteers and planning team ▪ Develop social media/marketing tool kit:
» Volunteer recruitment flyers for print/email
» Flyers sized for social media platforms
» Social media sample posts
» PowerPoint slide for city council
» FAQ document
These efforts helped build awareness of the PITC and highlight its purposes and benefits, as well as provide information about the implementation of the PITC. The planning team set a goal to recruit 500 volunteers to implement the street-based homeless count of families, youth, seniors, and adults. Recruitment activities conducted for the 2022 PIT Count included:
• Distribution of general count and youth count recruitment flyers to community partners
• Posting flyers on city websites and social media platforms (Facebook, Instagram, Twitter)
• E-mail blasts to past PIT count volunteers, local businesses, and community partners • Engage local colleges, universities, and school districts
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• Press release announcing need for volunteers and information about ways to support the count
• New website developed exclusively for the general and youth homeless PIT Count:
MoreThanACount.org
• City leads were engaged to recruit volunteers within their city since volunteers tend to be more reliable and are more likely to participate on the day of the count
Volunteer Registration
Volunteer feedback from the 2020 count identified volunteer management and communication as an area in need of improvement. In response to this feedback, the planning team obtained a volunteer management system to register and communicate with volunteers. The system enhanced administrator’s ability to monitor completion of volunteer requirements using qualification fields, collected signed liability/release waivers, simplified volunteer’s ability to review and accept assignments, allowed city leads to view volunteer lists, and provided volunteers access to the required volunteer training.
Volunteer eligibility included:
• Submit signed Liability Release form
• View mandatory training (general count or youth count)
• Pass training quiz
• Confirm use of smartphone or mobile device with ability to download Survey123
• Ability to walk and/or stand for an extended period
• At least 18 years old or 16-17 years old with an accompanying adult
• Abide COVID-19 mandates, including but not limited to using proper Personal Protective Equipment (PPE) and observing social distance requirements
• Volunteers were encouraged to be fully vaccinated or test prior to participating in any PIT count activities
Volunteer Communication
All individuals interested in volunteering for the homeless count were encouraged to register and create a volunteer profile. Once a profile was created, the individual could work to complete requirements for participation. To enhance communication with and maintain volunteers informed about PIT Count activities, weekly updates were generated through the volunteer portal using a RivcoPIT County email address. Volunteers could also email the planning team questions or specific requests. Reminders were sent to individuals missing information or those who had not completed the volunteer requirements. If at any time a participant was no longer available to volunteer, they could communicate this by accessing the volunteer portal. Once all requirements had been met, administrators changed the status on the person’s profile to “accepted”. Upon registration, volunteers were asked to select two cities where they would like Page | 19
to volunteer. A week prior to the PIT Count, volunteers were assigned to their deployment site and provided the address, cite lead contact information, and volunteer check-in time.
Volunteer Trainings
HUD releases a PIT count collection notice every
year that guides CoCs about the data that must be
collected to successfully complete the homeless
count. An important requirement is that all
volunteers participating in the PIT Count be
trained accordingly to promote uniformity and
ensure high-quality data collection. Volunteers
completed on-line training and testing before
obtaining access to the ESRI 123 Survey. A QR
code was created and provided to volunteers for
quick access and to ensure the correct survey was
used.
Volunteer Training Objectives:
» learn about the importance of the homeless count
» learn how to prepare for the count
» learn the roles of the team
» learn how to perform the count
» learn how to be safe throughout the process
» learn how to download and complete the survey tool accurately
In consideration of established COVID-19 Public Health precautions, the planning team facilitated two live, virtual trainings in early January 2022. One training was intended for general count volunteers and the second training was specific to volunteers participating in the youth count.
Both trainings utilized the same curriculum with the youth training covering additional key topics related to youth like the definition of homeless youth, sensitivity towards Lesbian, Gay, Bisexual, Transgender, Queer (LGBTQ+) youth, general tips for engaging youth and mandated child abuse reporting guidelines.
Since volunteer registration was still open, the trainings were recorded and uploaded to the volunteer portal where registered volunteers could access and view or review as often as needed. After viewing the recorded training, volunteers were prompted to take a short quiz to complete their training requirement. Administrators used quiz completion as confirmation for completing the training.
Live, Virtual Volunteer
Trainings
General and Youth Count
Trainings
1 ½ - 2-hour trainings
Recorded and Uploaded to
Volunteer Portal
148 volunteers joined general
and youth training
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h. Incentives
The unsheltered homeless count provides the community an opportunity to interact with and engage unsheltered individuals. Volunteers are provided with resources and items to give their homeless neighbors that may help break the ice and motive the person to respond to the survey.
Incentives are also used to thank the person being interviewed for their time and responses. In 2022, incentives were distributed to individuals responding to the survey during the week of the count. Approximately, 1,500 incentives were distributed to deployment sites for the homeless count. Incentives were packed in light weight, easy to carry and distribute backpacks that were appealing to individuals receiving them.
Incentive bags included:
• Light weight, string backpack
• Beanie
• Gloves
• Socks
• HomeConnect (Coordinated Entry
System) lanyard or bracelet
Travel-sized, hygiene items included in incentive bags:
o Shampoo/ conditioner
o Feminine hygiene products
o Toothbrush/ toothpaste
o Lotion
o Soap
Special COVID-19 funding to be used for homeless street outreach efforts through the Emergency Solutions Grant (ESG) facilitated the purchase of additional items, not included in incentive bags in previous years:
o Hand warmers
o Manicure set
o Thermal blanket
o Hand-crank flashlight
o Hand sanitizers
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a. Youth Count Planning and Community Engagement
As in previous counts, Operation SafeHouse (OSH) served as a lead agency in the YPITC planning efforts. OSH is a non-profit organization that offers emergency shelter and transitional living for youth living in Riverside County. OSH focuses on servicing homeless youth and youth in crisis between the ages of 11 and 24. The youth PIT Count coordinator was an experienced homeless youth outreach team leader from Operation Safe House.
The planning team facilitated 6 community planning sessions in the months leading up to the count.
These sessions included all aspects of the Point-in-Time Count (General Unsheltered Count, Unincorporated Area Count, Service-Based Count, and Youth Count). In addition to general discussion, smaller break-out workgroups brought together a diverse group of youth service providers to discuss and plan for the YPIT Count.
YOUTH POINT-IN-
TIME COUNT
PLANNING
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Community partners and service providers included:
The workgroup was able to draw insight, information sharing, and discussion toward planning efforts and encouraged cooperation in areas focusing on youth-friendly volunteer recruitment, identification of hot spots, youth homelessness awareness, and incentives. Additionally, the subcommittee worked to:
» Identify youth-friendly volunteers
» Create canvasing teams familiar with the city and homeless youth hot spots
» Recruit experienced individuals who had strong knowledge or worked directly with youth and homeless to allow for easier rapport building when surveying
» Ensure that youth volunteers understood the day-to-day challenges and trends homeless youth face to be effective on the streets
b. Challenges in Identifying Homeless Youth and Homeless Transitional Aged Youth Conducting a YPITC is challenging because homeless youth and homeless transitional aged youth are extremely difficult to identify. Key factors that contribute to this challenge include but are not limited to:
• Unwilling to participate out of fear of being sent back to their home/ group home • Unwilling to participate out of fear that law enforcement will be notified • Unwilling to participate out of fear of being labeled “homeless” in front of their peers or to avoid the “stigma” of being homeless
• Distrust of adults and/or authority figures
• May not show overt signs of being homeless or may try to “blend in” with their peers • May not believe themselves to be homeless
• May not want to access homeless resources out of fear of being placed in shelter with much older homeless individuals
• May experience short periods of homelessness at various times throughout the year o The CoC’s Youth Advisory Committee (YAC) and Youth Action Board (YAB) o California Family Life Centers
o Queer Works
o Transgender Health and Wellness Center
o Operation SafeHouse
o SafeHouse of the Desert
o Riverside University Health System – Behavioral Health o Springs Charter Schools
o Riverside County Youth Commission
o All five of the Youth Advisory Council Districts
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c. Youth Count Deployment Sites
Deployment sites are designated locations that serve as a base of operations for the street-based count. Each youth deployment site was led by an individual with street outreach experience and familiarity with hotspots and areas where youth tend to congregate. Site leads were assigned to coordinate activities in the same deployment site through the duration of the count to lessen the risk of duplication.
d. Homeless Youth Awareness and Promotion
To raise awareness regarding the homeless Youth Count and the Come and Be Connect events, event flyers and social media was utilized. Because youth are active on social media like Instagram and Facebook, youth specific posts were created to disseminate information and reach as many youths as possible. During community presentations and community planning sessions, attendees were asked to distribute the volunteer recruitment flyers, Come and Be Connected flyers and/or social media posts on their respective social media pages.
e. Youth Count Volunteer Recruitment
To conduct a successful Youth Count, the planning team relied on the participation of many volunteers to canvas the entire county. Volunteer recruitment efforts for the Youth Count mirrored general count recruitment. The Youth Count planning team established a goal of recruiting 100 youth volunteers. At registration, volunteers were given the option to assist in general count, the Youth Count or both. Additionally, they were asked to provide their availability during the week of the count to allow the planning team to reach out if additional support was needed.
f. Youth Involvement
The homeless Youth Count provides an
opportunity to raise awareness about
youth experiencing housing instability
and facing homelessness. The YPITC
planning team worked closely with the
County Continuum of Care’s Youth
Advisory Committee (YAC) and Youth
Action Board (YAB) to obtain their input
in recruiting youth friendly volunteers,
partnering with agencies servicing
youth, and best practices in engaging
homeless youth on the day of the count.
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Youth Advisory Committee (YAC)
YAC is made up of 40-50 youth service providers and advises the Continuum of Care on issues and strategic planning activities related to ending youth homelessness. YAC agencies were recruited to serve as a designated deployment site and/or vendors at the Come and Be Connected events, to assist with a youth specific incentive drive, to recruit youth they serve to participate in the YPITC, and to register and volunteer for the homeless youth count.
Youth Action Board (YAB)
YAB is composed of homeless and formerly homeless youth between the ages of 18 and 24. YAB members share their voice to advocate for homeless youth and their input is taken into consideration in policymaking decisions of the Riverside Continuum of Care. YAB members are instrumental in helping shape policies that relate to ending youth homelessness. They serve as the experts that review and provide input on youth project applications and serve as ambassadors to strengthen relationships within the community and promote youth activism in governmental affairs. YAB members attended community planning meetings and activities such as an incentive drive for youth. Youth Action Board members participated in the street-based Youth Count and Come and Be Connected events.
Riverside County Youth Commission
The Riverside County Youth Commission has established itself as a strong supporter of the YPITC.
Each of the 5 County Supervisorial District supports a Youth Advisory Council. The Council is intended for high school students in each district who wish to serve their communities. The Youth Commission consists of all 5 District’s Youth Advisory Councils who make recommendations to the County of Riverside Board of Supervisors about youth related issues. The YPITC planning team invited the Council to participate in the homeless Youth Count and support the Come and Be Connected events. The Commissioners agreed unanimously to support YPITC efforts.
g. Youth Count Incentives
Incentive bags and bottled water were made available to YPIT counting teams to entice youth to participate in the interview but also as a thank you for their participation. Approximately, 400 incentive bags were assembled and provided to youth count leaders for distribution to youth experiencing homelessness.
The youth incentive was a light-weight drawstring bag that included:
o Gloves
o Socks
o Cold weather hat/beanie
o Hygiene items
o Mini-resource booklet
o Other items such as safe sex kits, non-
perishable foods, school supplies and
blankets
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Special ESG COVID-19 funding, intended for homeless street outreach efforts, allowed the planning team to purchase additional items, not included in incentive bags in previous years:
o Hand warmers
o Manicure set
o Thermal blanket
o Hand-crank flashlight
o Phone charger kit
o Hand sanitizers
METHODOLOGY
Unsheltered Count
The PITC plan for the day of the count included basic enumeration, surveys conducted by interview, and observations conducted by trained volunteers, outreach teams, and persons with lived experience.
Using mobile electronic technology with GIS mapping capability enables the capture of the survey location and data in real-time and fosters easier follow-up activities with unsheltered persons.
Additional PITC activities occurred within a 7-10 day period beginning with the day of the count. The 2022 unsheltered count methodology was implemented similarly to the 2020 count. The following includes the dates of the primary components of the 2022 PIT Count:
The Riverside County’s 2022 Homeless Point-in-Time Count was conducted on the following dates:
• Street-Based Count: February 23, 2022, 5:30 a.m. to 9:30 a.m. (extended to February 28, 2022) o In line with HUD’s special exceptions and guidance of extending the survey period from 7 to 14 days, the street-based count was extended to February 28, 2022, to ensure a comprehensive, full count.
• Youth and Young adults (ages 24 and under) Count: February 23, 2022 – March 4, 2022, 2:00 p.m. - 8:00 p.m.; multi-day count; including street-based and Service-Based Count o In line with HUD’s special exceptions and guidance of extending the survey period from 7 to 14 days, the youth count was extended to March 4, 2022, to ensure a comprehensive, full count.
Feedback from leads determined extreme weather conditions in Riverside County resulted in low volunteer participation that slowed down counting efforts.
• Service-Based Count: February 23, 2022 - February 25, 2022, 9:00 a.m. - 5:00 p.m.; three-day count
• Unincorporated (non-city) Area Count: February 23, 2022 – March 2, 2022
Street-Based Count
The Riverside count was conducted as a ‘blitz’, meaning the count was conducted in all cities at the same time. The street-based PIT Count took place on February 23, 2022, from 5:30 a.m. to 9:30 a.m.
Two weeks prior to the count, city leaders engaged in a soft count to identify hot spots and areas where unsheltered individuals were known to congregate. If the identified known locations were not reached on the morning of the count, the areas were counted on one of the seven days following.
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City leads printed city maps or used the ESRI Survey 123 app to enter location information and create a web map that included information such as street names and landmarks, safe/non-safe areas, and city boundaries. Using this information, city leaders worked with law enforcement to divide their city into smaller/manageable areas to create their coverage area maps. Canvasing teams were assisted by homeless outreach workers and law enforcement to ensure safety during the count. Given the COVID- 19 pandemic, the 2022 PIT Street Count design included a safety-first approach to protect the health of everyone involved.
719 individuals (625 general count; 94 youth count) assisted in implementing the 2022 homeless count.
Overall, there was a 14% decrease, compared to 2020, in the total number of volunteers who participated in the count. The decrease in volunteer participation was attributed to the ongoing COVID- 19 pandemic.
In total, 842 individuals created an account and a
profile from December 2021 to February 18, 2022.
Of these, 53 individuals withdrew due to
scheduling conflicts (possibly due to the change in
date of the count), health complications, and cold
weather on the morning of the count. 155 individuals
did not meet requirements (attend training and pass quiz) or did not respond to requests to complete volunteer requirements, and they were removed from the list of potential volunteers.
On the day of the count:
» Trained volunteers reported to assigned deployment site to check-in
» Site leaders finalized their counting teams that included 3-5 volunteers each
» Everyone on the team had a specific role:
o Team Leader (previous PIT Count experience)
o Driver (must have large vehicle and be a licensed driver) o Counters (attended the volunteer training and have Survey123 app on phone/device) o Look-out/Incentives
o Law Enforcement Escort (as needed)
» Teams were assigned a specific city location to count in and were guided by a map with clearly marked areas and boundaries
» Law enforcement conducted a brief safety presentation
» Volunteers received incentive bags, deployment site leader contact information, flashlights, safety vests, volunteer id badges and deployed with fully charged cell phones or devices
» Once the assigned area was covered, volunteers were instructed to return to the deployment site to check-out and return materials
14%
decrease
2022
719
volunteers
2020
842
volunteers
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On the morning of the general count, attendance sign-in sheets recorded a total of 469 registered volunteers who signed in and participated at a Point-in-Time Count deployment site. Some individuals signed-in but were not registered and were assigned to assist in other count activities except to conduct surveys. Law enforcement partners were not required to register as volunteers since their primary role was to escort volunteers. However, city leaders and Sheriff’s Office reported a total of 146 officers/deputies deployed to assist and participate in the homeless count. The total number of volunteers who assisted in the implementation of the general count was 625.
Homeless Youth and Transitional Aged Youth Count
.
.
▪ February 23, 2022 to March 4, 2022 from 2:00 p.m. - 8:00 p.m. ▪ Planned and implemented following the same data collection methodology as the general unsheltered count.
▪ Multi-day count and survey to identify:
o Unaccompanied minors between 11 – 17 years not in the care of a parent, guardian, or responsible adult
o Transitional Aged Youth (TAY): 18 – 24-year-olds
On the day of the count:
» Youth Count volunteers checked-in with the deployment site lead » Deployment site leads assigned volunteers into a counting team at check in » Leads provided each team with clearly marked maps indicating assigned areas to canvas » Teams were instructed to stay within the area boundaries to avoid duplication » The YPITC was divided into 3 shifts
» The YPITC was extended past initial 3-days to ensure a full count with the support of county staff and OSH street outreach teams
Deployment Site Locations
1. Operation SafeHouse, Riverside, CA
2. Rubidoux Youth Opportunity Center, Riverside, CA
3. California Family Life Center, Empower Youth, Hemet, CA
4. SafeHouse of the Desert, Thousand Palms, CA
5. Department of Public and Social Services, Indio Office, Indio, CA
6. Department of Public and Social Services, Banning Office, Banning, CA
7. Building Up Lives Foundation, Moreno Valley, CA
Social Work Action Group (SWAG) took the lead in conducting the YPITC in the cities of Lake Elsinore, Temecula, Murrieta, and Perris since they had established street outreach contracts with these cities and are familiar with the youth homeless population.
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55 registered individuals participated in the youth street-base count during the extended count and an additional 26 unduplicated volunteers attended Come and Be Connected events. Law enforcement deputies/officers did not participate in the Youth Count. The total number of volunteers that participated in implementing the Youth PIT Count was 94.
The YPITC employed special outreach and service activities designed to promote youth participation in the count. Come and Be Connected magnet events were designed to engage youth participation in the interview process and to connect youth to community services. The events included raffles and giveaways, food, and entertainment that appealed to youth. Information about the PITC and special events was distributed through social media and flyers and posted in colleges and universities, youth service provider agencies, recreation facilities, and libraries and Continuum of Care agencies.
Come and Be Connected youth friendly host sites included:
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A diverse group of vendors offering housing, social services, transitional living programs, rapid rehousing, reproductive health, mental health services, domestic violence, rehabilitation services were invited to attend an event closest to their service area. Over 30 vendors participated in a Come and Be Connected event and every event included at minimum 7-10 vendors.
Additionally, planners ensured that every event included Medical, CalFresh, CalWORKs and rapid rehousing services. In addition to service provision and survey participation for the Youth PIT Count, the Come and Be Connected events served to bring awareness to the community about youth homelessness and the multitude of issues faced by young adults.
Service-Based Count
Coordination of the Service-Based Count focused on identifying and inviting organizations providing social services to the homeless population at various locations. The service-based count included public or private agencies (i.e., community pantry, homeless shelter, food bank, community resource centers) frequented by individuals and families experiencing homelessness. For the 2022 Point-in-Time Count 12 community homeless service providers participated in the Service-Based Count.
Service-Based Count Agency Engagement
▪ Approximately 40 community agencies were identified as possible partners
▪ Planning staff communicated with potential agencies via email and invited them to participate. An informational fact sheet about the purpose of the Service-Based Count was provided ▪ February 23, 2022 – February 25, 2022 from 9:00 a.m. – 5:00 p.m. ▪ A multi-day count
▪ Implemented to ensure that unsheltered individuals not counted or missed on the day of the street-based count were identified and interviewed.
On the day of the count:
» Participating agencies welcomed volunteers or used their own trained staff to screen and interview clients/customers identified as possibly experiencing homelessness
» Clients were asked for their participation in a survey regarding their housing status
» To eliminate duplication, volunteers used screening questions to determine if the person had already completed the survey or if they had recently been interviewed by someone
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▪ Planning staff attended Emergency Food and Shelter Program (EFSP) meetings to invite agencies to participate
▪ The planning team collected general information (i.e., hours of operation, number of people served, types of services provided) of interested agencies
▪ Agencies had the option of training their own staff to conduct the interviews or requesting community
volunteers
▪ Participating organizations chose the days and times
to participate (within the service-based count time
frame)
▪ Volunteers/staff used the Survey123 app to conduct
interviews
▪ Any staff or volunteer participating in the service-
based count was required to register and attend the
volunteer training
Service-Based Count Training
The planning team facilitated a 1 hour live, virtual training attended by 12 agency representatives.
Topics included in the training were:
» Purpose and importance of the Service-Based Count
» Confirmation of days and times of agency participation
» Confirmation of the number of volunteers needed (a minimum of two volunteers were assigned per location)
» An Q & A forum to answer questions from participating agencies
o Community Pantry
o Set Free Thrift Store
o Galilee Center
o Food Now
o City of Moreno Valley
o Department of Public Social Services
(DPSS) – Self-sufficiency
o FIND Food Bank
o Catholic Charities
o Lutheran Social Services
o Jewish Family Services San Diego
o First 5 Riverside County – 2 Family
Resource Centers
Service-Based Count Participating Agencies
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Unincorporated (non-city) Count
Due to Riverside County’s expansive geography, some harder to access encampments and unincorporated areas required multiple days to fully cover them. The Riverside Sheriff Office (RSO) Homeless Outreach Team (HOT) took the lead role in planning and implementing the Unincorporated Area Count.
The Homeless Outreach Team worked to identify the best dates to canvas unincorporated areas, identified deployment site locations, worked with a county coordinator, and requested an adequate number of trained volunteers to assist.
HOT coordinated deputies at 10 of the Riverside Sheriff’s Office (RSO) Stations to implement the Unincorporated Area Count. In some instances, deputies collaborated with a city and conducted the Unincorporated Area Count in conjunction with the general count. The Homeless Outreach Team communicated with lead deputies to ensure proper coverage and if an area was unable to be canvassed by the assigned team, there were other community agencies on stand-by if RSO deputies needed assistance.
Two planning meetings were coordinated, and community agencies were invited to provide input and share available resources. Unincorporated areas included 12 tribal reservations and the planning team extended an invitation to tribal community leaders to participate in all aspects of the homeless count.
During the meetings, a total of 80 unincorporated areas were identified to be canvassed in addition to 12 tribal reservations. Key agencies took leadership roles to ensure complete coverage of non-city areas:
• Riverside County Sheriff's Office (RSO)
• Department of Behavioral Health (RUHS-BH) HHOPE
• Riverside County Code Enforcement
▪ February 23, 2022 – March 2, 2022
▪ Street-Based Count conducted in non-city areas of the County
During the week of the count:
» The Unincorporated Area Count followed the same structure as the general and Youth Counts » Riverside County Sheriff’s Office (RSO) deputies served as site leads » Volunteers checked in to their assigned deployment site » Deputies escorted counting teams to pre-identified unincorporated areas to count
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Sheltered Count
Homeless Management Information System (HMIS)
In accordance with HUD requirements and methodology standards, the Sheltered Count involved counting homeless individuals and families who stayed in emergency shelters and transitional housing on the night of February 22, 2022. Sheltered Count and subpopulation data was derived from HMIS data and provider-level surveys.
The HMIS team developed a 30-minute virtual training to prepare all HMIS participating agencies on the data collection process and requirements for the PIT Count and Housing Inventory Count (HIC). The training was recorded and shared with partners to allow for review. The training emphasized the users’ responsibilities for ensuring data quality, accuracy, completeness, and timeliness. The training also included:
» 2022 HIC & PIT Count changes
» Types of projects to include in the HIC
» HIC spreadsheet demonstration
» Important deadlines
HMIS participating agencies were given 2 weeks to review and complete the PIT Count data entry and the HIC. For non-HMIS participating agencies (domestic violence housing providers), a survey and a PIT Count data entry form were provided which collected demographic, household, and subpopulation data.
This information was used to complete the population reporting requirement. The survey included a definition of terms and detailed instructions to ensure data verification and data quality standards were met.
Housing Inventory Count (HIC)
The Housing Inventory Count (HIC) provides a snapshot of the number of beds and units available on the night designated for the Count by program type. The HIC also includes the number of beds dedicated to serve people experiencing homelessness as well as persons in Permanent Supportive Housing.
SUB-POPULATIONS OF INTEREST
Based on the principle of providing services where they are needed most, attention is given to special homeless subpopulations. These special populations are defined as follows:
Families with children Any group of people that identify themselves as a family regardless of marital status or relationship. Households composed of at least one adult and one child under the age of 18 (according to HUD definition)
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Young adults/ Youths Ages 18-24
Seniors Ages 60 and older
Veterans Individuals who indicate they have served in any of the armed forces.
Specialized Services
On the morning of the general street-based count, specialized services were coordinated for children, youth and seniors determined to be in immediate need of assistance. Staff was on stand-by and ready to deploy from Operation SafeHouse and Adult Protective Services (APS). All volunteers received contact numbers and were instructed to call if they encountered a person in need of immediate assistance. .
1. If a youth under the age of 18 years old is identified, contact Operation SafeHouse at (951) 515-4614.
2. If you identify a senior who is over 60 years old or disabled adult AND is • Elderly/frail
• Having trouble ambulating/transferring/DME
• Lacks food/resources to buy food/water
• Appears to have chronic multiple medical needs but is not having acute episode requiring hospitalization or immediate medical care Contact the Adult Services Hotline at 1(800) 491 -7123. Be prepared to provide a thorough description of the client such as clothing, location and contact number if available.
3. If unable to obtain assistance at the numbers provided call the Point-in-Time Count Hotline at (951) 358-3844
Veteran Services Coordination Plan
The veteran services coordination plan has been a component of the homeless count for several years.
The veteran plan takes advantage of the broad range of programs, services, and resources available to veterans in Riverside County by connecting them to service providers on the day of the count. As a result of the COVID-19 pandemic, the 2022 count did not include the veteran services coordination plan.
Instead, client information was collected, and their information was shared with an appropriate service provider.
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STRATEGIES AND METHODS
Avoiding Duplication
Whether the count takes place in a single day or over multiple days, strategies for identifying and eliminating double counting are important to the accuracy of the Point-In-time Count (PITC). Using a `blitz’ approach to the street count helps to limit the potential for interviewing someone more than once. Some activities of the PITC, however, occur on more than one day.
Strategies for managing data collection included the following methods to avoid duplication of data:
1) The survey instrument and interview incorporated
screening questions to avoid duplication. After
greeting the individual, interviewers asked if they had already been asked questions about where they
stayed during the night. After confirming the person
slept in a location that qualified them as homeless, a
verbal interview collected the survey data.
2) For data collection, survey teams were assigned to
conduct the count and survey in specific geographic areas, on a designated date and time.
3) Using electronic devises with geolocation capabilities and survey start and end times enhanced the ability to identify potential duplication of files.
4) The survey information was used to generate a unique identifier for each survey and respondent.
Records for persons who were contacted and refused to be interviewed also included a unique identifier and were further designated in the data as observed rather than interviewed.
5) The survey instrument also collected the surveyor’s name and contact information so that contact could be made if clarification was needed.
Identifying Potential Duplication
During collection, the raw data was aggregated using the ESRI ARC GIS Survey 123 platform which allowed for high-level data management at the individual record level. A unique identifier was created for every person, and for each record, the surveys were classified as either interview or observation based on how the information was collected, and specific data such as key characteristics of observed persons (such as tattoos or pets), and when and where the data was gathered. This data formed the foundation for the de-duplication of records.
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Although the interview process included questions to establish the respondent’s homeless status, and if they had already responded to the survey, individual records were reviewed to ensure the person’s responses qualified them as homeless, and they were in the bounds of the Riverside CoC geography. The review also provided an opportunity to identify inconsistencies in the individual record. Records for interviews and observations that fell outside the authorized PITC, such as those created when volunteers practiced using the survey tool, and records that indicated the person did not meet HUD’s homeless definition were excluded. The Riverside PITC gathered and retained information about persons referred to as ‘couch surfers’ who were temporarily housed with friends or others in the community. The survey captured these persons in the living situation field as ‘couch’ and records with this designation were excluded from the PITC count and the report to HUD.
Deduplication Process
A multi-phase deduplication process was applied to the records identified as potentially duplicated.
Unique identifiers, personal characteristics, time, date and location for data collection, descriptions in the records, and the name and contact information for the interviewer were used. Surveys were assigned a record number and household members were tied together by a global identification number. The project and global identification numbers were sorted, searched, and reviewed for possible duplication. A unique identity, generated from joining portions of data: initials of first and last name, age, gender, race, ethnicity, and birthplace also assisted in identifying duplicate records. Records subject to removal were reviewed by two people prior to removal. The ESRI Survey 123 platform eliminated the need for post-count data entry. The survey instrument indicated the GPS location of the surveyor’s mobile device and date and time the data was captured, providing a geographic location of where the survey took place. This offered another factor to assist in deduplication.
Ensuring Data Integrity
Ensuring data integrity was important to the accuracy of the PITC results. Data quality and deduplication verified:
o Persons included in the count were homeless per PIT count requirements o All persons identified as homeless in the PIT count were homeless on the night the CoC designated as its PITC date
o Persons identified as homeless on the CoC’s designated PITC date were not already counted o The internal logic of the data is sound. For example, a child who was 5 years old at the time of the PITC would not logically also be a parenting youth. The record would be flagged for additional review to determine if the record should be excluded in its entirety, or simply removed from analysis of certain fields.
The ESRI Survey 123 platform has logic built in to perform automated, ‘hidden’ calculations. For example, the form combined the answers from a subset of questions to determine whether the
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respondent met HUD’s definition of chronically homeless and calculated the result instantly as the survey is completed. These calculations allowed for real-time generation of such metrics as the count was taking place, enhancing efficiency, and reducing potential human error. The survey captured the name and contact information for each interviewer. Contact was made if there were questions or need for clarification of data.
Managing and Merging Interview and Observation Records
Variable names and parameters for interview and
observation records differed slightly but were comparable.
For example, interviews captured the actual age of the
person in years on the day of the count and were
subsequently clustered into the age groups needed for HUD reporting (children under 18, youth 18-25, adults 25+).
Observation records collected age in the age ranges of the clusters based on the appearance of the person (child under 18, young adult under 25, and adult over 25). The age data was merged into the age ranges for analysis, but the actual age data was retained for the interviewed persons. The gender variable was treated similarly.
For the housing situation on the night of the count, interview records collected the person’s response while the observed records reported where the individual was seen, for example, under the bridge. For the data collected by observation, the surveyor also classified the level of confidence about the person’s homeless status. ‘Definitely homeless’ was the determination for over 75% (649) of persons. For cases where the surveyor did not assign a ‘definitely’ homeless classification, the record was reviewed to ensure the data placed the person as sleeping in an area not intended for human habitation on the night of the count.
Validity, Reliability, and Confidence in the PITC
Validity and reliability are foundational concerns in research and data analysis. » Did the variables measure the condition intended?
» Would the results likely be consistent if the count was repeated? » How do we know that the people counted or interviewed represent the homeless population overall?
The Riverside County PITC gathered data from the entire population. To accomplish this, the PITC engaged in multiple methods for identifying persons who were homeless, canvassed the entire geographic area, and invited everyone contacted to complete a standardized survey with trained survey- takers.
Page | 37
What were the results of the effort to gather data from each person living in homelessness in the region on the PITC date? Apart from one small area closed due to hazardous road conditions, the 2022 PITC unsheltered count canvassed the entire geographic area, and the sheltered count drew data for all sheltered persons meeting the HUD definition from the centralized HMIS database. The survey design and HMIS both included data to validate a person as homeless under the HUD definition. The sources of data included 1336 HMIS records each with verified homeless status (40%), 1119 unsheltered interviews screened to ensure they met the HUD definition (34%), and 861 observations (26%), for a count of 3316.
Observation was reserved for use when the individual being approached declined to be surveyed, or it was dangerous or infeasible to contact a person who was visible. In each case where observation was used, the surveyor was asked the reason that it was being used, and the level of confidence that the person was homeless. Of the 861 observations, surveyors assessed 649 as ‘definitely’ homeless and sleeping on the street or in a place not meant for human habitation. This means that 88% of the count was verified as part of the population with potential error at 12%.
For the personal characteristics associated with the individuals in the PITC, the level of confidence and margin of error differ from the overall population count. Because the PITC intended to represent the entire homeless population on the date of the count and not a random sample that is often assumed in statistical calculations, the 3316 was assumed to be the full population and the 861 a sample. Statistical testing of some key variables (age, race) yielded a confidence level of .77564, meaning that there is 78% assurance that the data represents the population.
RESULTS
For the 2022 PITC, the CoC lead agency HWS partnered with Urban Initiatives to analyze, summarize, and report the 2022 PITC data. To assess trends in the homeless count and to help the community to better understand homelessness, the data is presented in a variety of ways: across time, for individual cities and supervisorial districts and for selected groups: Families, Youth, Seniors, and Veterans.
Overview of Unsheltered Homeless
Community response to the pandemic altered conditions, such as emergency shelter resources, street outreach, attention and response to healthcare needs, and the availability of walk-in services such as pantries in the community. The results of the 2022 count saw some potential impacts: a substantive increase (83%) in sheltered homeless, a decrease in unsheltered homelessness (8%), and possibly a high level of family disruption identified as the cause for street homelessness. Family disruption was more than double the other contributing factors. Further research would be required to validate whether the households were disrupted by COVID-mandated quarantine or isolation, and access to support from family and friends. 3316
Total Count
1980
Unsheltered Count
1336
Sheltered Count
Page | 38
2022 Overall Numbers and Trends
The total of 3316 persons enumerated in the 2022 PITC included 1336 sheltered identified in HMIS records and 1980 persons identified by the activities of the unsheltered count: street and Service-Based Counts, rural outreach, and magnet events.
The 2022 PITC gathered unsheltered data through 1119
interviews and 861 observations totaling 1980 persons.
The 1980 unsheltered persons counted included: 150
seniors ages 60 or above, 9 families with a total of 29 persons (eleven children under the age of 18; three
youth ages 18-24; 14 adults ages 25+; and one unknown
age) as well as 237 transitional age youth. This is a
decrease of 8% in unsheltered persons when compared
with the 2155 unsheltered persons counted in 2020.
The trends in total count from 2015 – 2022 and the
change in total unsheltered differ as the graphs show. The depiction of the overall count number (3316) shows the
substantive increase between 2020 and 2022 while the
change in total unsheltered graph shows the decrease in unsheltered numbers. Together this means that while the number of homeless grew overall, the increase was in the sheltered population (83%), not the unsheltered group
(8% decrease). These trends reflect other community
changes such as increased shelter capacity and particular investment in addressing the needs of unsheltered
persons during the COVID-19 pandemic.
-500
0 500
1,000
1,500
2,000
2,500
2015 2016 2017 2018 2019 2020 2022*
Change in Total Unsheltered
2015-2022
0 1,000
2,000
3,000
4,000
2014 2016 2018 2020 2022 2024
Trend in Total Homeless
Persons 2015-2022
Page | 39
Demographics and Characteristics of
Unsheltered Persons
The count assessed the age, race, gender,
ethnicity for each person and captured other
information to help understand and respond
to the conditions and needs of the group, such
as household type, personal challenges and
barriers, factors contributing to their
homelessness, living situation, veteran status,
former incarceration, foster care experience,
first time homeless status, and pet ownership.
1 The racial distribution of unsheltered homeless
persons in 2022 was 54% White, 13% Black/African
American/African, 10% Multiple-Races, 3% American
Indian/Alaskan Native/Indigenous, and 1% each for
Asian/Asian American and Native Hawaiian/ Pacific Islander.
The prevalence of White, Black, and Multiple-Races over other races was seen in many of the unsheltered count
results. It is also noted that the Multiple-Races category included a few responses incorporating White or Black as part of the described races, driving the prevalence higher.
The ethnic and gender makeup of unsheltered homeless persons revealed that less than one-third of group was comprised of women (25%) and of Hispanic/ Latino(a) (x) (30%).
3%
1%
13%
1%
10%
54%
0% 20% 40% 60% 80%
American Indian, Alaskan…
Asian, Asian American
Black, African American,…
Native Hawaiian, Pacific…
Multiple Races
White
2022 Unsheltered Homeless
Race
%
30%
47%
24%
2022 Unsheltered - Ethnicity
Hispanic NonHispanic Unknown Ethnicity
66%
25%
0%
0%
0%
9%
0% 50% 100%
Male
Female
Transgender
Questionining
Gender Non-Con
Unknown Gender
2022 Unsheltered - Gender
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Challenges and Barriers
The unsheltered survey included questions about the challenges and special conditions that could impact the ability to gain or remain housed. Substance abuse (21%) and mental health issues (15%) were among the most prevalent characteristics in the challenges and barriers for unsheltered persons.
Compared to the 2020 PITC, mental health issues declined by 20% and substance abuse dropped by 6%.
These factors also decreased by 14% and 11% respectively in the full PITC count. The most frequently cited factor contributing to homelessness reported by the unsheltered group was family disruption (33%), followed by a lack of income (16%), unemployment (11%), substance abuse (8%) and a collection of other factors such as fire and relationship breakup (16%). Combining the challenges and the factors contributing to homelessness points to the complexity in understanding the characteristics of unsheltered homeless persons, and the planning of interventions that are needed to resolve their homelessness.
SUB-POPULATION REPORTS
Families with Children
Although the number of unsheltered households with at least one adult and one child under age 18 (families) rose by 50% between 2020 and 2022, it was the smallest identified group of interest in the unsheltered PITC. While the full sheltered and unsheltered PITC found 490 persons living in families, only nine (9) households with 29 persons were identified in the unsheltered group in 2022. These households included eleven (11) children under the age of 18, three (3) youth between ages 18 through 24, and fourteen (14) adults who were predominantly non-Hispanic/Latin(o), (a), (x) (72%) and predominantly male (55%).
Racially, the family members mirrored the distribution
of other groups in the PITC, with prevalence to White
(66%), Black/African American/African (21%), Multiple-
Races (10%) and in this case, a small percentage of
Native Hawaiian. The families spent the night in tents or sheds, vehicles, or abandoned buildings. Family
disruption was the most frequently reported contributor to homelessness (41%) far outweighing ‘other’ as the
second factor (9%).
Families were challenged by substance abuse (9%) and PTSD (9%), and chronic and mental health issues, HIV/AIDS, and developmental disability all reported equally (5%). This is a first experience in homelessness for almost one-third (32%) of the group.
Page | 41
Youth (18-24)
Understanding and solving youth homelessness is a focus for the Riverside Count CoC. Overall, the trend in the number of homeless youths was relatively stable between 2017 and
2019 (178-181), then rose by over 41% in 2020 before
dropping by 7% to 237 in 2022.
The Riverside PITC was able to gather data on 234
unaccompanied youth and three youth identified as part of family households, for a total unsheltered count of 237. An additional 75 youth were housed in emergency or transitional shelter. The sheltered group includes two (2) youth parenting households, while the unsheltered group included six (6) pregnant youth. When compared with the characteristics of youth in the national initiative, the description of youth in the Riverside CoC revealed both similarities and differences. Of the 237 unaccompanied youth contacted during the PITC, 40% refused to be interviewed; 33% were living on the street and 25% in vehicles.
Youth reported the top factors contributing to their
homelessness as family disruption (45%), runaway
(12%), lack of income (10%) and substance abuse (10%).
Their responses to their challenges and barriers,
however, showed 33% with mental health issues, 32%
with Post-Traumatic Stress, and 23% with substance
abuse. None of the youth reported being engaged in sex
work. Participation in education for youth in the
Riverside PITC showed 56% completing a High School
education (52% completing the 12th grade and 4% achieving a GED) and 10% completing some college. Nearly one in four (22%), however, indicated that they only completed some High School.
With respect to contact with systems of care, 33% reported placement in foster care. 6% reported experiencing
domestic violence and 54% were experiencing homelessness for the first time. Although there were no parenting youth among the unsheltered group, 6 females reported being
pregnant.
The PITC survey asked if youth needed information or services. Of the 1,119 interviewed unsheltered individuals, 558 (49%) provided their contact information, agreed to have their information shared with 106
178 177 181
256 237
0 100
200
300
2016 2017 2018 2019 2020 2022
Unsheltered Youth
9% 4%
22%
1%
52%
1% 10%
0 10
20 30
40 Last Grade Completed -
Youth
Where Youth Slept the Night
Before the Count (interview only)
Living Situation # %
Abandoned Building 5 7%
Encampment 8 12%
Park 2 3%
Street 22 33%
Tent Shed 5 7%
Under Bridge 1 1%
Vehicle 17 25%
Other 8 12%
Page | 42
a service provider, and selected the types of services needed. A total of 20 youth (18-24) interviewed provided their contact information for follow up care. Services identified by youth included health and medical care, food pantries in the community, substance abuse services, help with couch surfing, legal assistance, foster care assistance, and animal or other services.
Seniors (60+)
Homeless seniors, age 60+, are a focus of the
Riverside County CoC. The 2022 PITC identified a
total of 150 unsheltered seniors throughout the
region. When compared with the senior count of
175 persons (60+) in 2020, the 2022 PITC of 150
showed a decrease in senior homelessness of 14%
(25).
The percentage of first time homelessness among
seniors was 29% and seniors represented
approximately 10 % (44) of the persons known to be
homeless for the first time.
Veterans
The general trend in the number of unsheltered
veterans between 2016 and 2022 showed a slight decrease in 2017 and 2018 followed by a steady incline from 2019-2022, with a 31% decrease between 2020 and 2022. The percentage of veterans in the unsheltered population, however, remained low at 4% (77). Only 49 veterans were housed in emergency or transitional housing 4% of sheltered count. The total veteran group (126) was only 4% of the total count (3316).
Unsheltered veterans were similar in race and ethnicity to other groups. The largest proportion was non- Hispanic (75%), White (49%) followed by Black/African American (25%) and Multiple-Races (10%).
One difference is the proportion of American Indian/Alaskan Native/Indigenous people who comprised 8% of unsheltered veterans.
Hispanic
25%Non-
Hispanic,
75%
2022 Veteran Ethnicity
100 91 99 107 112
0 77
0 50
100
150
2016 2017 2018 2019 2020 2021 2022
Unsheltered Veteran
2016 - 2022
Seniors (60+) Characteristic (unsheltered) %
First Time Homelessness Among Seniors 29%
Challenges and Barriers
Chronically Homeless 51%
Mental Health Issue 21%
Physical Disability 34%
Substance Abuse 27%
Ethnicity
Hispanic, Latin(o), (a), (x) 31%
Gender
Male 77%
Living Situation – Night Before the Count
In vehicle 31%
Street 27%
Tent/Shed 14%
Pet Owners 17%
Factors Contributing to Homelessness
Lack of Income 28%
Family Disruption 21%
Unemployment 14%
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First Time Homeless
People falling into homelessness for the first time is a group of interest to the Riverside County CoC with 423
first time unsheltered homeless persons counted during
the 2022 PITC, a 13% decrease when compared with
the 2020 PITC report of 485 newly homeless. The data
for first time homeless persons in 2022 showed some
measures worth noting. The chart to the right
summarizes some of those characteristics.
Adults aged 25-59 comprised the largest portion (81%)
of the persons counted in the PITC with seniors (60+)
comprising 10% and Youth (18-24) another 9%.
Veterans represented 4% of the overall PITC, and 4% of
the unsheltered count but 5% of the first time homeless group. Substance Abuse (33%), Post-Traumatic Stress
Disorder (26%), Mental Health Issues (25%), and
Chronic Health issues (20%) ranked in the top four
challenges and barriers for persons experiencing
homelessness for the first time. By looking at the
percentages, it is apparent that persons entering
homelessness for the first time may have co-occurring
challenges and barriers.
With respect race and ethnicity, the racial distribution pattern of predominantly White, Black/African American/African, and Multiple-Races comprising over 80% held for first time homeless who measured 57%, 13% and 12% respectively. There was, however, a slightly higher percent of American Indian/ Alaskan Native/ Indigenous people among the first time homeless (4%) compared with the total unsheltered group (3%). For ethnicity, 47% first time homeless were identified at Hispanic/Latino (a) (x) as compared to 30% of the full unsheltered group. 47%
52%
1%
First Time Homeless - Ethncity
Hispanic Latino (a) (x) Non- Hispanic,Latino
Unknown
Characteristic
% of First Time
Homeless
Age
Adults (25-59) 81%
Seniors (60+) 10%
Youth (18-24) 9%
Veterans 5%
Challenges and Barriers (top 4)
Chronic Health Issue 20%
Mental Health Issue 25%
Post-Traumatic Stress Disorder 26%
Substance Abuse 33%
Hispanic, Latino (a) (x) 47%
Male 70%
No Single Gender (4) 1%
Living Situation (top 3)
On street 28%
In vehicle 18%
In Encampment 17%
In a tent or shed 17%
Pet Owners 17%
Reasons Contributing to
Homelessness (top 3)
Family Disruption 30%
Lack of Income 20%
Unemployment 10%
4% 12%
2%
13%
11%
1%
57%
First Time Homeless - Race
AmericanIndian MultipleRace Asian
Black Unknown NativeHawaiian
White
Page | 44
Where first time homeless persons were living at the time of the count was relatively dispersed in comparison with other subgroups. The largest portion of first time homeless were found on the street (28%), with dwelling in vehicles,
encampments, or tents or sheds holding nearly equal
portions (17%-18%). Reasons identified as contributing to homelessness among first time homeless persons included family disruption (30%), lack of income (20%) and
unemployment (10%).
One striking feature of the first time homeless group was gender. While the gender makeup of 70% male and 29%
female was like that seen in other subgroups, the four (4) persons (1%) identified as ‘no single gender’ comprised one of the highest concentrations of that gender classification in any group in the PITC, representing over 36% of all persons self-identifying as no single gender.
Chronic Homelessness
In the 2022 PITC, chronically homeless persons
represented 28% of the unsheltered group, 19% of
the sheltered population overall, and 25% of the
total PITC.
Geographic distribution of unsheltered chronically
homeless persons shows that although the range
for number of chronic persons in geographic district
subregions is relatively broad (72 to 162), the
percentage of chronically homeless persons among the unsheltered group in each district tends to be about one-third.
The racial distribution of unsheltered chronically homeless persons was like that of other groups with White (65%), Black/African American/African (12%) and Multiple-Races (12%) categories dominating. In this case, American Indian increased to 5% as compared with the 3% of the overall unsheltered population.
299 341 387
727
519 560
0 200
400
600
800
2016 2017 2018 2019 2020 2022
Unsheltered Chronic Homeless
2016-2022
Page | 45
Formerly Incarcerated
A history of criminal activity and release from jail or prison can be a barrier to housing. A total of 209 unsheltered persons interviewed indicated they had been in jail or prison (19%). The PITC formerly incarcerated unsheltered count demonstrated a higher number of Whites (130, 62%), exceeding Black and Multiple-Races combined (50, 23%). The age distribution of formerly incarcerated persons was as expected, vastly adults ages 25-59 (89%) and seniors (60+) (5%) with remaining 6% among youth ages 18-24.
Couch Surfers
Although not part of the official PITC count, data was
collected on couch surfers, expecting to find many
youths in that living situation. The couch surfer results were somewhat unexpected, and provided new insight
on 31 persons, including 12 youth, who were housed in
that situation.
Individuals who reported sleeping on a couch on the
night of the count are not part of the PITC numbers or
the unsheltered count analysis. Sleeping on someone’s
couch does not qualify as being homeless under HUD’s
definitions for the CoC program. Often, however,
these arrangements are temporary or could change at
any time, sending the person into homelessness.
Prevention of homelessness and rapid resolution of
homelessness are keys in helping to reduce or end
homelessness. Understanding persons living in
situations that places them of being at-risk of
becoming homeless is important to effective, early
intervention. Although not included in the official PITC report to HUD, the Riverside PITC gathered
information from the 31 people who declared they
stayed on someone’s couch on the night of the count.
Anecdotal information might lead a community to
assume that couch surfers are predominantly youth
under 25 years of age. The 2022 PITC, however found
adults comprising the largest portion of couch surfers.
Other demographic information and characteristics
associated with the “couch-surfers“, is described on
the table to the right.
10%
39%42%
10%
COUCH SURFERS AGE GROUP
Child<18
Youth (18-24)
Adult >25 <60
Senior 60+
UNSHELTERED COUCH SURFERS
Special Interest Questions # %
Families with Children 1 3%
Chronically Homeless 13 42%
Veterans 3 10%
Gender # %
Female 9 29%
Male 21 68%
Transgender 1 3%
Challenges / Barriers # %
Chronic Health Issue 3 10%
Domestic Violence 2 6%
HIV AIDS 0 0%
Mental Health Issue 11 35%
Physical Disability 7 23%
Post-Traumatic Stress 7 23%
Substance Abuse 9 29%
Traumatic Brain Injury 3 10%
Developmental Disability 6 19%
Page | 46
The age results for couch surfers were not expected. Couch surfing may generate a picture of a teen youth ‘crashing’ on a couch and moving from one friend’s house to another. The picture painted by the data in Riverside, however, showed adults between the ages of 25 and 59 as the largest group (42%), followed closely by youth ages 18-24 (39%), included children under 18 (10%), and seniors age 60+ (10%). Even combining youth and children into one cluster (49%) and adults including seniors into another, the adult group is slightly larger (52%).
Couch surfers identified through the count were
predominantly male (68%) and White (42%). They
differed from other groups with a substantially
higher number of individuals who were Hispanic
(71%). More than a third (39%) reported being
homeless for the first time. Veterans comprised 10%
of the couch surfing group. Like many unsheltered
counterparts, family disruption was the most
frequently cited factor for not being stably housed
(45%). Lack of income (13%) and in this case,
runaway status (3%) ranked in the top three causes.
Other contributing factors were house fire, kicked
out of house, and failed marketplace housing. To
remain in their couch surfing location, 13% had to contribute financially and 6% had to do work or help with household chores. Couch surfers report a higher incidence of mental illness (35%), foster care experience (23%), and domestic violence (6%) than other groups. Unsheltered count sub-population summary tables can be found in Appendix A.
More Than a Count Initiative Outcomes
The PITC survey asked if there was information or services the person needed or would like help with.
Of the 1,119 interviewed unsheltered individuals, 558 (49%) provided their contact information, agreed to have their information shared with a service provider, and provided the types of services needed.
Housing was the most frequently identified need, followed by equal requests for behavioral/mental health services, mainstream resources (CalFresh, Cash Aid), and help obtaining documents.
Teams successfully connected with 92 or 16% of the 558 individuals requesting follow-up. Of those, 23 were no longer interested in receiving services and an additional 18 individuals reported they were already connected to a community service-provider.
Page | 47
The following provides additional information about the outreach efforts:
Services and Linkages Housing and Housing Services
35 individuals received assistance 4 individuals received assistance o Completed VISPDAT*
o Mental health services
o Employment seeking assistance and employment referrals o Obtain essential documents Transportation assistance
o Food and beverages
o Backpack, sleeping bag, and clothing
o Hygiene items
• Temporary shelter
• Section 8 application
• Emergency Housing Voucher (EHV)
application
• Shelter Referral
• Enrolled to CES
*Assessment used by Riverside County to prioritize individuals for housing assistance through a Coordinated Entry System called HomeConnect
Outreach teams reported the following challenges when conducting follow-up:
• The nomadic nature of the unsheltered population made it difficult to find them in the same location they were in during the count.
• Possible street sweeps affected the ability to find individuals in the same location. • Because outreach teams are already conducting street outreach, they were able to locate individuals.
• Teams had limited success due to lack of trust (persons did not answer their phone or returned phone calls).
• If email was the only way to contact a person, an email response from the unsheltered individual took several weeks.
• Most individuals do not use their legal name when living on the street. In some instances, it was difficult to find persons using the proper name they provided. • When reaching out to LGBTQ+ clients, outreach teams encountered challenges since some individuals were not out to their family and/or friends and did not return calls because an LGBT organization was reaching out.
• Homeless youth move around a lot and are difficult to follow up with. • Homeless youth experiencing housing instability will ask for assistance when they do not have a place to stay, but if they find a place to stay, even if only temporary, they may stop searching for or accepting services.
Outreach teams also reported positive outcomes:
• The geolocation mapping feature was helpful in locating individuals. • Outreach teams were made aware of new encampments or areas they had not previously canvased
Page | 48
Specialized Services Plan Outcome
On the morning of the count, Operation Safe House and the County’s Adult Protective Services (APS) were on stand-by for immediate response if volunteers encountered a youth or senior in need of immediate assistance. Operation Safe House did not receive any requests for immediate response. Volunteers did contact the APS hotline to refer 13 individuals identified as homeless seniors (60+) in need of immediate assistance. APS staff was deployed to locate and connect with the individuals.
CONCLUSION
General Discussion
The 2022 PITC established a strong, comprehensive platform for enumerating homelessness. Future counts can build on the experience of 2022 to enhance the “engaged count” approach in future years.
Although there is an overall increase, the Riverside County CoC Point-in-Time Count data indicates progress in stemming the tide of homelessness in several areas: A decrease in unsheltered homeless persons, an increase in sheltered chronically homeless, and substantial decline in victims of domestic violence overall. Moving homeless persons from the streets and other places not meant for human habitation into shelter or housing is a fundamental goal expressed by the U.S. Department of Housing and Urban Development (HUD) and a general desire for communities in Riverside.
While reducing chronic homelessness is a core component of national goals, alleviating homelessness among other groups can also help reduce homelessness overall, and intervene with persons who might otherwise become chronically homeless. The Riverside CoC hosts 560 chronically homeless unsheltered persons but there are several subgroups with smaller populations living unsheltered: pregnant youth (6); families (9 households); seniors (150 individuals); and youth (237 unaccompanied youth). Innovative strategies for resolving homelessness among these groups could bring each group to ‘functional zero’ where no more enter homelessness than exit to permanent housing.
Similarly, consider addressing the ‘pockets’ of unsheltered homelessness in geographic areas with low numbers but experienced an increase between 2020 and 2022, such as Eastvale (6, 50% increase in unsheltered), La Quinta (7, 133%), and Wildomar (7, 17% increase). Intervention in these geographies could prevent further growth in unsheltered persons for 2023.
In general, the Riverside County CoC should work to sustain trends for unsheltered groups that decreased 2020 - 2022, such as substance abuse and mental health issues and continue to focus on ending veteran and youth homelessness.
o 8 – unable to located
o 1 - sheltered in a motel
o 1 - placed in an
emergency shelter
o 2 - chose to stay in
vehicle
o 1 - chose to remain in
encampment
Page | 49
Additional Strategies/Actions
The data and additional information collected points to areas in need of further exploration, such as:
• Explore family disruption as the factor most frequently cited as contributing to homelessness. • As expressed as a need by surveyed youth, explore couch-surfing as a resource (host homes for example).
• Examine the data for couch surfers to better understand how this type of housing could be incorporated into prevention or diversion strategies.
• Work cooperatively to address the need for ID, and other documents required to qualify for assistance.
• Create options for pet care associated with shelters and housing, removing pet ownership as a barrier.
PIT COUNT PLANNING RECOMMENDATIONS
General Count Recommendations
RECOMMENDATION 1: Create a CoC PIT Count Committee
The CoC PIT Count committee can:
• Organize community planning meetings
• Ensure accountability in the PIT Count process
• Increase CoC member and community partner involvement • Provide regular updates and request approvals (as needed) from the CoC and Board of Governance
• Keep PIT Count activities moving by assigning leadership roles
RECOMMENDATION 2: Increase CoC Member Involvement
• Engage CoC funded & ESG projects early and encourage their collaboration by taking on lead planning and implementation roles in their communities
• Delegate leadership positions to CoC partners at planning meetings
RECOMMENDATION 3: Improve Volunteer Management Tool
• Automate volunteer registration confirmations, updates, and deployment site assignments
• Improve registered volunteer experience by providing instant notifications of time-sensitive information
• Track volunteer activities and create reports
RECOMMENDATION 4: Increase Participation of Previously or Currently Homeless Individuals to:
• Increase opportunities for homeless or formerly homeless persons to participate as interviewers in the count (potentially reducing the number of interview refusals)
• Assist in identifying known locations/hot spots
Page | 50
• Assist as volunteer as guides
• Advise on survey questions
RECOMMENDATION 5: Housing and Services Linkages Initiative • Linkages need to happen on the day of the count
• Find confidential way of asking individuals who identify as LGBTQ+ who they are out to in their family or on the streets
• Collect legal name and nicknames of individuals to make it easier for outreach teams to locate
RECOMMENDATION 6: Shelter Count
• Explore characteristics in sheltered population via HMIS records to be able to paint a more detailed understanding of sheltered homeless persons
YOUTH COUNT PLANNING RECOMMENDATIONS
RECOMMENDATION 1: Youth Count Coordinator and Advisory Committee The Youth Count requires a full-time coordinator experienced in conducting local homeless youth outreach and who is knowledgeable about the needs of this population. The Youth Coordinator will:
• Ensure timely planning and community involvement
• Assign lead roles to key community partners and schedule/map locations
• Offer guidance about incorporating youth in the count
• Develop a youth-informed mapping tool to identify both hotspots and canvassing areas
RECOMMENDATION 2: Involve Youth
• Hire youth who have lived experience with homelessness
• Continue to provide incentives that are useful to youth (e.g., phone chargers) in addition to water and handouts currently distributed
• Youth can serve as guides to find and engage youth and assist in creating mapping tool
• Collaborate with participating youth service providers to bring youth from their respective program to planning meetings and on the day of the Youth Count
• Provide stipends or compensate youth for participating in Youth PIT Count planning and on the day of count activities
RECOMMENDATION 3: Engage Key Stakeholders (currently underused) • LGBTQ Partners and Community
• Colleges and Universities
• County Library System
• School Districts and School Homeless Liaisons
Page | 51
RECOMMENDATION 4: Recruit and Properly Incentivize Youth Friendly Volunteers • Increase opportunities for homeless or formerly homeless persons to participate as interviewers in the count (potentially reducing the number of interview refusals)
• Engage youth/peer leaders at Behavioral Health Transitional Age Youth Clinics (five in the County), many who are recovering from homelessness, addiction, or mental health issues
• Continue to engage youth at the Youth Opportunity Centers (YOC). The YOC’s are one stop centers that provide services and support to youth ages 16 – 24.
• Effectively train youth volunteers in the proper engagement of their peers
RECOMMENDATION 5: Expand Coverage
• Track outreach data frequently (at least monthly) to identify new ‘hotspots’ as they develop
• Continue use of technology with GIS capabilities for the unsheltered count
• Go beyond only canvasing hot spots
• Identify homeless youth that are disconnected/ not engaged in services
• Consider incentivizing youth for bringing other youth to be counted
• Continue to collect information about youth who are couch surfing or are doubled-up
RECOMMENDATION 6: Improve Youth Volunteer Training
• Include time to review the survey with volunteers to familiarize them with questions • Allow volunteers to practice conducting surveys and practice roleplaying in training. Provide an opportunity for youth volunteers to practice best and worst-case scenarios
• Allow volunteers to practice approaching and engaging youth
• Ensure that all youth volunteers understand effective street outreach strategies and where to draw the line between case management and linkages to care/services
RECOMMENDATION 7: Youth Homelessness Awareness
• Continue use of magnet events for youth
• Promote National Homeless Youth Awareness Month (in November) to increase community involvement in the Youth PIT count
• Promote the needs of TAY Youth including the need for youth shelters
• Provide educational workshops regarding TAY youth development issues to increase service provider involvement
Page | 52
LIMITATIONS
Despite the enhanced efforts to improve the accuracy of the count, the actual number of individuals and families experiencing homelessness is estimated to be higher than PIT Count results, especially in the Youth Count. The following are Point-in-Time Count limitations to consider:
The PIT Count is a snapshot of the number of homeless people counted at one point in time.
The count does not completely capture the entire number of the unsheltered homeless population in any community, nor does it fully explain why people are homeless in a particular area.
On-going challenges of locating homeless individuals. Many more individuals experience homelessness during the year than on the night of the count. The nature of unsheltered individuals is that they move around a lot, may be in and out of homelessness during the year, and others may conceal their housing status due to the stigma associated with being homeless or due to law enforcement. Site leads indicated that extreme weather conditions in Riverside County, throughout the morning of the count, impacted counting efforts. To ensure an accurate count, outreach teams were deployed to revisit some missed areas in specific cities.
Not all homeless individuals engaged on the day of the count agree to be interviewed.
Volunteers reported that they arrived at an empty encampment site when it was evident that many people were living there.
Counting youth is even more challenging compared to the overall population resulting in a significant under representation of homeless youth. Youth may not consider themselves homeless and may not access homeless services making it more difficult to locate them. There is still limited participation from public schools, colleges and universities, LGBTQ, foster youth, and other youth service providers.
Youth PIT Count results continue to be limited by not being able to coordinate with the homeless liaisons in the school districts. This is a federal advocacy issue where McKinney-Vento programs should be an active participant in Youth PIT Counts.
Despite its shortcomings, the PIT Count provides communities an annual opportunity to focus collectively on the presence of homeless people in their communities, and document this need.
Page | 53
ACKNOWLEDGEMENTS
The CoC PIT Count Planning team would like to express gratitude to the people in our community, network of non-profit organizations, faith based-communities, cities, county staff (including homeless outreach teams), and law enforcement partners for their relentless support and participation in the 2022 PIT Count and Survey.
The CoC PIT Count Planning team extends their gratitude to the 719 volunteers who gave their time volunteering on the day and week of the count. Conducting a full-count in the fourth largest county in California, by size during the COVID-19 pandemic and under tough winter-storm conditions is no small endeavor. Thank you to all participants for your commitment and support of the Riverside County Homeless Point-in-Time Count.
We would like to acknowledge the guidance and support received from the Board of Supervisors and District Legislative Staff and Assistants.
Supervisor Kevin Jeffries,
First District
Jeffrey Greene
Kerstin Justus
Robin Reid
Chief of Staff
Legislative Assistant
Legislative Assistant
Supervisor Karen Spiegel,
Second District
Philip Paule
Debbie Rose
Liliana Allin
Chief of Staff
Legislative Assistant
Legislative Assistant
Supervisor Chuck Washington,
Third District
Joe Pradetto
Sundae Sayles
Robyn Brock
Claudia Maunz-McLellan
Chief of Staff
Legislative Assistant
Legislative Assistant
Legislative Assistant
Supervisor V. Manuel Perez,
Fourth District
Steven Hernandez
Greg Rodriguez
Margarita Felix
Chief of Staff
Legislative Assistant
Legislative Assistant
Supervisor Jeff Hewitt,
Fifth District
Boomer Shannon
Stephanie Garthwaite
Amber Smalley
Katrina Cline
Chief of Staff
Legislative Assistant
Legislative Assistant
Legislative Assistant
“Volunteers do not
necessarily have
the time, but they
do have the heart!”
Page | 54
A special thanks Operation Safehouse for serving as the lead agency for the Homeless Youth Count. Thank you to AJ Vasquez who coordinated the Youth PIT Count and demonstrated commitment and dedication to executing an accurate youth count.
Thank you to Rainbow Marler, the youth count deployment site leads and the entire Operation Safehouse street outreach team.
Thank you to Dr. Jennifer Chevinsky and Barbara Cole from the County of Riverside Department of Public Health who shared their expertise and knowledge about implementing an unsheltered homeless count in the middle of a pandemic.
A sincere thank you to Nathan Cheung, Bethany Balisky and Riverside County Information Technology (RCIT) for their assistance in creating and publishing the survey tool and the MoreThanACount.org website.
We would like to acknowledge the assistance of the Department Public Social Services (DPSS) and their team of Public Information Specialists who assisted in promoting the homeless count in the community, creating highlight videos, press releases, podcasts, social media tool kit, and promotional materials.
• Kimberly Trone
• Gene Kennedy
• Angela Naso
• Leslee Abrego
• Alyssa Garcia
• Chelsea Godfrey
• Tina Bellanger
A special thanks to Brook Federico and her team from the County Executive office for their assistance with media and community engagement.
City and law enforcement leaders were vital to the success of this year’s PIT Count. They were involved in all aspects of the planning, coordination, and implementation of the street-based count in their respective cities. City and deployment site leaders also increased homelessness awareness by recruiting volunteers and promoting the PIT Count in their community. Volunteer and staff were appreciative to have law enforcement presence. PIT Count deployment site leaders did a phenomenal job coordinating all count-related activities.
We want to acknowledge the support and partnership with the Urban Initiatives team that led the data analysis and development of the 2022 PIT Count Data report.
Dr. Pat Leslie Dr. Joe Colleti Dr. Deme Hill
Page | 55
City/Community Key Leader(s) Deployment Site
Banning
City of Banning
Roman Ruiz
Ralph Wright
Officer Christopher Sayeski
Banning Police Department
Banning Senior Center
Beaumont
City of Beaumont
Sergeant Christopher Ramos
Beaumont Police Department
Beaumont Police Department
Blythe
City of Blythe
Sergeant Troy Fabanich
Blythe Police Department
Behavioral Health – HOPE Team
Blythe Police Department
Blythe Police Department
Calimesa
City of Calimesa
Deputy Juan Cedeno
Riverside Sheriff’s Office
Calimesa City Hall
Canyon Lake
City of Canyon Lake
Riverside Sheriff’s Office
None
Cathedral City
City of Cathedral City
Officer Jeremy Powers
Officer Joseph Brooks
Cathedral City Police Department
Behavioral Health – HOPE Team
Cathedral City Police Station
Coachella
City of Coachella
Rene Rosales
Sergeant Matos
Riverside Sheriff’s Office
Coachella Civic Center
Corona
City of Corona
Denzel Maxwell
Lieutenant Chad Fountain
Sergeant Skip Shatford
City Net
Corona Police Department
Corona City Hall
Desert Hot Springs
City of Desert Hot Springs
Officer Christopher James
Desert Hot Springs Police
Department
Guy J. Tedesco Park (Henry V. Lozano
Community Center)
Eastvale
City of Eastvale
Eva Terekhova
Lieutenant Marc Boydd
Riverside Sheriff’s Office
City of Eastvale - Council Chambers
Page | 56
Hemet
City of Hemet
Veronica Allen
Lieutenant Eric Dickson
Sergeant Bryan Cunningham
City Net
Hemet Police Department
City of Hemet – Council Chambers
Indian Wells
City of Indian Wells
Kristen Nelson
Lieutenant David Wright
Riverside Sheriff’s Office
Palm Desert City Hall
Indio
City of Indio
Yanel Ramirez
Jesus A. Gomez
Sergeant Alex Franco
Indio Police Department
Coachella Valley Rescue Mission
Martha’s Village & Kitchen
Jurupa Valley
City of Jurupa Valley
Jose Ibarra
Officer Irwin Salas
Benny Zimmermann
Ryan Batista
Code Enforcement
Riverside Sheriff’s Office
Jurupa Valley City Hall
La Quinta
City of La Quinta
Martha Mendez
Sergeant George Acevedo
Deputy Maggie Lopez
Riverside Sheriff’s Office
La Quinta City Hall
Lake Elsinore
City of Lake Elsinore
Alexandra Teahen
Nicole Dailey
Sergeant Jeff Reese
Riverside Sheriff’s Office
Social Work Action Group (SWAG)
Lake Elsinore Cultural Arts Center
Menifee
City of Menifee
Jon Nicks
Sergeant Raul Perez
Police Chief Pat Walsh
Riverside Sheriff’s Office
Social Work Action Group (SWAG)
Kay Cisneros Senior Center
Page | 57
Moreno Valley
City of Moreno Valley
Launa Jimenez
Serina Astorga
Deputy Kimberly Mirabella
Riverside Sheriff’s Office
Cottonwood Golf Center
Murrieta
City of Murrieta
Brian Ambrose
Murrieta Police Department
Social Work Action Group (SWAG)
Murrieta Police Department
Norco
City of Norco
Alejandra Gonzalez
Michelle Anglin
Sergeant Aaron Avila
Deputy Rachell Whittenburg
City Net
Riverside Sheriff’s Office
Norco City Hall
Palm Desert
City of Palm Desert
Heather Horning
Code Compliance
Citizens on Patrol
Riverside Sheriff’s Office
Palm Desert Civic Center
Palm Springs
City of Palm Springs
Jay Virata
Denise Goolsby
Annie Rodriguez
Officer Frank Guarino
Officer Mike Kovaleff
Palm Springs Police Department
Palm Springs Convention Center
Perris
City of Perris
Sara Cortes de Pavon
Riverside Sheriff’s Office
Social Work Action Group (SWAG)
City of Perris Senior Center
Rancho Mirage
City of Rancho Mirage
Brian Kephart
Riverside Sheriff’s Office
Rancho Mirage City Hall
Riverside
City of Riverside
Janette Sanchez
Ali Hariri
Officer Chris Wagner
City of Riverside Access Center
City of Riverside Access Center
and
La Sierra University Church
San Jacinto
City of San Jacinto
Rene Yarnall
Rob Johnson
City Net
Riverside Sheriff’s Office
San Jacinto Community Center
Page | 58
Temecula
City of Temecula
Mike Wooten
Sergeant Edward Harding
Temecula Police Department
Social Work Action Group (SWAG)
Temecula HELP Center
Wildomar
City of Wildomar
Felicia Folmar
Sergeant Jeff Reese
Riverside Sheriff’s Office
Social Work Action Group (SWAG)
SWAG
County coordinators played a key role in the success of the homeless count. Thank you to all Housing and Workforce Solutions (HWS) and Department of Public Social Services (DPSS) staff for their time, energy, and dedication in their role as County Coordinators.
» Bobbi Bennett
» Jose Cano
» Jess Castro
» Joshua Coda
» Aden
Dalrymple
» Alexis Earkman
» Keiana Forbes
» Jamie Gibson
» Nolan Green
» Carlos Guerra
» Monique Guerra
» Cara Hander
» Brenda Hernandez
» Roberto Huesca
» Gordon Kuang
» Amparo Lopez
» Jasmine McNamara
» Abel Porraz
» Miguel Salgado
» Martha Samaniego
» Lindsay Sisti
» Amber Smalley
» Joshua Tomaszewski
» Brandon Trahan
» Selam Walker
» Raushanah Walker
» Melanie Wilson
» Gabriella Zafarana
A special thanks to the Riverside Sheriff’s Office (RSO) Homeless Outreach Team. Their committed participation in community planning meetings, coordination for the Unincorporated Area Count, and involvement of the count was invaluable.
Deputy Julia Cruz Deputy Julian Ramirez
Riverside Sheriff’s Office (RSO) Lead(s) Deployment Site Cabazon Station Deputy Cedeno
Deputy McConnell
Calimesa City Hall
Blythe Station Deputy Pfohlman
Cpl. Eckenrode
Blythe RSO Station
Hemet Station Deputy Enochs
Hemet RSO Station
Jurupa Valley Station Deputy Garcia Jurupa Valley RSO Station
Page | 59
Deputy Savage
Lake Elsinore Station Deputy Tran
Deputy McCracken
Lake Elsinore Cultural Arts Center
Moreno Valley Station Deputy Mirabella
Moreno Valley Cottonwood Golf Center
Palm Desert Station Deputy Nelson
Palm Desert City Hall
Perris Station Deputy Machado
Perris RSO Station
Southwest Station Sergeant Harding
Southwest RSO Station
Thermal Station Cpl. Quezada
Thermal RSO Station
We extend our appreciation to community agencies and their staff who generously set aside time to attend the volunteer training, an orientation or participate in a PIT Count activity to ensure full coverage existed every day across the county.
Addiction Therapeutic Services Coachella Valley Rescue Mission Medical Health Operational Area Coordinator (MHOAC)
Alternatives to Domestic Violence Community of Casa Blanca Molina Health Care Aspiranet Community Pantry NAMI Hemet/San Jacinto
AXIS Foundation County of Riverside Behavioral Health OakGrove Center Bank of America County of Riverside Board of Supervisors Office of Homeless Solutions California Family Life centers County of Riverside Code Enforcement Olive Crest CAREspace County of Riverside Department of Animal
Services Operation SafeHouse
Catholic Charities, Riverside County of Riverside Department of Behavioral Health Parks and Recreation
Central Neighborhood Health County of Riverside Department of Child Support Services Partners Against Violence
Citizen Advocates for Senior and
Homeless Solutions
County of Riverside Department of Mental
Health Path of Life Ministries
Citizens on Patrol
County of Riverside Department of Public
Social Services Planned Parenthood
City Code Enforcement
County of Riverside Department of Social
Services - Administration Queerworks
City Net County of Riverside Department of Social
Services - Adult Protective Services Rainbow Pride Alliance City of Banning County of Riverside Department of Social Services - Self Sufficiency Division RevComm Foundation City of Beaumont County of Riverside Emergency
Management Department Riverside Area Rape Crisis
City of Blythe County of Riverside Executive Office Riverside County Office of Education City of Calimesa County of Riverside Facilities Management Riverside County Office on Aging City of Canyon Lake County of Riverside First 5 - Family Resource Centers
Riverside County Probation
Department
City of Cathedral City
County of Riverside Housing and
Workforce Solutions (HWS) - Community
Action Partnership Riverside County Sheriff's Office
City of Coachella
County of Riverside Housing and
Workforce Solutions (HWS) - Continuum of
Care
Riverside County Youth Advisory
Council
City of Corona
County of Riverside Housing and
Workforce Solutions (HWS) - Housing
Authority
Riverside Life Services
Page | 60
City of Desert Hot Springs
County of Riverside Housing and
Workforce Solutions (HWS) - Workforce
Development Riverside Recovery Resources
City of Eastvale Department of Veteran Affairs Loma Linda Riverside University Health System (RUHS) - HHOPE Program
City of Hemet Eastvale Bible Church
Riverside University Health System
(RUHS)-Behavioral Health
City of Indian Wells Edgemont Women's Club
Riverside University Health System
(RUHS)-HIV/STD Program
City of Indio Families Living with AIDS Care Center Rubidoux Youth Opportunity Center City of Jurupa Valley FIND Food Bank San Jacinto School District-NAMI City of La Quinta Food Now Set Free Thrift Store
City of Lake Elsinore Galilee Center Social Work Action Group (SWAG) City of Menifee Hemet Unified School District Starting Over Inc.
City of Moreno Valley Indio WIN Center Step Up on Second City of Murrieta In-Home Supportive Services Stepping Stones TAY Center City of Norco Inland Empire Health Plan The Arena TAY Center City of Palm Desert Inland Equity Partnership The Happier Life Project City of Palm Springs Jamboree Housing The Litas Women's Biker Group City of Perris Jewish Family Service Desert The Salvation Army City of Rancho Mirage Jewish Family Service of San Diego Trauma Recovery Center City of Riverside La Sierra University Church Trinity University City of San Jacinto Legacy Shelters United States Bureau of Census City of Temecula Light House Baptist Church Val Verde School District City of Wildomar Lighthouse Social Service Center Valley Restart Shelter City Police Department Lutheran Social Services Veteran's Services Coachella Valley Association of
Governments Martha's Village and Kitchen
Western Riverside Council of
Governments
Youth Community Corps (YCC) Project
We greatly appreciate the investment of time and energy provided by the agencies that participated in implementing the Youth PIT Count. The success of the Youth PIT Count is due in largest part to the following youth-friendly agencies who kept the count running smoothly. o Building Up Lives Foundation (Deployment Site)
o California Family Life Center, Empower Youth (Deployment Site) o Continuum of Care (CoC)
o Department of Behavioral Health (RUHS-BH) HHOPE Team
o Department of Public and Social Services, Banning Office (Deployment Site) o Department of Public and Social Services, Indio Office (Deployment Site) o Indio WIN Youth Opportunity Center
o Queer Works
o Operation SafeHouse (Deployment Site)
o Operation SafeHouse of the Desert (Deployment Site)
o Riverside County Library System
o Riverside County Office of Education (RCOE)
o Riverside County Youth Commission
o Riverside University Health System – HOPE Team
o Rubidoux Youth Opportunity Center (Deployment Site)
o Springs Charter Schools
Page | 61
o Social Work Action Group (SWAG)
o Stepping Stones Transitional Age Youth (TAY) Center
o The Arena Transitional Age Youth (TAY) Center
o Transgender Health and Wellness Center
o Youth Advisory Committee (YAC) – Continuum of Care
o Youth Action Board (YAB) – Continuum of Care
We are extremely grateful to University of California, Riverside (UCR) student interns for their energy, dedication and involvement in the preparation and implementation of the 2022 PIT and YPIT Counts.
• Gabriella Zafarana • Mariel Sarmiento
County of Riverside, Department Housing and Workforce Solution (HWS) Continuum of Care Division
2022 Point-in-Time Count Planning Team
Administrative Office
Heidi Marshal
Director
Carrie Harmon
Assistant Director
Tanya Torno
Deputy Director
Emma Perez-Singh
Administrative Services Manager
Continuum of Care Division
Laura González
PIT Count Coordinator
Monique Guerra
Homeless Youth Coordinator
Natalis Ng
Administrative Services Officer
Jonathan Rastegar
Administrative Services Assistant
Melanie Wilson
Administrative Services Assistant
Joshua Tomaszewski
Community Program Specialist
Miguel Salgado
Administrative Services Analyst
Selam Walker
Research Specialist
Gordon Kuang
Business Process Analyst
Mary Madsen
Administrative Services Analyst II
Jamie Gibson
Program Specialist II
Raushanah Walker
Senior Program Specialist
Martha Samaniego
Program Specialist II
Elizabeth Hernandez
Senior Program Specialist
Brandon Trahan
Admin Services Supervisor
Carlos Guerra
Admin Services Analyst
Page | 62
Cynthia Whittenberg
Administrative Services Analyst II
Alejandra Larson
Administrative Services Analyst
Ivan Gomez
Accounting Technician I
Catalina Guitron
Contracts & Grants Analyst
James Moore III
Contracts & Grants Analyst
Page | 63
APPENDIX A: CITY, UNINCORPORATED AREA,
SUPERVISORIAL DISTRICT, AND SUB-
POPULATION SUMMARY TABLES
Page | 64
City Summary Tables
There are 28 cities in the County of Riverside. The table below shows the unsheltered, sheltered, and total homeless count. The cities of Riverside, Palm Springs, Corona, and Indio counted more unsheltered persons in comparison with other jurisdictions. Calimesa, Moreno Valley, Corona, and Temecula showed a decline between 2020 and 2022.
Jurisdiction Unsheltered 2022 Unsheltered Difference
(2020 vs. 2022)
Sheltered
2022 Total Percent of
Total Count
Banning 54 26% 11 65 2%
Beaumont 16 0% 3 19 1%
Blythe 79 8% 12 91 3%
Calimesa 8 -53% 0 8 0%
Canyon Lake 0 0% 0 0 0%
Cathedral City 61 39% 12 73 2%
Coachella 74 -5% 0 74 2%
Corona 110 1% 78 188 6%
Desert Hot Springs 48 -29% 15 63 2%
Eastvale 6 50% 17 23 1%
Hemet 82 -12% 85 167 5%
Indian Wells 0 0% 0 0 0%
Indio 105 27% 322 427 13%
Jurupa Valley 96 -7% 9 105 3%
La Quinta 7 133% 0 7 0%
Lake Elsinore 35 -30% 40 75 2%
Menifee 28 47% 4 32 1%
Moreno Valley 77 -53% 10 87 3%
Murrieta 12 -33% 149 161 5%
Norco 14 17% 13 27 1%
Palm Desert 26 44% 0 26 1%
Palm Springs 222 18% 54 276 8%
Perris 59 14% 11 70 2%
Rancho Mirage 3 -75% 0 3 0%
Riverside (District 1) 307 -10% 398 705 21%
Riverside (District 2) 207 -16% 12 219 7%
San Jacinto 57 84% 19 76 2%
Temecula 28 -53% 39 67 2%
Unincorporated 1 24 -46% 0 24 1%
Unincorporated 2 27 -13% 0 27 1%
Unincorporated 3 48 -11% 0 48 1%
Unincorporated 4 45 -22% 9 54 2%
Unincorporated 5 8 -47% 0 8 0%
Wildomar 7 17% 14 21 1%
Total 1980 8% 1336 3316 100%*
*Percentages do not add up to 100% due to rounding
Page | 65
Trend in City Unsheltered Counts 2019 to 2022
There was no consistent unsheltered count trend among all cities. Some cities experienced modest change and others saw more radical shifts in overall homelessness. Several jurisdictions, however, had a pattern of increase between 2019 and 2020, followed by a decrease between 2020 and 2022 as seen in the graph below, Change in Unsheltered 2019-2022 below (i.e., Unincorporated 5, Riverside, Rancho Mirage, Murrieta, Moreno Valley, Desert Hot Springs, Coachella, Calimesa).
Change in Unsheltered 2019-2022
Jurisdiction 2019 2020 2022
Banning 39 43 54
Beaumont 15 16 16
Blythe 48 73 79
Calimesa 16 17 8
Canyon Lake 0 0 0
Cathedral City 82 44 61
Coachella 51 78 74
Corona 164 109 110
Desert Hot Springs 45 68 48
Eastvale 0 4 6
Hemet 112 93 82
Indian Wells 2 1 0
Indio 52 83 105
Jurupa Valley 139 103 96
La Quinta 9 3 7
Lake Elsinore 66 50 35
Menifee 17 19 28
Moreno Valley 38 165 77
Murrieta 17 18 12
Norco 11 12 14
Palm Desert 23 18 26
Palm Springs 196 189 222
Perris 77 52 59
Rancho Mirage 6 12 3
Riverside (District 1 and District 2) 439 587 514
San Jacinto 48 31 57
Temecula 59 59 28
Unincorporated District 1 45 44 24
Unincorporated District 2 44 31 27
Unincorporated District 3 65 54 48
Unincorporated District 4 98 58 45
Unincorporated District 5 9 15 8
Wildomar 13 6 7
Total: 2,045 2,155 1,980
Page | 66
CITY SUMMARY TABLES
Page | 67
BANNING
The City of Banning experienced a 26% increase in its unsheltered count from 2020 to 2022. The portion of first time homeless (44%) was higher than most other areas. Like many areas, unsheltered persons in Banning tended to be adults (72%) and male (61%). The general distribution for race mirrors the typical pattern: White, Black, and Multiple Races, however, the percentage of persons known to be White was lower (35%) and the proportion of American Indian/Indigenous was higher (11%) in comparison to other cities. The unsheltered population included 59% chronically homeless persons and 38% living in encampments. Family disruption was the highest ranked contributor to homelessness, with lack of income and various ‘other’ causes in the top three factors. Substance abuse (41%), physical disability (31%), and mental health issues (25%) were the most frequently referenced challenges.
CITY OF BANNING
Unsheltered Sheltered Total
54 11 65
.
UNSHELTERED
Category # % of City Count
Interviewed 32 59%
Observed 22 41%
Age (all) # %
Adults (25-59) 39 72%
Children (≤17) 0 0
Seniors (≥ 60) 4 8%
Youth (18-24) 6 11%
Unknown Ages 5 9%
Total 54 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 6 11%
Asian, Asian American 0 0%
Black, African American, African 9 17%
Native Hawaiian, Pacific Islander 1 2%
Multiple Races 5 9%
White 19 35%
Unknown Race 14 26%
Total 54 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 14 26%
Non- Hispanic 27 50%
Unknown Ethnicity 13 24%
Total 54 100%
Gender (all) # %
Female 16 30%
Male 33 61%
No Single Gender 0 0%
Page | 68
Questioning 1 2%
Transgender 0 0%
Unknown Gender 4
7%
Total 54 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 5 16%
Domestic Violence 1 3%
HIV AIDS 0 0%
Mental Health Issue 8 25%
Physical Disability 10 31%
PTSD 9 28%
Substance Abuse 13 41%
Traumatic Brain Injury 3 9%
Developmental Disability 3 9%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 19 59% Veterans 1 3%
First Time Homeless (self-report) 14 44%
Pet Owner 9 28%
Foster Care Experience 2 6%
Formerly Incarcerated 6 19%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 9 28%
Jail Release 1 3%
Lack of Income 3 9%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 2 6%
Substance Abuse 2 6%
Unemployment 5 16%
Other 6 19%
Living Situation - Night before the Count (interview) # % Abandoned Building 5 16%
Bus Station 0 0%
Encampment 12 38%
Park 0 0%
Street 4 13%
Tent/Shed 9 28%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 2 6%
Other 0 0%
Total 32 100%
Page | 69
BEAUMONT
The City of Beaumont’s homeless population held similar patterns to many other groups: predominantly adult, White, male, and non-Hispanic/Latino(a)(x) (Hispanic), however, the group did not include Multiple-Race persons. Nearly one-half (45%) of interviewed persons reported being homeless for the first time.
Like other areas, family disruption was reported as a major factor in homelessness. Unlike other areas, Beaumont unsheltered persons reported other factors as the second most frequent factor contributing to homelessness (18%), followed by jail release and substance abuse. Physical disability was the most prevalent challenge (27%).
CITY OF BEAUMONT
Unsheltered Sheltered Total
16 3 19
.
UNSHELTERED
Category # % of City Count
Interviewed 11 69%
Observed 5 31%
Age (all) # %
Adults (25-59) 10 63%
Children (≤17) 0 0%
Seniors (≥ 60) 2 13%
Youth (18-24) 4 25%
Unknown Ages 0 0%
Total 16 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 0 0%
Asian, Asian American 0 0%
Black, African American, African 1 6%
Native Hawaiian, Pacific Islander 1 6%
Multiple Races 0 0%
White 11 69%
Unknown Race 3 19%
Total 16 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x)
6 38%
Non- Hispanic 8 50%
Unknown Ethnicity 2 13%
Total 16 100%
Gender (all) # %
Female 4 25%
Page | 70
Male 10 63%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 2 13%
Total 16 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 2 18%
Domestic Violence 0 0%
HIV AIDS 1 9%
Mental Health Issue 1 9%
Physical Disability 3 27%
PTSD 1 9%
Substance Abuse 1 9%
Traumatic Brain Injury 1 9%
Developmental Disability 1 9%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 4 36% Veterans 0 0%
First Time Homeless (self-report)
5 45%
Pet Owner 0 0%
Foster Care Experience 0 0%
Formerly Incarcerated 1 9%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 3 27%
Jail Release 1 9%
Lack of Income 0 0%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 1 9%
Unemployment 0 0%
Other 2 18%
Living Situation - Night before the Count (interview) # % Abandoned Building 1 9%
Bus Station 0 0%
Encampment 0 0%
Park 0 0%
Street 5 45%
Tent/Shed 0 0%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 1 9%
Other 4 36%
Total 11 100%*
*Percentages do not add up to 100% due to rounding
Page | 71
BLYTHE
The City of Blythe experienced an 8% increase in unsheltered homeless persons. First time homeless individuals accounted for 48% of all persons identified during the count. Adults (ages 25-59, 82%) and Seniors (age 60+, 8%) comprised 90% of the unsheltered homeless persons. Substance abuse (33%), chronic health issue (28%), mental health issue (25%), and physical disability (25%) were the leading challenges identified. Contributors to homelessness were lack of income (20%), substance abuse (18%), and unemployment (15%). The use of abandoned buildings for shelter (30%) was higher in Blythe compared with many areas. Nearly half (48%) were experiencing homelessness for the first time and one-third (33%) were accompanied by pets.
CITY OF BLYTHE
Unsheltered Sheltered Total
79 12 91
.
UNSHELTERED
Category # % of City Count
Interviewed 40 51%
Observed 39 49%
Age (all) # %
Adults (25-59) 65 82%
Children (≤17) 0 0%
Seniors (≥ 60) 6 8%
Youth (18-24) 6 8%
Unknown Ages 2 3%
Total 79 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 1%
Asian, Asian American 0 0%
Black, African American, African 16 20%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 7 9%
White 49 62%
Unknown Race 6 8%
Total 79 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 14 18%
Non- Hispanic 59 75%
Unknown Ethnicity 6 8%
Total 79 100%*
Gender (all) # %
Female 30 38%
Male 46 58%
No Single Gender 0 0%
Page | 72
Questioning 0 0%
Transgender 0 0%
Unknown Gender 3 4%
Total 79 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 11 28%
Domestic Violence 3 8%
HIV AIDS 1 3%
Mental Health Issue 10 25%
Physical Disability 10 25%
PTSD 5 13%
Substance Abuse 13 33%
Traumatic Brain Injury 2 5%
Developmental Disability 4 10%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 19 48% Veterans 1 3%
First Time Homeless (self-report)
19 48%
Pet Owner 13 33%
Foster Care Experience 0 0%
Formerly Incarcerated 5 13%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 4 10%
Jail Release 2 5%
Lack of Income 8 20%
Medical Discharge 0 0%
Mental Illness 2 5%
Runaway 0 0%
Substance Abuse 7 18%
Unemployment 6 15%
Other 11 28%
Living Situation - Night before the Count (interview) # % Abandoned Building 12 30%
Bus Station 1 3%
Encampment 7 18%
Park 1 3%
Street 9 23%
Tent/Shed 5 13%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 1 3%
Other 4 10%
Total 40 100%*
*Percentages do not add up to 100% due to rounding
Page | 73
CALIMESA
The City of Calimesa counted eight (8) unsheltered persons during the Point-in-Time Count and had no persons living in shelter, making it a community with the lowest count; only Rancho Mirage (3), La Quinta (7), and Canyon Lake (0) were smaller. The 2022 unsheltered count represented a 53% decrease over 2020. Half of the unsheltered individuals were adults, and the other half were seniors. Like many other communities, unsheltered persons were predominantly White, non-Hispanic, males. One-third (33%) were chronically homeless, and the same percentage reported mental health issues as a life factor. Two thirds (67%) of the unsheltered were first-time homeless, pet owners, report a lack of income as a factor contributing to homelessness, and sleep in a vehicle.
CITY OF CALIMESA
Unsheltered Sheltered Total
8 0 8
.
UNSHELTERED
Category # % of City Count
Interviewed 6 75%
Observed 2 25%
Age (all) # %
Adults (25-59) 4 50%
Children (≤17) 0 0%
Seniors (≥ 60) 4 50%
Youth (18-24) 0 0%
Unknown Ages 0 0%
Total 8 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 13%
Asian, Asian American 0 0%
Black, African American, African 0 0%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 0 0%
White 6 75%
Unknown Race 1 13%
Total 8 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 2 25%
Non- Hispanic 5 63%
Unknown Ethnicity 1 13%
Total 8 100%*
Gender (all) # %
Female 2 25%
Male 6 75%
No Single Gender 0 0%
Page | 74
Questioning 0 0%
Transgender 0 0%
Unknown Gender 0 0%
Total 8 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 0 0%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 2 33%
Physical Disability 1 17%
PTSD 0 0%
Substance Abuse 1 17%
Traumatic Brain Injury 0 0%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 2 33% Veterans 0 0%
First Time Homeless (self-report)
4 67%
Pet Owner 4 67%
Foster Care Experience 0 0%
Formerly Incarcerated 1 17%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 1 17%
Jail Release 0 0%
Lack of Income 4 67%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 0 0%
Other 1 17%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 0 0%
Park 0 0%
Street 2 33%
Tent/Shed 0 0%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 4 67%
Other 0 0%
Total 6 100%
*Percentages do not add up to 100% due to rounding
Page | 75
CATHEDRAL CITY
The City of Cathedral City experienced a 39% increase in the number of unsheltered individuals from 2020 to 2022. The unsheltered group was comprised of adults ages 25-59 (79%), seniors (10%) and youth (7%) plus 5% persons of unknown age. Twenty-one percent (21%) were first time homeless, and more than half were living on the street. The group continued the overall patterns for race and gender (White 41%, male 72%), however, the proportion of Hispanic (36%), and chronically homeless individuals (50%) was higher than other groups. Substance abuse (36%), mental health issues (25%), and chronic health (29%) issues were reported as challenges.
CATHEDRAL CITY
Unsheltered Sheltered Total
61 12 73
.
UNSHELTERED
Category # % of City
Count Interviewed 28 46%
Observed 33 54%
Age (all) # %
Adults (25-59) 48 79%
Children (≤17) 0 0%
Seniors (≥ 60) 6 10%
Youth (18-24) 4 7%
Unknown Ages 3 5%
Total 61 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 2 3%
Asian, Asian American 0 0%
Black, African American, African 6 10%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 15 25%
White 25 41%
Unknown Race 13 21%
Total 61 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 22 36%
Non- Hispanic 27 44%
Unknown Ethnicity 12 20%
Total 61 100%
Gender (all) # %
Female 14 23%
Male 44 72%
No Single Gender 0 0%
Page | 76
Questioning 0 0%
Transgender 0 0%
Unknown Gender 3 5%
Total 61 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 8 29%
Domestic Violence 1 4%
HIV AIDS 1 4%
Mental Health Issue 7 25%
Physical Disability 6 21%
PTSD 5 18%
Substance Abuse 10 36%
Traumatic Brain Injury 5 18%
Developmental Disability 3 11%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 14 50% Veterans 4 14%
First Time Homeless (self-report)
6 21%
Pet Owner 2 7%
Foster Care Experience 1 4%
Formerly Incarcerated 1 4%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 8 29%
Jail Release 0 0%
Lack of Income 7 25%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 9 32%
Unemployment 2 7%
Other 1 4%
Living Situation - Night before the Count (interview) # % Abandoned Building 2 7%
Bus Station 0 7%
Encampment 2 7%
Park 0 0%
Street 15 54%
Tent/Shed 1 4%
Tiny Home (without basic amenities)
0 0%
Under Bridge 1 4%
Vehicle 4 14%
Other 3 11%
Total 28 100*
*Percentages do not add up to 100% due to rounding
Page | 77
COACHELLA
Between 2020 and 2022, The City of Coachella’s unsheltered number decreased by 5% . The 2022 Coachella’s unsheltered group of 74 persons encompassed all four of the major age categories: adult 88%, youth 3%, seniors 5%, and children (3%). Of those interviewed, 45% reported being homeless for the first time. Living situations reported included staying in a tent or shed (59%) and living on the street (21%).
The ethnic composition of the unsheltered population in Coachella was majority Hispanic/Latin(o)(a)(x) (76%). 80% of the 74 individuals counted were reported Male. Nearly one-third, 32% suffered from chronic health issues, and a similar number reported family disruption as a factor contributing to their homelessness.
CITY OF COACHELLA
Unsheltered Sheltered Total
74 0 74
..
UNSHELTERED
Category # % of City Count
Interviewed 56 76%
Observed 18 24%
Age (all) # %
Adults (25-59) 65 88%
Children (≤17) 2 3%
Seniors (≥ 60) 4 5%
Youth (18-24) 2 3%
Unknown Ages 1 1%
Total 74 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 1%
Asian, Asian American 1 1%
Black, African American, African 2 3%
Native Hawaiian, Pacific Islander 1 1%
Multiple Races 11 15%
White 46 62%
Unknown Race 12 16%
Total 74 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 56 76%
Non- Hispanic 13 18%
Unknown Ethnicity 5 7%
Total 74 100%*
Gender (all) # %
Female 13 18%
Male 59 80%
No Single Gender 0 0%
Questioning 0 0%
Page | 78
*Percentages do not add up to 100% due to rounding
Transgender 0 0%
Unknown Gender 2 3%
Total 74 100*
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 18 32%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 7 13%
Physical Disability 11 20%
PTSD 1 2%
Substance Abuse 18 32%
Traumatic Brain Injury 2 4%
Developmental Disability 7 13%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 2 3%
Chronically Homeless (generated based on qualifying responses) 19 34% Veterans 3 5%
First Time Homeless (self-report)
25 45%
Pet Owner 5 9%
Foster Care Experience 0 0%
Formerly Incarcerated 6 11%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 18 32%
Jail Release 2 4%
Lack of Income 8 14%
Medical Discharge 2 4%
Mental Illness 1 2%
Runaway 3 5%
Substance Abuse 5 9%
Unemployment 9 16%
Other 3 5%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 1 2%
Encampment 2 4%
Park 2 4%
Street 12 21%
Tent/Shed 33 59%
Tiny Home (without basic amenities)
0 0%
Under Bridge 1 2%
Vehicle 3 5%
Other 2 4%
Total 56 100%*
Page | 79
CORONA
The unsheltered count for the City of Corona remained relatively stable, increasing by only 1% between 2020 and 2022. The largest portion of the unsheltered group lived on the street (43%). Demographically, unsheltered persons mirrored the pattern seen elsewhere: White (53%), male (68%), adult (75%). The portion of Hispanic/Latino(a)(x) (45%), however, was slightly higher than other communities.
More than one-third or 38% of unsheltered persons interviewed fit the criteria for chronic homelessness, yet a similar percent was experiencing homelessness for the first-time. Substance abuse (40%), Post-Traumatic Stress Disorder (26%), and chronic health issues (20%) were the top challenges reported, while nearly one-half (42%) listed family disruption as a contributing factor to their homelessness. Although substance abuse was the most prevalent challenging condition (40%) only (15%) reported substance abuse as a factor contributing to their homelessness. Veterans comprised about 6% of the unsheltered count and 26% identified Post-Traumatic Stress Disorder on the list of challenging factors.
CITY OF CORONA
Unsheltered Sheltered Total
110 78 188
.
UNSHELTERED
Category # % of City Count
Interviewed 65 59%
Observed 45 41%
Age (all) # %
Adults (25-59) 83 75%
Children (≤17) 0 0%
Seniors (≥ 60) 3 3%
Youth (18-24) 14 13%
Unknown Ages 10 9%
Total 110 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 1%
Asian, Asian American 1 1%
Black, African American, African 15 14%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 15 14%
White 58 53%
Unknown Race 20 18%
Total 110 100*
Ethnicity (all)
#
%
Hispanic, Latin(o), (a), (x) 50 45%
Non- Hispanic 40 36%
Unknown Ethnicity 20 18%
Total 110 100%*
Gender (all) # %
Female 26 24%
Page | 80
Male 75 68%
No Single Gender 0 0%
Questioning 0 0%
Transgender 1 1%
Unknown Gender 8 7%
Total 110 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 13 20%
Domestic Violence 3 5%
HIV AIDS 0 0%
Mental Health Issue 13 20%
Physical Disability 9 14%
PTSD 17 26%
Substance Abuse 26 40%
Traumatic Brain Injury 8 12%
Developmental Disability 8 12%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 25 38% Veterans 4 6%
First Time Homeless (self-report)
25 38%
Pet Owner 6 9%
Foster Care Experience 1 2%
Formerly Incarcerated 19 29%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 27 42%
Jail Release 5 8%
Lack of Income 3 5%
Medical Discharge 2 3%
Mental Illness 3 5%
Runaway 0 0%
Substance Abuse 10 15%
Unemployment 3 5%
Other 8 12%
Living Situation - Night before the Count (interview) # % Abandoned Building 9 14%
Bus Station 0 0%
Encampment 7 11%
Park 10 15%
Street 28 43%
Tent/Shed 2 3%
Tiny Home (without basic amenities)
0 0%
Under Bridge 2 3%
Vehicle 2 3%
Other 5 8%
Total 65 100%
*Percentages do not add up to 100% due to rounding
Page | 81
DESERT HOT SPRINGS
The 2022 homeless count found a total of 63 homeless persons living in the City of Desert Hot Springs.
The number of unsheltered persons fell by 29% compared to the Point-in-Time Count in 2020. The unsheltered group was primarily adults (67%) and seniors (4%), white (50%), non-Hispanic (40%), and male (56%). The group had nearly equal percentages (43%) of substance abusers and first-time homeless. Unsheltered persons were likely to be found living in a vehicle (33%), tent or shed (20%), or on the street (27%).
DESERT HOT SPRINGS
Unsheltered Sheltered Total
48 15 63
.
UNSHELTERED
Category # % of Count
Interviewed 30 63%
Observed 18 38%
Age (all) # %
Adults (25-59) 32 67%
Children (≤17) 0 0%
Seniors (≥ 60) 2 4%
Youth (18-24) 3 6%
Unknown Ages 11 23%
Total 48 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 2 4%
Asian, Asian American 0 0%
Black, African American, African 1 2%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 3 6%
White 24 50%
Unknown Race 18 38%
Total 48 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 10 21%
Non- Hispanic 19 40%
Unknown Ethnicity 19 40%
Total 48 100*
Gender (all) # %
Female 11 23%
Male 27 56%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 10 21%
Total 48 100%
Page | 82
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 3 10%
Domestic Violence 2 7%
HIV AIDS 0 0%
Mental Health Issue 8 27%
Physical Disability 5 17%
PTSD 8 27%
Substance Abuse 13 43%
Traumatic Brain Injury 4 13%
Developmental Disability 3 10%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 13 43% Veterans 3 10%
First Time Homeless (self-report)
14 47%
Pet Owner 8 27%
Foster Care Experience 1 3%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 10 33%
Jail Release 1 3%
Lack of Income 4 13%
Medical Discharge 0 0%
Mental Illness 1 3%
Runaway 2 7%
Substance Abuse 2 7%
Unemployment 4 13%
Other 4 13%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 3 10%
Park 0 0%
Street 8 27%
Tent/Shed 6 20%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 10 33%
Other 3 10%
Total 30 100%
*Percentages do not add up to 100% due to rounding
Page | 83
EASTVALE
The City of Eastvale experienced a 50% increase among the unsheltered population between 2020 and 2022. However, this was a total of six (6) persons. The group contained five (5) adults ages 25-59 and one senior age 60+. Over half (60%) of the group stayed in tents/sheds, and the remainder in vehicles or other locations. Lack of income was the primary reason identified as contributing to homelessness (60%). Physical disability and family disruption were also reported as reasons for homelessness.
CITY OF EASTVALE
Unsheltered Sheltered Total
6 17 23
.
UNSHELTERED
Category # % of City Count
Interviewed 5 83%
Observed 1 17%
Age (all) # %
Adults (25-59) 5 83%
Children (≤17) 0 0%
Seniors (≥ 60) 1 17%
Youth (18-24) 0 0%
Unknown Ages 0 0%
Total 6 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 17%
Asian, Asian American 0 0%
Black, African American, African 2 33%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 0 0%
White 2 33%
Unknown Race 1 17%
Total 6 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 1 17%
Non- Hispanic 4 67%
Unknown Ethnicity 1 17%
Total 6 100*
Gender (all) # %
Female 2 33%
Male 4 67%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 0 0%
Total 6 100%
Page | 84
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 0 0%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 0 0%
Physical Disability 1 20%
PTSD 0 0%
Substance Abuse 0 0%
Traumatic Brain Injury 0 0%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 1 20% Veterans 1 20%
First Time Homeless (self-report)
4 80%
Pet Owner 0 0%
Foster Care Experience 0 0%
Formerly Incarcerated 0 0%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 1 20%
Jail Release 0 0%
Lack of Income 3 60%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 0 0%
Other 1 20%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 0 0%
Park 0 0%
Street 0 0%
Tent/Shed 3 60%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 2 40%
Other 0 0%
Total 5 100%
*Percentages do not add up to 100% due to rounding
Page | 85
HEMET
The City of Hemet experienced a decrease of 12% in the unsheltered homeless population between 2020 and 2022. The total homeless population in Hemet was almost evenly distributed between unsheltered (82) and sheltered individuals (85). Nearly half (49%) of the people interviewed reported being homeless for the first time. When compared with other areas, Hemet had a higher proportion of youth ages 18 to 24 (18%) and chronically homeless (61%) in the unsheltered group.
Most of the unsheltered portion of the community followed the pattern frequently seen throughout the 2022 Point-in-Time Count: White (44%), male (72%), non-Hispanic (57%). Substance abuse (46%), PTSD (39%), and mental health issues (30%) were the most frequently cited personal challenges. Family disruption (40%) and a lack of income (25%) were the top factors identified as contributing to homelessness.
CITY OF HEMET
Unsheltered Sheltered Total
82 85 167
.
UNSHELTERED
Category # % of City Count
Interviewed 57 70%
Observed 25 30%
Age (all) # %
Adults (25-59) 57 70%
Children (≤17) 1 1%
Seniors (≥ 60) 7 9%
Youth (18-24) 15 18%
Unknown Ages 2 2%
Total 82 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 5 6%
Asian, Asian American 0 0%
Black, African American, African 15 18%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 16 20%
White 36 44%
Unknown Race 10 12%
Total 82 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 29 35%
Non- Hispanic 47 57%
Unknown Ethnicity 6 7%
Total 82 100%*
Gender (all) # %
Female 21 26%
Male 59 72%
No Single Gender 0 0%
Page | 86
Questioning 0 0%
Transgender 0 0%
Unknown Gender 2 2%
Total 82 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 11 19%
Domestic Violence 5 9%
HIV AIDS 1 2%
Mental Health Issue 17 30%
Physical Disability 14 25%
PTSD 22 39%
Substance Abuse 26 46%
Traumatic Brain Injury 11 19%
Developmental Disability 6 11%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 1 2%
Chronically Homeless (generated based on qualifying responses)
35 61%
Veterans 2 4%
First Time Homeless (self-report)
28 49%
Pet Owner 8 14%
Foster Care Experience 1 2%
Formerly Incarcerated 14 25%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 23 40%
Jail Release 4 7%
Lack of Income 14 25%
Medical Discharge 1 2%
Mental Illness 0 0%
Runaway 3 5%
Substance Abuse 5 9%
Unemployment 3 5%
Other 4 7%
Living Situation - Night before the Count (interview) # % Abandoned Building 5 9%
Bus Station 0 0%
Encampment 5 9%
Park 2 4%
Street 33 58%
Tent/Shed 7 12%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 3 5%
Other 2 4%
Total 57 100%*
*Percentages do not add up to 100% due to rounding
Page | 87
INDIO
The City of Indio’s unsheltered population grew by 27% between 2020 and 2022 and ranked as the fourth highest area of unsheltered homeless persons in the County. Demographically, the unsheltered group in Indio had the same pattern as other communities of adult (61%), White (70%), male (63%).
Additionally, Indio also had a higher proportion of youth (22%) and Hispanic (50%) and chronically homeless (47%).
The Indio unsheltered population reported family disruption (36%), unemployment (17%) and lack of income (12%) as factors contributing to homeless. Most unsheltered persons in the city were living on the street (30%), in an encampment (22%), or in a tent or shed (17%).
CITY OF INDIO
Unsheltered Sheltered Total
105 322 427
.
UNSHELTERED
Category # % of City Count
Interviewed 59 56%
Observed 46 44%
Age (all) # %
Adults (25-59) 64 61%
Children (≤17) 0 0%
Seniors (≥ 60) 9 9%
Youth (18-24) 23 22%
Unknown Ages 9 9%
Total 105 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 1%
Asian, Asian American 0 0%
Black, African American, African 3 3%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 10 10%
White 74 70%
Unknown Race 17 16%
Total 105 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 52 50%
Non- Hispanic 33 31%
Unknown Ethnicity 20 19%
Total 105 100%
Gender (all) # %
Female 32 30%
Male 66 63%
Page | 88
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 7 7%
Total 105 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 7 12%
Domestic Violence 4 7%
Mental Health Issue 14 24%
Physical Disability ‘10 17%
PTSD 16 27%
Substance Abuse 22 37%
Traumatic Brain Injury 9 15%
Developmental Disability 7 12%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/Children 0 0%
Chronically Homeless (generated based on qualifying responses) 28 47% Veterans 4 7%
First Time Homeless (self-report)
21 36%
Pet Owner 8 14%
Foster Care Experience 2 3%
Formerly Incarcerated 10 17%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 21 36%
Jail Release 0 0%
Lack of Income 7 12%
Medical Discharge 1 2%
Mental Illness 0 0%
Runaway 2 3%
Substance Abuse 4 7%
Unemployment 10 17%
Other 11 19%
Living Situation - Night before the Count (interview) # % Abandoned Building 3 5%
Bus Station 0 0%
Encampment 13 22%
Park 2 3%
Street 18 30%
Tent/Shed 10 17%
Tiny Home (without basic amenities)
0 0%
Under Bridge 2 3%
Vehicle 5 8%
Other 6 10%
Total 59 100%* *Percentages do not add up to 100% due to rounding
Page | 89
JURUPA VALLEY
The City of Jurupa Valley experienced a decrease of 7% in unsheltered people between 2020 and 2022.
The unsheltered group tended to live in encampments (35%), in vehicles (28%) or in tents/sheds (27%).
Jurupa Valley contained a moderate number of homeless youth (13%), pet owners (48%), and first-time homeless (37%).
Once again, the demographic distribution was familiar: White, adult, male, non-Hispanic. The challenges include more over-lapping conditions with five conditions being reported at levels at 20 % or above (up to 33%). These conditions were mental health issues (20%), chronic health issues (25%), physical disability (22%), substance abuse (33%) and PTSD (23%).
CITY OF JURUPA VALLEY
Unsheltered Sheltered Total
96 9 105
.
UNSHELTERED
Category # % of City Count
Interviewed 60 63%
Observed 36 38%
Age (all) # %
Adults (25-59) 60 63%
Children (≤17) 0 0%
Seniors (≥ 60) 8 8%
Youth (18-24) 12 13%
Unknown Ages 16 17%
Total 96 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 1%
Asian, Asian American 0 0%
Black, African American, African 19 20%
Native Hawaiian, Pacific Islander 1 1%
Multiple Races 10 10%
White 47 49%
Unknown Race 18 19%
Total 96 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 29 30%
Non- Hispanic 42 44%
Unknown Ethnicity 25 26%
Total 96 100%
Gender (all) # %
Female 25 26%
Male 57 59%
No Single Gender 0 0%
Page | 90
Questioning 0 0%
Transgender 0 0%
Unknown Gender 14 15%
Total 96 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 15 25%
Domestic Violence 3 5%
HIV AIDS 1 2%
Mental Health Issue 12 20%
Physical Disability 13 22%
PTSD 14 23%
Substance Abuse 20 33%
Traumatic Brain Injury 9 15%
Developmental Disability 8 13%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 32 53% Veterans 3 5%
First Time Homeless (self-report)
22 37%
Pet Owner 29 48%
Formerly Incarcerated 8 13%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 14 23%
Jail Release 3 5%
Lack of Income 9 15%
Medical Discharge 1 2%
Mental Illness 4 7%
Runaway 4 7%
Substance Abuse 4 7%
Unemployment 12 20%
Other 5 8%
Living Situation - Night before the Count (interview) # % Abandoned Building 1 2%
Bus Station 0 0%
Encampment 21 35%
Park 0 0%
Street 2 3%
Tent/Shed 16 27%
Tiny Home (without basic amenities)
2 3%
Under Bridge 1 2%
Vehicle 17 28%
Other 0 0%
Total 60 100%
*Percentages do not add up to 100% due to rounding
Page | 91
LA QUINTA
Despite an increase of 133%, the City of La Quinta had one of the smallest unsheltered homeless counts when compared with other jurisdictions. 80% of persons reported sleeping in their vehicle and one person (20%) was sleeping under a bridge. The demographic distribution in La Quinta included 29% White, 43% male, and 57% adults.
There were three conditions associated with the unsheltered group: chronic health issues (20%), Post- Traumatic Stress Disorder (40%), and physical disability (20%). Like other areas, family disruption and lack of income were frequently reported as factors causing homelessness. It is interesting to note that while no youth or domestic violence victims were reported, a runaway status was reported for a 31- year-old individual.
CITY OF LA QUINTA
Unsheltered Sheltered Total
7 0 7
.
UNSHELTERED
Category # % of City Count
Interviewed 5 71%
Observed 2 29%
Age (all) # %
Adults (25-59) 4 57%
Children (≤17) 0 0%
Seniors (≥ 60) 1 14%
Youth (18-24) 0 0%
Unknown Ages 2 29%
Total 7 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 14%
Asian, Asian American 0 0%
Black, African American, African 0 0%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 0 0%
White 2 29%
Unknown Race 4 57%
Total 7 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 2 29%
Non- Hispanic 3 43%
Unknown Ethnicity 2 29%
Total 7 100%*
Gender (all) # %
Female 2 29%
Male 3 43%
Page | 92
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 2 29%
Total 7 100%*
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 1 20%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 0 0%
Physical Disability 1 20%
PTSD 2 40%
Substance Abuse 0 0%
Traumatic Brain Injury 0 0%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 0 0% Veterans 0 0%
First Time Homeless (self-report)
3 60%
Pet Owner 1 20%
Foster Care Experience 0 0%
Formerly Incarcerated 0 0%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 2 40%
Jail Release 0 0%
Lack of Income 1 20%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 1 20%
Substance Abuse 0 0%
Unemployment 0 0%
Other 1 20%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 0 0%
Park 0 0%
Street 0 0%
Tent/Shed 0 0%
Tiny Home (without basic amenities)
0 0%
Under Bridge 1 20%
Vehicle 4 80%
Other 0 0%
Total 5 100%
*Percentages do not add up to 100% due to rounding
Page | 93
LAKE ELSINORE
Between 2020 and 2022, unsheltered homelessness in the City of Lake Elsinore dropped by 30%. Less than half (41%) of the unsheltered group interviewed during the Point-in-Time Count reported being homeless for the first time and 64% qualified as chronically homeless.
Lake Elsinore’s unsheltered group held the pattern familiar to most areas: largely White, male, non- Hispanic. The vast majority were adults (83%, including 11% seniors). Nearly two-thirds of unsheltered people interviewed indicated substance abuse as a challenge/barrier (59%) and the same percentage were living on the street during the Point-in-Time Count.
CITY OF LAKE ELSINORE
Unsheltered Sheltered Total
35 40 75
.
UNSHELTERED
Category # % of City Count
Interviewed 22 63%
Observed 13 37%
Age (all) # %
Adults (25-59) 29 83%
Children (≤17) 0 0%
Seniors (≥ 60) 4 11%
Youth (18-24) 1 3%
Unknown Ages 1 3%
Total 35 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 3%
Asian, Asian American 0 0%
Black, African American, African 1 3%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 0 0%
White 27 77%
Unknown Race 6 17%
Total 35 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 13 37%
Non- Hispanic 16 46%
Unknown Ethnicity 6 17%
Total 35 100%
Gender (all) # %
Female 8 23%
Male 27 77%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 0 0%
Total 35 100%
Page | 94
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 4 18%
Domestic Violence 2 9%
HIV AIDS 2 9%
Mental Health Issue 8 36%
Physical Disability 3 14%
PTSD 10 45%
Substance Abuse 13 59%
Traumatic Brain Injury 8 36%
Developmental Disability 1 5%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 14 64% Veterans 1 5%
First Time Homeless (self-report)
9 41%
Pet Owner 2 9%
Foster Care Experience 1 5%
Former Incarceration 9 41%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 8 36%
Jail Release 0 0%
Lack of Income 2 9%
Medical Discharge 0 0%
Mental Illness 1 5%
Runaway 1 5%
Substance Abuse 4 18%
Unemployment 1 5%
Other 5 23%
Living Situation - Night before the Count (interview) # % Abandoned Building 1 5%
Bus Station 0 0%
Encampment 3 14%
Park 0 0%
Street 13 59%
Tent/Shed 1 5%
Tiny Home (without basic amenities)
0 0%
Under Bridge 1 5%
Vehicle 2 9%
Other 1 5%
Total 22 100%*
*Percentages do not add up to 100% due to rounding
Page | 95
MENIFEE
The City of Menifee experienced a 47% rise in unsheltered homelessness between 2020 and 2022. The living situation of unsheltered people in Menifee was relatively evenly distributed with 23% dwelling on the street, in vehicles or other locations, and 15% found in tents or sheds or abandoned buildings.
Menifee fit the typical pattern of demographics: adult (82% including seniors), White (54%), non- Hispanic (54%), male (75%). About one-fourth (23%) reported mental health and substance abuse as a challenge or barrier and 15% cited brain injury. Family disruption was reported three times more frequently than other factors contributing to homelessness.
CITY OF MENIFEE
Unsheltered Sheltered Total
28 4 32
.
UNSHELTERED
Category # % of City Count
Interviewed 13 46%
Observed 15 54%
Age (all) # %
Adults (25-59) 21 75%
Children (≤17) 0 0%
Seniors (≥ 60) 2 7%
Youth (18-24) 2 7%
Unknown Ages 3 11%
Total 28 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 0 0%
Asian, Asian American 3 11%
Black, African American, African 0 0%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 4 14%
White 15 54%
Unknown Race 6 21%
Total 28 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 8 29%
Non- Hispanic 15 54%
Unknown Ethnicity 5 18%
Total 28 100%*
Gender (all) # %
Female 4 14%
Male 21 75%
No Single Gender 0 0%
Questioning 1 4%
Transgender 0 0%
Unknown Gender 2 7%
Total 28 100%
Page | 96
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 1 8%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 3 23%
Physical Disability 1 8%
PTSD 1 8%
Substance Abuse 3 23%
Traumatic Brain Injury 2 15%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 3 23% Veterans 2 15%
First Time Homeless (self-report)
4 31%
Pet Owner 0 0%
Foster Care Experience 0 0%
Formerly Incarcerated 3 23%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 7 54%
Jail Release 0 0%
Lack of Income 0 0%
Medical Discharge 0 0%
Mental Illness 1 8%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 2 15%
Other 2 15%
Living Situation - Night before the Count (interview) # % Abandoned Building 2 15%
Bus Station 0 0%
Encampment 0 0%
Park 0 0%
Street 3 23%
Tent/Shed 2 15%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 3 23%
Other 3 23%
Total 13 100%*
*Percentages do not add up to 100% due to rounding
Page | 97
MORENO VALLEY
The City of Moreno Valley experienced a 53% reduction in unsheltered homelessness between 2020 and 2022. Many of the unsheltered persons were living on the street (35%), or in tents or sheds (17%), or encampments (13%). 43% of the unsheltered persons interviewed were homeless for the first time.
Demographically, Moreno Valley was more diverse than other areas. Youth numbers (23%) were larger compared to other communities and another 62% of the unsheltered group were adults. Unlike other areas, unsheltered persons in Moreno Valley were identified in each of the racial groups; 40% White, 26% Black/African American, 10% Multiple Races, 6% American Indian/Indigenous People, 1% each were Asian/Asian American or Native Hawaiian/Pacific Islander. Substance Abuse (44%), Chronic Health Issues (24%), PTSD (22%), and Brain Injury (22%) were the top-ranking conditions reported by interviewees.
Like other areas, family disruption (43%) had the highest incidence among the factor contributing to homelessness.
CITY OF MORENO VALLEY
Unsheltered Sheltered Total
77 10 87
.
UNSHELTERED
Category # % of City Count
Interviewed 54 70%
Observed 23 30%
Age (all) # %
Adults (25-59) 48 62%
Children (≤17) 0 0%
Seniors (≥ 60) 7 9%
Youth (18-24) 18 23%
Unknown Ages 4 5%
Total 77 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 5 6%
Asian, Asian American 1 1%
Black, African American, African 20 26%
Native Hawaiian, Pacific Islander 1 1%
Multiple Races 8 10%
White 31 40%
Unknown Race 11 14%
Total 77 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 31 40%
Non- Hispanic 34 44%
Unknown Ethnicity 12 16%
Total 77 100%
Gender (all) # %
Female 19 25%
Page | 98
Male 54 70%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 4 5%
Total 77 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 13 24%
Domestic Violence 4 7%
HIV AIDS 0 0%
Mental Health Issue 11 20%
Physical Disability 6 11%
PTSD 12 22%
Substance Abuse 24 44%
Traumatic Brain Injury 12 22%
Developmental Disability 7 13%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 30 56% Veterans 4 7%
First Time Homeless (self-report)
23 43%
Pet Owner 4 7%
Foster Care Experience 2 4%
Formerly Incarcerated 16 30%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 23 43%
Jail Release 0 0%
Lack of Income 7 13%
Medical Discharge 0 0%
Mental Illness 2 4%
Runaway 0 0%
Substance Abuse 3 6%
Unemployment 2 4%
Other 15 28%
Living Situation - Night before the Count (interview) # % Abandoned Building 2 4%
Bus Station 0 0%
Encampment 7 13%
Park 3 6%
Street 19 35%
Tent/Shed 9 17%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 6 11%
Other 8 15%
Total 54 100%*
*Percentages do not add up to 100% due to rounding
Page | 99
MURRIETA
Between 2020 and 2022, unsheltered homelessness dropped by one-third (33%) in the City of Murrieta.
Demographic patterns were like other areas, White, adult, male, non-Hispanic. Substance abuse (55%), mental health issues (45%), developmental disability (45%), and PTSD (36%) ranked as top challenges for unsheltered persons. Most unsheltered individuals were living in vehicles (36%) or encampments (27%).
CITY OF MURRIETA
Unsheltered Sheltered Total
12 149 161
.
UNSHELTERED
Category # % of City Count
Interviewed 11 92%
Observed 1 8%
Age (all) # %
Adults (25-59) 10 83%
Children (≤17) 0 0%
Seniors (≥ 60) 2 17%
Youth (18-24) 0 0%
Unknown Ages 0 0%
Total 12 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 0 0%
Asian, Asian American 1 8%
Black, African American, African 1 8%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 1 8%
White 9 75%
Unknown Race 0 0%
Total 12 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 1 8%
Non- Hispanic 10 83%
Unknown Ethnicity 1 8%
Total 12 100%*
Gender (all) # %
Female 5 42%
Male 7 58%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 0 0%
Total 12 100%
Page | 100
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 1 9%
Domestic Violence 1 9%
HIV AIDS 0 0%
Mental Health Issue 5 45%
Physical Disability 3 27%
PTSD 4 36%
Substance Abuse 6 55%
Traumatic Brain Injury 3 27%
Developmental Disability 5 45%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 7 64% Veterans 1 9%
First Time Homeless (self-report)
3 27%
Pet Owner 1 9%
Foster Care Experience 0 0%
Formerly Incarcerated 2 18%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 4 36%
Jail Release 0 0%
Lack of Income 4 36%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 0 0%
Other 2 18%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 3 27%
Park 0 0%
Street 1 9%
Tent/Shed 1 9%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 4 36%
Other 2 18%
Total 11 100%*
*Percentages do not add up to 100% due to rounding
Page | 101
NORCO
The City of Norco experienced a 17% rise in unsheltered homelessness between 2020 and 2022.
Unsheltered individuals were found in many living situations like on the street, in a tent or shed, in a park, or vehicle.
Demographically, males comprised most of the unsheltered persons (71%). Unlike other communities, 67% of the group selected other factors as the reason for homelessness followed by lack of income at 17%. Post-Traumatic Stress Disorder held the highest percentage (33%) among the challenging conditions.
CITY OF NORCO
Unsheltered Sheltered Total
14 13 27
.
UNSHELTERED
Category # % of Count
Interviewed 6 43%
Observed 8 57%
Age (all) # %
Adults (25-59) 12 86%
Children (≤17) 0 0%
Seniors (≥ 60) 0 0%
Youth (18-24) 1 7%
Unknown Ages 1 7%
Total 14 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 7%
Asian, Asian American 4 29%
Black, African American, African 1 7%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 0 0%
White 5 36%
Unknown Race 3 21%
Total 14 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 1 7%
Non- Hispanic 7 50%
Unknown Ethnicity 6 43%
Total 14 100%
Gender (all) # %
Female 2 14%
Male 10 71%
No Single Gender 0 0%
Page | 102
Questioning 0 0%
Transgender 0 0%
Unknown Gender 2 14%
Total 14 100%*
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 0 0%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 0 0%
Physical Disability 1 17%
PTSD 2 33%
Substance Abuse 1 17%
Traumatic Brain Injury 0 0%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 1 17% Veterans 0 0%
First Time Homeless (self-report)
2 33%
Pet Owner 0 0%
Foster Care Experience 0 0%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 0 0%
Jail Release 0 0%
Lack of Income 1 17%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 0 0%
Other 4 67%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 2 33%
Park 1 17%
Street 1 17%
Tent/Shed 0 0%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 1 17%
Other 1 17%
Total 6 100%* *Percentages do not add up to 100% due to rounding
Page | 103
PALM DESERT
Between 2020 and 2022, the unsheltered homeless number rose by 44% in the City of Palm Desert.
Individuals reported sleeping on the street (75%) or encampments (13%) the night before the count.
The unsheltered group were male (81%), White (73%), and non-Hispanic (54%). First-time homeless represented 19% of the unsheltered group.
Post-Traumatic Stress Disorder (56%), substance abuse (50%), and physical disability (38%) were the most frequently reported challenging conditions. Family disruption (38%), lack of income (25%), and other factors (31%) were reported as contributors to homelessness.
CITY OF PALM DESERT
Unsheltered Sheltered Total
26 0 26
.
UNSHELTERED
Category # % of City Count
Interviewed 16 62%
Observed 10 38%
Age (all) # %
Adults (25-59) 23 88%
Children (≤17) 0 0%
Seniors (≥ 60) 1 4%
Youth (18-24) 1 4%
Unknown Ages 1 4%
Total 26 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 2 8%
Asian, Asian American 0 0%
Black, African American, African 1 4%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 1 4%
White 19 73%
Unknown Race 3 12%
Total 26 101%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 8 31%
Non- Hispanic 14 54%
Unknown Ethnicity 4 15%
Total 26 100%
Gender (all) # %
Female 3 12%
Male 21 81%
No Single Gender 1 4%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 1 4%
Total 26 100%*
Page | 104
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 4 25%
Domestic Violence 1 6%
HIV AIDS 0 0%
Mental Health Issue 2 13%
Physical Disability 6 38%
PTSD 9 56%
Substance Abuse 8 50%
Traumatic Brain Injury 4 25%
Developmental Disability 2 13%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 11 69% Veterans 1 6%
First Time Homeless (self-report)
3 19%
Pet Owner 0 0%
Foster Care Experience 0 0%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 6 38%
Jail Release 1 6%
Lack of Income 4 25%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 0 0%
Medical Discharge 0 0%
Other 5 31%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus station 1 6%
Encampment 2 13%
Park 0 0%
Street 12 75%
Tent/Shed 0 0%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 1 6%
Other 0 0%
Total 16 100%
*Percentages do not add up to 100% due to rounding
Page | 105
PALM SPRINGS
The City of Palm Springs had an increase of 18% over the 2020 count. Unsheltered persons comprised 80% of the overall homeless count for Palm Springs in 2022. During the Point-in-Time Count, nearly half (47%) of the unsheltered were living on the street, 15% were in vehicles, and 9% in abandoned buildings. Although adults were the largest portion of unsheltered persons (76%), youth comprised 7%.
The unsheltered group included persons from each race, but the predominant pattern remained the same: White (60%), Black (12%), and Multiple Races (6%) and non-Hispanic (51%).
Except for brain injury, the full list of challenging conditions was reported by unsheltered persons in Palm Springs including substance abuse (50%), PTSD (46%), and mental health issues (44%). Similarly, the most frequently listed factors contributing to homelessness were lack of income, family disruption, and substance abuse.
CITY OF PALM SPRINGS
Unsheltered Sheltered Total
222 54 276
.
UNSHELTERED
Category # % of City Count
Interviewed 78 35%
Observed 144 65%
Age (all) # %
Adults (25-59) 168 76%
Children (≤17) 0 0%
Seniors (≥ 60) 11 5%
Youth (18-24) 16 7%
Unknown Ages 27 12%
Total 222 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 4 2%
Asian, Asian American 2 1%
Black, African American, African 27 12%
Native Hawaiian, Pacific Islander 1 0%
Multiple Races 13 6%
White 134 60%
Unknown Race 41 18%
Total 222 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 34 15%
Non- Hispanic 114 51%
Unknown Ethnicity 74 33%
Total 222 100%*
Gender (all) # %
Female 46 21%
Male 152 68%
No Single Gender 1 1%
Page | 106
Questioning 0 0%
Transgender 0 0%
Unknown Gender 23 10%
Total 222 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 26 33%
Domestic Violence 8 10%
HIV AIDS 5 6%
Mental Health Issue 34 44%
Physical Disability 18 23%
PTSD 36 46%
Substance Abuse 39 50%
Traumatic Brain Injury 0 0%
Developmental Disability 15 19%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 43 55% Veterans 12 15%
First Time Homeless (self-report)
17 22%
Pet Owner 8 10%
Foster Care Experience 1 1%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 19 24%
Jail Release 2 3%
Lack of Income 20 26%
Medical Discharge 1 1%
Mental Illness 3 4%
Runaway 1 1%
Substance Abuse 10 13%
Unemployment 6 8%
Other 12 15%
Living Situation - Night before the Count (interview) # % Abandoned Building 7 9%
Bus Station 2 3%
Encampment 3 4%
Park 5 6%
Street 37 47%
Tent/Shed 5 6%
Tiny Home (without basic amenities)
0 0%
Under Bridge 1 1%
Vehicle 12 15%
Other 6 8%
Total 78 100%*
*Percentages do not add up to 100% due to rounding
Page | 107
PERRIS
The City of Perris saw a 14% increase of unsheltered homeless between 2020 and 2022. More than one- third of the unsheltered persons interviewed met the criteria for chronic homelessness. Unsheltered persons were found living on the street (29%), in tents or sheds (29%), encampments (17%), and vehicles (15%) with a few in abandoned buildings, a park, or other locations. The age, gender, ethnic, and racial distribution of unsheltered persons followed the pattern seen throughout the region: adult, male, non-Hispanic, with people who were White, Black and Multiple Races found most frequently.
With the exceptions of domestic violence and HIV/AIDS, there was a relatively even distribution of challenging conditions found among the unsheltered with 20% (mental health, physical disability, substance abuse) and 12% (PTSD, developmental disability, brain injury). Family disruption (34%), unemployment (15%), and other factors not listed (15%) were cited contributors to homelessness.
CITY OF PERRIS
Unsheltered Sheltered Total
59 11 70
.
UNSHELTERED
Category # % of City Count
Interviewed 41 69%
Observed 18 31%
Age (all) # %
Adults (25-59) 34 58%
Children (≤17) 0 0%
Seniors (≥ 60) 7 12%
Youth (18-24) 12 20%
Unknown Ages 6 10%
Total 59 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 3 5%
Asian, Asian American 2 3%
Black, African American, African 10 17%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 6 10%
White 24 41%
Unknown Race 14 24%
Total 59 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 22 37%
Non- Hispanic 25 42%
Unknown Ethnicity 12 20%
Total 59 100%*
Gender (all) # %
Female 16 27%
Male 42 71%
Page | 108
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 1 2%
Total 59 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 6 15%
Domestic Violence 0 0%
HIV AIDS 1 2%
Mental Health Issue 8 20%
Physical Disability 9 22%
PTSD 5 12%
Substance Abuse 9 22%
Traumatic Brain Injury 5 12%
Developmental Disability 5 12%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless 14 34%
Veterans 1 2%
First Time Homeless 7 17%
Pet Owner 5 12%
Foster Care Experience 4 10%
Formerly Incarcerated 8 20%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 14 34%
Jail Release 3 7%
Lack of Income 2 5%
Medical Discharge 1 2%
Mental Illness 3 7%
Runaway 0 0%
Substance Abuse 3 7%
Unemployment 6 15%
Other 6 15%
Living Situation - Night before the Count (interview) # % Abandoned Building 1 2%
Bus Station 0 0%
Encampment 7 17%
Park 1 2%
Street 12 29%
Tent/Shed 12 29%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 6 15%
Other 2 5%
Total 41 100%*
*Percentages do not add up to 100% due to rounding
Page | 109
RANCHO MIRAGE
With a total of only three persons, the City of Rancho Mirage had the smallest homeless population enumerated in the Point-in-Time Count compared to the 2020 count. Data for two of the three persons comes from observation, with one female refusing to be interviewed and a male unable to be reached physically.
CITY OF RANCHO MIRAGE
Unsheltered Sheltered Total
3 0 3
.
UNSHELTERED
Category # % of City Count
Interviewed 1 33%
Observed 2 67%
Age (all) # %
Adults (25-59) 3 100%
Children (≤17) 0 0%
Seniors (≥ 60) 0 0%
Youth (18-24) 0 0%
Unknown Ages 0 0%
Total 3 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 0 0%
Asian, Asian American 0 0%
Black, African American, African 0 0%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 0 0%
White 0 0%
Unknown Race 3 100%
Total 3 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 1 33%
Non- Hispanic 0 0%
Unknown Ethnicity 2 67%
Total 3 100%
Gender (all) # %
Female 1 33%
Male 2 67%
No Single Gender 0 0%
Questioning 0 0%
Page | 110
Transgender 0 0%
Unknown Gender 0 0%
Total 3 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 0 0%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 0 0%
Physical Disability 0 0%
PTSD 0 0%
Substance Abuse 0 0%
Traumatic Brain Injury 0 0%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 0 0% Veterans 0 0%
First Time Homeless (self-report) 0 0%
Pet Owner 0 0%
Foster Care Experience 0 0%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 0 0%
Jail Release 0 0%
Lack of Income 0 0%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 1 100%
Other 0 0%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Encampment 1 100%
Park 0 0%
Street 0 0%
Tent/Shed 0 0%
Tiny Home (without basic amenities) 0 0%
Under Bridge 0 0%
Vehicle 0 0%
Other 0 0%
Total 1 100%
Page | 111
RIVERSIDE
The City of Riverside crosses two district boundaries, Districts 1 and 2. Together, they comprise the highest number of homeless persons of any city (924). The City of Riverside in District 1 showed a 10% decrease in unsheltered homeless persons between 2020 and 2022. Similarly, the City of Riverside in District 2 experienced a 16% decrease in the number of unsheltered persons during the same period.
The portion of Riverside in each district comprised the largest components of unsheltered persons in those districts and the largest overall counts of sheltered and unsheltered persons (705 and 219 respectively). 20% of the unsheltered persons were formerly incarcerated, 6% reported domestic violence as a challenge or barrier, and 2% were living in a bus station.
Unsheltered persons were largely found on the streets (39%), in tents or sheds (17%), in vehicles (16%) or encampments (12%) with the remainder in parks, abandoned buildings, and other paces. More than half (56%) of the unsheltered responding to interviews were assessed by the survey tool as chronically homeless. The most prevalent personal conditions, referred to collectively as challenges, were substance abuse (36%), mental health issues (32%), and Post-Traumatic Stress Disorder (28%). Factors cited as contributing to homelessness included family disruption (34%), lack of income (16%), and a combination of other factors not listed (19%).
CITY OF RIVERSIDE
Unsheltered Sheltered Total
514 410 924
.
UNSHELTERED
Category # % of City Count
Interviewed 256 50%
Observed 258 50%
Age (all) # %
Adults (25-59) 307 60%
Children (≤17) 4 1%
Seniors (≥ 60) 35 7%
Youth (18-24) 87 17%
Unknown Ages 81 16%
Total 514 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 5 1%
Asian, Asian American 5 1%
Black, African American, African 87 17%
Native Hawaiian, Pacific Islander 3 1%
Multiple Races 45 9%
White 254 49%
Unknown Race 115 22%
Total 514 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 126 25%
Non- Hispanic 215 42%
Unknown Ethnicity 173 34%
Total 514 100%*
Page | 112
Gender (all) # %
Female 124 24%
Male 317 62%
No Single Gender 2 0%
Questioning 0 0%
Transgender 1 0%
Unknown Gender 70 14%
Total 514 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 55 21%
Domestic Violence 16 6%
HIV AIDS 2 1%
Mental Health Issue 81 32%
Physical Disability 55 21%
PTSD 71 28%
Substance Abuse 92 36%
Traumatic Brain Injury 42 16%
Developmental Disability 36 14%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 3 1%
Chronically Homeless (generated based on qualifying responses) 144 56% Veterans 21 8%
First Time Homeless (self-report)
92 36%
Pet Owner 49 19%
Foster Care Experience 3 1%
Formerly Incarcerated 52 20%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 87 34%
Jail Release 13 5%
Lack of Income 41 16%
Medical Discharge 0 0%
Mental Illness 7 3%
Runaway 7 3%
Substance Abuse 11 4%
Unemployment 28 11%
Other 48 19%
Living Situation - Night before the Count (interview) # % Abandoned Building 7 3%
Bus Station 4 2%
Encampment 30 12%
Park 13 5%
Street 99 39%
Tent/Shed 44 17%
Tiny Home (without basic amenities)
0 0%
Under Bridge 1 0%
Vehicle 41 16%
Other 17 7%
Total 256 100%*
*Percentages do not add up to 100% due to rounding
Page | 113
SAN JACINTO
The City of San Jacinto experienced an increase (84%) in unsheltered homeless between 2020 and 2022, including 68% of the group experiencing homelessness for the first time. The unsheltered group contained persons in each age group 79% adults and 7% seniors, 11% youth, and 2% children. Nearly two-thirds (63%) of unsheltered persons were White, while 11% were Black/African American, and equal percentages (5%) were American Indian/ Indigenous People and Multiple Races, and over half were non- Hispanic. Unsheltered homeless persons were found living in encampments and abandoned buildings (at 24% each) followed by living on the street and in vehicles (at 14% each), with the remainder in parks, tent or shed, and other locations.
Personal challenges with the highest percentages included chronic health issues, substance abuse, and PTSD each at 35%, followed by mental health issues at 32%. Factors contributing to homelessness were family disruption (62%), lack of income (16%) and other factors not listed (19%) as well as unemployment and substance abuse (each at 3%).
CITY OF SAN JACINTO
Unsheltered Sheltered Total
57 19 76
.
UNSHELTERED
Category # % of City Count
Interviewed 37 65%
Observed 20 35%
Age (all) # %
Adults (25-59) 45 79%
Children (≤17) 1 2%
Seniors (≥ 60) 4 7%
Youth (18-24) 6 11%
Unknown Ages 1 2%
Total 57 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 3 5%
Asian, Asian American 0 0%
Black, African American, African 6 11%
Native Hawaiian, Pacific Islander 1 2%
Multiple Races 3 5%
White 36 63%
Unknown Race 8 14%
Total 57 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 19 33%
Non- Hispanic 32 56%
Unknown Ethnicity 6 11%
Total 57 100%
Gender (all) # %
Female 18 32%
Page | 114
Male 38 67%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 1 2%
Total 57 100%*
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 13 35%
Domestic Violence 4 11%
HIV AIDS 0 0%
Mental Health Issue 12 32%
Physical Disability 8 22%
PTSD 13 35%
Substance Abuse 13 35%
Traumatic Brain Injury 7 19%
Developmental Disability 3 8%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 1 3%
Chronically Homeless (generated based on qualifying responses) 16 43% Veterans 4 8%
First Time Homeless (self-report)
25 68%
Pet Owner 4 11%
Foster Care Experience 3 8%
Formerly Incarcerated 13 35%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 23 62%
Jail Release 0 0%
Lack of Income 6 16%
Medical Discharge 0 0%
Mental Illness 1 3%
Runaway 0 0%
Substance Abuse 1 3%
Unemployment 1 3%
Other 7 19%
Living Situation - Night before the Count (interview) # % Abandoned Building 9 24%
Bus Station 0 0%
Encampment 9 24%
Park 3 8%
Street 5 14%
Tent/Shed 2 5%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 5 14%
Other 4 11%
Total 37 100% *Percentages do not add up to 100% due to rounding
Page | 115
TEMECULA
The City of Temecula experienced a 53% decrease in unsheltered homelessness between 2020 and 2022. The 2022 total included 8 persons who were homeless for the first time. The largest segment of unsheltered persons was found living in vehicles (42%) with the next largest group found on the street (32%), and the remainder in tents or sheds, or places not meant for human habitation. Over 50% of the interviewed persons were assessed as chronically homeless.
Like many other areas, adults and seniors comprised most unsheltered persons (93%) and the group was predominantly White (79%) and Multiple Races (7%) with males representing 54%, females 39% and (1) no single gender and (1) unknown completing the group. Nearly half reported substance abuse as a personal challenge, while 37% reported PTSD, 26% mental health issues, 21% chronic health condition, and developmental disability and physical disability each at 11%. Factors contributing to homelessness included family disruption and substance abuse (each at 21%), lack of income (16%), unemployment and other factors not listed (each at 11%), and runaway status at 5%.
CITY OF TEMECULA
Unsheltered Sheltered Total
28 39 67
.
UNSHELTERED
Category # % of City Count
Interviewed 19 68%
Observed 9 32%
Age (all) # %
Adults (25-59) 23 82%
Children (≤17) 0 0%
Seniors (≥ 60) 3 11%
Youth (18-24) 1 4%
Unknown Ages 1 4%
Total 28 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 0 0%
Asian, Asian American 0 0%
Black, African American, African 0 0%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 2 7%
White 22 79%
Unknown Race 4 14%
Total 28 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 7 25%
Non- Hispanic 19 68%
Unknown Ethnicity 2 7%
Total 28 100%
Gender (all) # %
Female 11 39%
Page | 116
Male 15 54%
No Single Gender 1 4%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 1 4%
Total 28 100%*
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 4 21%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 5 26%
Physical Disability 2 11%
PTSD 7 37%
Substance Abuse 9 47%
Traumatic Brain Injury 0 0%
Developmental Disability 2 11%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 10 53% Veterans 1 5%
First Time Homeless (self-report)
8 42%
Pet Owner 1 5%
Foster Care Experience 0 0%
Formerly Incarcerated 3 16%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 4 21%
Jail Release 0 0%
Lack of Income 3 16%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 1 5%
Substance Abuse 4 21%
Unemployment 2 11%
Other 2 11%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 3 16%
Park 0 0%
Street 6 32%
Tent/Shed 1 5%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 8 42%
Other 1 5%
Total 19 100%
*Percentages do not add up to 100% due to rounding
Page | 117
WILDOMAR
The unsheltered count in the City of Wildomar rose by 17% between 2020 and 2022. More than half (57%) of the unsheltered persons reported being homeless for the first time. Use of vehicles (57%) and abandoned buildings (29%) were the primary living situations for unsheltered persons who were interviewed.
The unsheltered population was exclusively adult, predominantly Hispanic (71%), and male (71%).
Unsheltered persons fell into three race categories: White and Multiple Race each at 43% with the remaining 14% being Black/African American/ African.
The most frequently cited challenging conditions were brain injury and substance abuse (29% each) with mental illness and Post-Traumatic Stress Disorder following at 14% each. The factors contributing to homelessness were equally distributed in most categories.
CITY OF WILDOMAR
Unsheltered Sheltered Total
7 14 21
.
UNSHELTERED
Category # % of Count
Interviewed 7 100%
Observed 0 0%
Age (all) # %
Adults (25-59) 6 86%
Children (≤17) 0 0%
Seniors (≥ 60) 1 14%
Youth (18-24) 0 0%
Unknown Ages 0 0%
Total 7 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 0 0%
Asian, Asian American 0 0%
Black, African American, African 1 14%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 3 43%
White 3 43%
Unknown Race 0 0%
Total 7 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 5 71%
Non- Hispanic 2 29%
Unknown Ethnicity 0 0%
Total 7 100%
Gender (all) # %
Female 2 29%
Male 5 71%
Page | 118
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 0 0%
Total 7 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 0 0%
Domestic Violence 1 14%
HIV AIDS 0 0%
Mental Health Issue 1 14%
Physical Disability 0 0%
PTSD 1 14%
Substance Abuse 2 29%
Traumatic Brain Injury 2 29%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 1 14% Veterans 0 0%
First Time Homeless (self-report)
4 57%
Pet Owner 1 14%
Foster Care Experience 0 0%
Formerly Incarcerated 1 14%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 1 14%
Jail Release 0 0%
Lack of Income 1 14%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 1 14%
Substance Abuse 1 14%
Unemployment 1 14%
Other 1 14%
Living Situation - Night before the Count (interview) # % Abandoned Building 2 29%
Bus Station 0 0%
Encampment 0 0%
Park 0 0%
Street 0 0%
Tent/Shed 0 0%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 4 57%
Other 1 14%
Total 7 100%
Page | 119
UNINCORPORATED AREA TABLES
Page | 120
UNINCORPORATED AREA- DISTRICT 1
Unincorporated area 1 experienced a 15% decrease in the number of unsheltered individuals compared to 2020. When compared to other areas, unincorporated area 1 had a lower percentage of chronically homeless persons and was largely comprised of adults, Whites, non-Hispanics, and males. For those interviewed, vehicle (65%) was the highest reported living situation with tents or shed (24%) second, and the remainder on the streets (12%).
UNINCORPORATED AREA- DISTRICT 1
Unsheltered 24
Sheltered 0
Total 24
UNSHELTERED
Category # % of Area Count
Interviewed 17 71%
Observed 7 29%
Age (all) # %
Adults (25-59) 17 71%
Children (≤17) 0 0%
Seniors (≥ 60) 5 21%
Youth (18-24) 0 0%
Unknown Ages 2 8%
Total 24 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 4%
Asian, Asian American 0 0%
Black, African American, African 5 21%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 2 8%
White 13 54%
Unknown Race 3 13%
Total 24 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 4 17%
Non- Hispanic 16 67%
Unknown Ethnicity 4 17%
Total 24 100%*
Gender (all) # %
Female 6 25%
Male 15 63%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 3 13%
Total 24 100%*
Page | 121
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 4 24%
Domestic Violence 0 0%
HIV AIDS 1 6%
Mental Health Issue 1 6%
Physical Disability 4 24%
PTSD 3 18%
Substance Abuse 6 35%
Traumatic Brain Injury 4 24%
Developmental Disability 2 12%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 9 53% Veterans 2 12%
First Time Homeless (self-report)
8 47%
Pet Owner 6 35%
Foster Care Experience 0 0%
Formerly Incarcerated 2 12%
Reasons for Homelessness (interviewed, not mutually exclusive) # % Family Disruption 5 29%
Jail Release 0 0%
Lack of Income 4 24%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 3 18%
Other 4 24%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 0 0%
Park 0 0%
Street 2 12%
Tent/Shed 4 24%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 11 65%
Other 0 0%
Total 17 100%*
*Percentages do not add up to 100% due to rounding
Page | 122
UNINCORPORATED AREA- DISTRICT 2
Unincorporated area 2 experienced a decrease of 13% in the number of unsheltered individuals compared to 2020. The unsheltered group was largely comprised of adults, Whites, non-Hispanics, and males. Unsheltered persons reported living in tents/sheds (32%), encampments (28%) or vehicles (28%) as the primary dwellings.
UNINCORPORATED AREA- DISTRICT 2
Unsheltered 27
Sheltered 0
Total 27
UNSHELTERED
Category # % of Area Count
Interviewed 25 93%
Observed 2 7%
Age (all) # %
Adults (25-59) 22 81%
Children (≤17) 1 4%
Seniors (≥ 60) 3 11%
Youth (18-24) 1 4%
Unknown Ages 0 0%
Total 27 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 4%
Asian, Asian American 0 0%
Black, African American, African 1 4%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 6 22%
White 16 59%
Unknown Race 3 11%
Total 27 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 8 30%
Non- Hispanic 18 67%
Unknown Ethnicity 1 4%
Total 27 100%*
Gender (all) # %
Female 10 37%
Male 17 63%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 0 0%
Total 27 100%
Page | 123
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 4 16%
Domestic Violence 0 0%
HIV AIDS 0 0%
Mental Health Issue 8 32%
Physical Disability 3 12%
PTSD 7 28%
Substance Abuse 8 32%
Traumatic Brain Injury 6 24%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 1 4%
Chronically Homeless (generated based on qualifying responses) 15 60% Veterans 0 0%
First Time Homeless (self-report)
6 24%
Pet Owner 8 32%
Foster Care Experience 0 0%
Formerly Incarcerated 1 4%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 10 40%
Jail Release 0 0%
Lack of Income 4 16%
Medical Discharge 1 4%
Mental Illness 0 0%
Runaway 2 8%
Substance Abuse 0 0%
Unemployment 3 12%
Other 4 16%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 7 28%
Park 1 4%
Street 2 8%
Tent/Shed 8 32%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 7 28%
Other 0 0%
Total 25 100%
*Percentages do not add up to 100% due to rounding
Page | 124
UNINCORPORATED AREA- DISTRICT 3
Unincorporated area 3 experienced a decrease of 11% in the number of unsheltered individuals compared to 2020. 53% of unsheltered individuals were identified as chronically homeless and the group was largely comprised of adults, Whites, non-Hispanics, and males. Unsheltered persons reported living in encampments (37%), vehicle (23%), and streets (13%) on the day of the homeless count.
UNINCORPORATED AREA- DISTRICT 3
Unsheltered 48
Sheltered 0
Total 48
UNSHELTERED
Category # % of Area Count
Interviewed 30 63%
Observed 18 38%
Age (all) # %
Adults (25-59) 44 92%
Children (≤17) 2 4%
Seniors (≥ 60) 1 2%
Youth (18-24) 0 0%
Unknown Ages 1 2%
Total 48 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 3 6%
Asian, Asian American 0 0%
Black, African American, African 8 17%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 8 17%
White 28 58%
Unknown Race 1 2%
Total 48 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 6 13%
Non- Hispanic 38 79%
Unknown Ethnicity 4 8%
Total 48 100%
Gender (all) # %
Female 16 33%
Male 31 65%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 1 2%
Total 48 100%
Page | 125
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 7 23%
Domestic Violence 1 3%
HIV AIDS 0 0%
Mental Health Issue 9 30%
Physical Disability 7 23%
PTSD 10 33%
Substance Abuse 16 53%
Traumatic Brain Injury 9 30%
Developmental Disability 8 27%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 1 3%
Chronically Homeless (generated based on qualifying responses) 16 53% Veterans 0 0%
First Time Homeless (self-report) 12 40%
Pet Owner 11 37%
Foster Care Experience 0 0%
Formerly Incarcerated 6 20%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 13 43%
Jail Release 1 3%
Lack of Income 3 10%
Medical Discharge 1 3%
Mental Illness 1 3%
Runaway 2 7%
Substance Abuse 4 13%
Unemployment 2 7%
Other 3 10%
Living Situation - Night before the Count (interview) # % Abandoned Building 2 7%
Bus Station 0 0%
Encampment 11 37%
Park 0 0%
Street 4 13%
Tent/Shed 6 20%
Tiny Home (without basic amenities) 0 0%
Under Bridge 0 0%
Vehicle 7 23%
Other 0 0%
Total 30 100%
*Percentages do not add up to 100% due to rounding
Page | 126
UNINCORPORATED AREA- DISTRICT 4
Unincorporated area 4 experienced a decrease of 22% in the number of unsheltered individuals compared to 2020. When compared with other areas, unincorporated area 4 had a similar percentage of chronically homeless persons (58%) and was largely comprised of adults, Whites, and males.
Encampment (46%) was the highest reported living situation followed by vehicle (19%).
UNINCORPORATED AREA- DISTRICT 4
Unsheltered 45
Sheltered 9
Total 54
UNSHELTERED
Category # % of Area Count
Interviewed 26 58%
Observed 19 42%
Age (all) # %
Adults (25-59) 33 73%
Children (≤17) 0 0%
Seniors (≥ 60) 6 13%
Youth (18-24) 2 4%
Unknown Ages 4 9%
Total 45 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 2%
Asian, Asian American 0 0%
Black, African American, African 5 11%
Native Hawaiian, Pacific Islander 1 2%
Multiple Races 1 2%
White 30 67%
Unknown Race 7 16%
Total 45 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 13 29%
Non- Hispanic 15 33%
Unknown Ethnicity 17 38%
Total 45 100%
Gender (all) # %
Female 10 22%
Male 29 64%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 6 13%
Total 45 100%*
Page | 127
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 2 8%
Domestic Violence 1 4%
HIV AIDS 0 0%
Mental Health Issue 8 31%
Physical Disability 6 23%
PTSD 5 19%
Substance Abuse 12 46%
Traumatic Brain Injury 2 8%
Developmental Disability 3 12%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 15 58% Veterans 2 8%
First Time Homeless (self-report)
6 23%
Pet Owner 3 12%
Foster Care Experience 1 4%
Formerly Incarcerated 3 12%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 6 23%
Jail Release 0 0%
Lack of Income 5 19%
Medical Discharge 0 0%
Mental Illness 2 8%
Runaway 1 4%
Substance Abuse 3 12%
Unemployment 4 15%
Other 4 15%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 12 46%
Park 0 0%
Street 1 4%
Tent/Shed 4 15%
Tiny Home (without basic amenities)
0 0%
Under Bridge 2 8%
Vehicle 5 19%
Other 2 8%
Total 26 100%
*Percentages do not add up to 100% due to rounding
Page | 128
UNINCORPORATED AREA- DISTRICT 5
Unincorporated area 5 experienced a decrease of 47% in the number of unsheltered individuals compared to 2020. Unincorporated area 5 reported the smallest unsheltered count among the unincorporated areas (8). Unincorporated area 5 did not report any chronically homeless persons and their demographics were comprised of adults, Whites, non-Hispanics, and males. Half of unsheltered persons reported staying in a vehicle (50%) followed by 1 person each staying in an encampment (17%), tent/shed (17%), and a tiny home (17%) on the day of the count.
UNINCORPORATED AREA- DISTRICT 5
Unsheltered 8
Sheltered 0
Total 8
UNSHELTERED
Category # % of Area Count
Interviewed 6 75%
Observed 2 25%
Age (all) # %
Adults (25-59) 7 88%
Children (≤17) 0 0%
Seniors (≥ 60) 1 13%
Youth (18-24) 0 0%
Unknown Ages 0 0%
Total 8 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 0 0%
Asian, Asian American 0 0%
Black, African American, African 2 25%
Native Hawaiian, Pacific Islander 1 13%
Multiple Races 0 0%
White 3 38%
Unknown Race 2 25%
Total 8 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 0 0%
Non- Hispanic 5 63%
Unknown Ethnicity 3 38%
Total 8 100%*
Gender (all) # %
Female 1 13%
Male 7 88%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Total 8 100%*
Page | 129
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 2 33%
Domestic Violence 1 17%
HIV AIDS 0 0%
Mental Health Issue 1 17%
Physical Disability 1 17%
PTSD 1 17%
Substance Abuse 0 0%
Traumatic Brain Injury 1 17%
Developmental Disability 0 0%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 0 0% Veterans 0 0%
First Time Homeless (self-report)
4 67%
Pet Owner 1 17%
Foster Care Experience 0 0%
Formerly Incarcerated 1 17%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 0 0%
Jail Release 0 0%
Lack of Income 1 17%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 0 0%
Unemployment 1 17%
Other 2 33%
Living Situation - Night before the Count (interview) # % Abandoned Building 0 0%
Bus Station 0 0%
Encampment 1 17%
Park 0 0%
Street 0 0%
Tent/Shed 1 17%
Tiny Home (without basic amenities)
1 17%
Under Bridge 0 0%
Vehicle 3 50%
Other 0 0%
Total 6 100%*
*Percentages do not add up to 100% due to rounding
Page | 130
SUPERVISORY DISTRICT PITC SUMMARY TABLES
SUPERVISORIAL DISTRICT DATA SUMMARIES
Page | 131
SUPERVISORY DISTRICT PITC SUMMARY TABLES
SUPERVISORIAL DISTRICT DATA SUMMARIES
There are five (5) Supervisorial Districts within the boundaries of the Riverside CoC and no two jurisdictions are identical. The geography ranges from densely populated urban areas to remote mountains and deserts. The Point-in-Time Count (PITC) for Districts range from 227 to 670 for unsheltered and 39 to 452 for sheltered homeless persons and total PITC of 289 in District 5 to 1094 in District 4. Details for the unsheltered population are found in the tables below. There was no unsheltered count in 2021 due to concerns about COVID-19.
Change in Unsheltered PIT Count for Each District Between 2020 and 2022 DISTRICT 1
2020 2022 Increase/Decrease
Jurisdiction # % # % # %
Canyon Lake 0 0% 0 0% 0 0%
Lake Elsinore 50 11% 35 9% -15 -30%
Riverside 341 77% 307 82% -34 -10%
Wildomar 6 1% 7 2% 1 17%
Unincorporated 1 44 10% 24 6% -20 -46%
Total: 441 100%* 373 100%* -68 -15%
*Percentages do not add up to 100% due to rounding
DISTRICT 2
2020 2022 Increase/Decrease
Jurisdiction # % # % # %
Corona 109 22% 110 24% 1 1%
Eastvale 4 1% 6 1% 2 50%
Jurupa Valley 103 20% 96 21% -7 -7%
Norco 12 2% 14 3% 2 17%
Riverside 246 49% 207 45% -39 -16%
Unincorporated 2 31 6% 27 6% -4 -13%
Total: 505 100% 460 100% -45 -8.90%
Page | 132
SUPERVISORY DISTRICT PITC SUMMARY TABLES
District 3
2020 2022 Increase/Decrease
Jurisdiction # % # % # %
Hemet 93 37% 82 36% -11 -11.80%
Murrieta 18 7% 12 5% -6 -33.30%
San Jacinto 31 12% 57 25% 26 83.90%
Temecula 59 23% 28 12% -31 -52.50%
Unincorporated 3 54 21% 48 21% -6 -11.10%
Total: 255 100% 227 100% -28 -11.00%
.
District 4
2020 2022 Increase/Decrease
Jurisdiction # % # % # %
Blythe 73 12% 79 12% 6 8.%
Cathedral City 44 7% 61 9% 17 39%
Coachella 78 12% 74 11% -4 -5%
Desert Hot Springs 68 11% 48 7% -20 -29%
Indian Wells 1 0% 0 0% -1 -100%
Indio 83 13% 105 16% 22 27%
La Quinta 3 1% 7 1% 4 133%
Palm Desert 18 3% 26 4% 8 44%
Palm Springs 189 30% 222 33% 33 18%
Rancho Mirage 12 2% 3 0% -9 -75%
Unincorporated 4 58 9% 45 7% -13 -22%
Total 627 100% 670 100% 43 6.90%
.
District 5
2020 2022 Increase/Decrease
Jurisdiction # % # % # %
Banning 43 13% 54 22% 11 26%
Beaumont 16 5% 16 6% 0 0.00%
Calimesa 17 5% 8 3% -9 -53%
Menifee 19 6% 28 11% 9 47%
Moreno Valley 165 51% 77 31% -88 -53%
Perris 52 16% 59 24% 7 14%
Unincorporated 5 15 5% 8 3% -7 -47%
Total 327 100%* 250 100% -77 -23.50%
*Percentages do not add up to 100% due to rounding
Page | 133
SUPERVISORY DISTRICT PITC SUMMARY TABLES
RACE (all) District 1 District 2 District 3 District 4 District 5 Total American Indian 7 5 11 15 14 52
Asian, Asian American 4 6 1 3 6 20
Black, AA, African 65 67 30 61 42 265
Multiple Race 33 48 30 61 24 196
Native Hawaiian, Pacific
Islander 1 3 1 3 4 12
White 192 233 129 403 109 1066
Unknown Race 71 98 25 124 51 369
Total 373 460 227 670 250 1980
GENDER (all) District 1 District 2 District 3 District 4 District 5 Total Female 89 116 70 162 62 499
No Single Gender 0 2 1 2 0 5
Male 249 278 148 449 173 1297
Questioning 0 0 0 0 2 2
Transgender 1 1 0 0 0 2
Unknown Gender 34 63 8 57 13 175
Total 373 460 227 670 250 1980
AGE GROUP BY SD (all) District 1 District 2 District 3 District 4 District 5 Total Child (≤17) 3 2 4 1 0 10
Youth 18-24 61 55 22 57 42 237
Adults (25-59) 239 302 176 505 163 1385
Senior 60+ 30 30 17 46 27 150
Unknown Ages 40 71 8 61 18 198
Total 373 460 227 670 250 1980
Page | 134
SUPERVISORY DISTRICT PITC SUMMARY TABLES
Living Situation (Interview) District 1 District 2 District 3 District 4 District 5 Total Abandoned Building 6 14 16 24 11 71
Bus 4 0 0 5 0 9
Encampment 14 56 31 45 27 173
Other 16 9 9 26 17 77
Park 9 16 5 10 4 44
Street 88 59 49 112 45 353
Tent /Shed 19 59 17 64 33 192
Tiny Home (without basic
amenities) 0 2 0 0 1 3
Under Bridge 2 3 0 8 0 13
Vehicle 44 43 27 45 25 184
Total 202 261 154 339 163 1119
Special Interest Questions
(interview) District 1 District 2 District 3 District 4 District 5 Total First Time Homeless 78 94 76 114 61 423
Pet Owner 33 68 25 48 23 197
Foster Care 3 2 4 6 8 23
Formerly Incarcerated 44 48 38 43 36 209
Challenges & Barriers
(Interview, not mutually
exclusive)
District 1 District 2 District 3 District 4 District 5 Total Chronic Health 42 53 36 80 29 240
Domestic Violence Victim 16 9 11 20 6 62
HIV/AIDS 4 2 1 7 2 16
Mental Health Issue 63 62 48 95 32 300
Physical Disability 45 43 34 73 31 226
Post -Traumatic Stress 57 68 56 87 29 297
Substance Abuse 81 87 70 135 51 424
Brain Injury 45 34 30 53 24 186
Developmental Disability 22 39 24 44 16 145
Page | 135
SUPERVISORY DISTRICT PITC SUMMARY TABLES
SUPERVISORIAL DISTRICT SUMMARY TABLES
Page | 136
SUPERVISORY DISTRICT PITC SUMMARY TABLES
SUPERVISORIAL DISTRICT 1
Unsheltered: 373
Sheltered: 452
TOTAL 825
UNSHELTERED
Category # % of Count
Interviewed 202 54%
Observed 171 46%
Age (all) # %
Adults (25-59)
239 64%
Children (≤17) 3 1%
Seniors (≥ 60) 30 8%
Youth (18-24) 61 16%
Unknown Ages 40 11%
Total 373 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 7 2%
Asian, Asian American 4 1%
Black, African American, African 65 17%
Native Hawaiian, Pacific Islander 1 0%
Multiple Races 33 9%
White 192 51%
Unknown Race 71 19%
Total 373 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 100 27%
Non- Hispanic 166 45%
Unknown Ethnicity 107 29%
Total 373 100%*
Gender (all ) # %
Female 89 24%
Male 249 67%
No Single Gender 0 0%
Questioning 0 0%
Transgender 1 0%
Unknown Gender 34 9%
Total 373 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 42 21%
Domestic Violence 16 8%
HIV AIDS 4 2%
Mental Health Issue 63 31%
Page | 137
SUPERVISORY DISTRICT PITC SUMMARY TABLES
*Percentages do not add up to 100% due to rounding
Physical Disability 45 22%
PTSD 57 28%
Substance Abuse 81 40%
Traumatic Brain Injury 45 22%
Developmental Disability 22 11%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 2 1%
Chronically Homeless (generated based on qualifying responses) 118 58% Veterans 19 9%
First Time Homeless (self-report)
78 39%
Pet Owner 33 16%
Foster Care Experience 3 1%
Formerly Incarcerated 44 22%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 69 34%
Jail Release 6 3%
Lack of Income 32 16%
Medical Discharge 0 0%
Mental Illness 3 1%
Runaway 4 2%
Substance Abuse 12 6%
Unemployment 23 11%
Other 42 21%
Living Situation - Night before the Count (interview) # % Abandoned Building 6 3%
Bus Station 4 2%
Encampment 14 7%
Park 9 4%
Street 88 44%
Tent/Shed 19 9%
Tiny Home (without basic amenities)
0 0%
Under Bridge 2 1%
Vehicle 44 22%
Other 16 8%
Total 202 100%
Page | 138
SUPERVISORY DISTRICT PITC SUMMARY TABLES
SUPERVISORIAL DISTRICT 2
Unsheltered: 460
Sheltered: 129
TOTAL 589
UNSHELTERED
Category # % of Count
Interviewed 261 57%
Observed 199 43%
Age (all) # %
Adults (25-59)
302 66%
Children (≤17) 2 0%
Seniors (≥ 60) 30 7%
Youth (18-24) 55 12%
Unknown Age 71 15%
Total 460 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 5 1%
Asian, Asian American 6 1%
Black, African American, African 67 15%
Native Hawaiian, Pacific Islander 3 1%
Multiple Races 48 10%
White 233 51%
Unknown Race 98 21%
Total 460 100%
Ethnicity (all) # %
Hispanic, Latin(o) (a), (x) 137 30%
Non- Hispanic 194 42%
Unknown Ethnicity 129 28%
Total 460 100%
Gender (all) # %
Female 116 25%
Male 278 60%
No Single Gender 2 0%
Questioning 0 0%
Transgender 1 0%
Unknown Gender 63 14%
Total 460 100%*
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 53 20%
Domestic Violence 9 3%
HIV AIDS 2 1%
Mental Health Issue 62 24%
Page | 139
SUPERVISORY DISTRICT PITC SUMMARY TABLES
*Percentages do not add up to 100% due to rounding
Physical Disability 43 16%
PTSD 68 26%
Substance Abuse 87 33%
Traumatic Brain Injury 34 13%
Developmental Disability 39 15%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 2 1%
Chronically Homeless (generated based on qualifying responses) 124 48% Veterans 27 10%
First Time Homeless (self-report)
94 36%
Pet Owner 68 26%
Foster Care Experience 2 1%
Formerly Incarcerated 48 18%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 84 32%
Jail Release 5 2%
Lack of Income 36 14%
Medical Discharge 4 2%
Mental Illness 11 4%
Runaway 11 4%
Substance Abuse 18 7%
Unemployment 28 11%
Other 38 15%
Living Situation - Night before the Count (interview) # % Abandoned Building 14 5%
Bus Station 0 0%
Encampment 56 21%
Park 16 6%
Street 59 23%
Tent/Shed 59 23%
Tiny Home (without basic amenities)
2 1%
Under Bridge 3 1%
Vehicle 43 16%
Other 9 3%
Total 261 100%*
Page | 140
SUPERVISORY DISTRICT PITC SUMMARY TABLES
SUPERVISORIAL DISTRICT 3
Unsheltered: 227
Sheltered: 292
TOTAL 519
UNSHELTERED
Category # % of Count
Interviewed 154 68%
Observed 73 32%
Age (all) # %
Adults (25-59)
176 78%
Children (≤17) 4 2%
Seniors (≥ 60) 17 7%
Youth (18-24) 22 10%
Unknown Ages 8 4%
Total 227 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 11 5%
Asian, Asian American 1 0%
Black, African American, African 30 13%
Native Hawaiian, Pacific Islander 1 0%
Multiple Races 30 13%
White 129 57%
Unknown Race 25 11%
Total 227 100%*
Ethnicity (all) # %
Hispanic, Latin(o) (a), (x) 60 26%
Non- Hispanic 145 64%
Unknown Ethnicity 22 10%
Total 227 100%
Gender (all) # %
Female 70 31%
Male 148 65%
No Single Gender 1 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 8 4%
Total 227 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 36 23%
Domestic Violence 11 7%
HIV AIDS 1 1%
Mental Health Issue 48 31%
Physical Disability 34 22%
Page | 141
SUPERVISORY DISTRICT PITC SUMMARY TABLES
*Percentages do not add up to 100% due to rounding
PTSD 56 36%
Substance Abuse 70 45%
Traumatic Brain Injury 30 19%
Developmental Disability 24 16%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 3 2%
Chronically Homeless (generated based on qualifying responses)
84 55%
Veterans 7 5%
First Time Homeless (self-report)
76 49%
Pet Owner 25 16%
Foster Care Experience 4 3%
Formerly Incarcerated 38 25%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 67 44%
Jail Release 5 3%
Lack of Income 30 19%
Medical Discharge 2 1%
Mental Illness 2 1%
Runaway 6 4%
Substance Abuse 14 9%
Unemployment 8 5%
Other 18 12%
Living Situation - Night before the Count (interview) # % Abandoned Building 16 10%
Bus Station 0 0%
Encampment 31 20%
Park 5 3%
Street 49 32%
Tent/Shed 17 11%
Tiny Home (without basic amenities)
0 0%
Under Bridge 0 0%
Vehicle 27 18%
Other 9 6%
Total 154 100%
Page | 142
SUPERVISORY DISTRICT PITC SUMMARY TABLES
SUPERVISORIAL DISTRICT 4
Unsheltered: 670
Sheltered: 424
TOTAL 1094
UNSHELTERED
Category # % of Count
Interviewed 339 51%
Observed 331 49%
Age (all) # %
Adults (25-59)
505 75%
Children (≤17) 1 0%
Seniors (≥ 60) 46 7%
Youth (18-24) 57 9%
Unknown Ages 61 9%
Total 670 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 15 2%
Asian, Asian American 3 0%
Black, African American, African 61 9%
Native Hawaiian, Pacific Islander 3 0%
Multiple Races 61 9%
White 403 60%
Unknown Race 124 19%
Total 670 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 212 32%
Non- Hispanic 297 44%
Unknown Ethnicity 161 24%
Total 670 100%
Gender (all) # %
Female 162 24%
Male 449 67%
No Single Gender 2 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 57 9%
Total 670 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 80 24%
Domestic Violence 20 6%
HIV AIDS 7 2%
Mental Health Issue 95 28%
Page | 143
SUPERVISORY DISTRICT PITC SUMMARY TABLES
Physical Disability 73 22%
PTSD 87 26%
Substance Abuse 135 40%
Traumatic Brain Injury 53 16%
Developmental Disability 44 13%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 2 1%
Chronically Homeless (generated based on qualifying responses)
162 48%
Veterans 30 9%
First Time Homeless (self-report)
114 34%
Pet Owner 48 14%
Foster Care Experience 6 2%
Formerly Incarcerated 43 13%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 94 28%
Jail Release 8 2%
Lack of Income 64 19%
Medical Discharge 4 1%
Mental Illness 8 2%
Runaway 10 3%
Substance Abuse 40 12%
Unemployment 42 12%
Other 52 15%
Living Situation - Night before the Count (interview) # % Abandoned Building 24 7%
Bus Station 5 1%
Encampment 45 13%
Park 10 3%
Street 112 33%
Tent/Shed 64 19%
Tiny Home (without basic amenities)
0 0%
Under Bridge 8 2%
Vehicle 45 13%
Other 26 8%
Total 339 100%*
*Percentages do not add up to 100% due to rounding
Page | 144
SUPERVISORY DISTRICT PITC SUMMARY TABLES
SUPERVISORIAL DISTRICT 5
Unsheltered: 250
Sheltered: 39
TOTAL 289
UNSHELTERED
Category # % of Count
Interviewed 163 65%
Observed 87 35%
Age (all) # %
Adults (25-59)
163 65%
Children (≤17) 0 0%
Seniors (≥ 60) 27 11%
Youth (18-24) 42 17%
Unknown Ages 18 7%
Total 250 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 14 6%
Asian, Asian American 6 2%
Black, African American, African 42 17%
Native Hawaiian, Pacific Islander 4 2%
Multiple Races 24 10%
White 109 44%
Unknown Race 51 20%
Total 250 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 83 33%
Non- Hispanic 119 48%
Unknown Ethnicity 48 19%
Total 250 100*
Gender (all) # %
Female 62 25%
Male 173 69%
No Single Gender 0 0%
Questioning 2 1%
Transgender 0 0%
Unknown Gender 13 5%
Total 250 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 29 18%
Domestic Violence 6 4%
HIV AIDS 2 1%
Mental Health Issue 32 20%
Page | 145
SUPERVISORY DISTRICT PITC SUMMARY TABLES
Physical Disability 31 19%
PTSD 29 18%
Substance Abuse 51 31%
Traumatic Brain Injury 24 15%
Developmental Disability 16 10%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses)
72 44%
Veterans 8 5%
First Time Homeless (self-report)
61 37%
Pet Owner 23 14%
Foster Care Experience 8 5%
Formerly Incarcerated 36 22%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 57 35%
Jail Release 6 4%
Lack of Income 17 10%
Medical Discharge 1 1%
Mental Illness 6 4%
Runaway 9 6%
Substance Abuse 2 1%
Unemployment 17 10%
Other 34 21%
Living Situation - Night before the Count (interview) # % Abandoned Building 11 7%
Encampment 27 17%
Park 4 2%
Street 45 28%
Tent/Shed 33 20%
Tiny Home (without basic amenities)
1 1%
Vehicle 25 15%
Other 17 10%
Total 163 100%
*Percentages do not add up to 100% due to rounding
Page | 146
SUBPOPULATIONS AND POPULATIONS OF INTEREST
Page | 147
FAMILIES WITH CHILDREN
Unsheltered 29
Sheltered 461
Total 490
UNSHELTERED
Category # % of Group
Count
Interviewed (known) 22 76%
Observed 7 24%
Age (all) # %
Adults (25-59) 14 48%
Children (≤17) 11 38%
Seniors (≥ 60) 0 0%
Youth (18-24) 3 10%
Unknown Age 1 3%
Total 29 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 0 0%
Asian, Asian American 0 0%
Black, African American, African 6 21%
Native Hawaiian, Pacific Islander 1 3%
Multiple Races 3 10%
White 19 66%
Unknown Race 0 0%
Total 29 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 8 28%
Non- Hispanic 21 72%
Unknown Ethnicity 0 0%
Total 29 100%
Gender (all) # %
Female 12 41%
Male 16 55%
Unknown Gender 1 3%
Total 29 100%*
Household Type (interview) # %
Family Households 9 100%
Persons in Families 29 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 1 5%
Page | 148
Domestic Violence 0 0%
HIV/AIDS 1 5%
Mental Health Issue 1 5%
Physical Disability 0 0%
PTSD 2 9%
Substance Abuse 2 9%
Traumatic Brain Injury 0 0%
Developmental Disability 1 5%
Special Interest Questions (interview, not mutually exclusive) # % First Time Homeless (self-report) 7 32%
Pet Owner 4 18%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 9 41%
Jail Release 0 0%
Lack of Income 0 0%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 1 5%
Substance Abuse 0 0%
Unemployment 0 0%
Other 2 9%
Living Situation - Night before the Count (interview) # % Abandoned Building 2 9%
Bus Station 0 0%
Encampment 0 0%
Park 0 0%
Street 0 0%
Tent/Shed 3 14%
Tiny Home (without basic amenities) 0 0%
Under Bridge 0 0%
Vehicle 2 9%
Other 4 18%
Unknown 11 50%
Total 22 100%
*Percentages do not add up to 100% due to rounding
Page | 149
TRANSITIONAL AGE YOUTH (18 – 24 years)
Unsheltered 237
Sheltered 75
Total 312
UNSHELTERED
Category # % of Group
Count
Interviewed 69 29%
Observed 168 71%
Age (all) # %
Adults (25 - 59) 0 0%
Children (≤17) 0 0%
Seniors (≥ 60) 0 0%
Youth (18-24) 237 100%
Unknown Ages 0 0%
Total 237 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 0%
Asian, Asian American 1 0%
Black, African American, African 47 20%
Native Hawaiian, Pacific Islander 2 1%
Multiple Races 33 14%
White 136 58%
Unknown Race 17 7%
Total 237 100%
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 88 37%
Non- Hispanic 77 32%
Unknown Ethnicity 72 30%
Total 237 100%*
Gender (all) # %
Female 92 39%
Male 142 60%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 3 1%
Total 237 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 7 10%
Domestic Violence 4 6%
HIV AIDS 0 0%
Mental Health Issue 23 33%
Page | 150
Physical Disability 3 4%
PTSD 22 32%
Substance Abuse 16 23%
Traumatic Brain Injury 5 7%
Developmental Disability 7 10%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 25 36% Veterans 0 0%
First Time Homeless (self-report) 37 54%
Pet Owner 9 13%
Foster Care Experience 23 33%
Formerly Incarcerated 30 43%
Pregnant 6 9%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 31 45%
Jail Release 0 0%
Lack of Income 7 10%
Medical Discharge 0 0%
Mental Illness 2 3%
Runaway 8 12%
Substance Abuse 7 10%
Unemployment 2 3%
Other 8 12%
Living Situation - Night before the Count (interview) # % Abandoned Building 5 7%
Bus Station 0 0%
Encampment 8 12%
Park 2 3%
Street 23 33%
Tent/Shed 5 7%
Tiny Home (without basic amenities) 0 0%
Under Bridge 1 1%
Vehicle 17 25%
Other 8 12%
Total 69 100%
Last Grade Completed (interview) # %
Some College 7 10%
GED 3 4%
High School (grade 12) 36 52%
Some High School (grades 9-11) 15 22%
Middle School (grades 7-8) 1 1%
No Grades Completed 1 1%
Doesn’t Know 6 9%
Total 69 100%*
*Percentages do not add up to 100% due to rounding
Page | 151
SENIORS (≥60)
Unsheltered 150
Sheltered 173
Total 323
UNSHELTERED
Category # % of Group Count
Interviewed 150 100%
Observed NA
Age (all) # %
Seniors (≥ 60) 150 100%
Total 150 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 9 6%
Asian, Asian American 2 1%
Black, African American, African 18 12%
Native Hawaiian, Pacific Islander 1 1%
Multiple Races 16 11%
White 100 67%
Unknown Race 4 3%
Total 150 100%*
Ethnicity (all) # %
Hispanic, Latin(o) (a), (x) 47 31%
Non- Hispanic 102 68%
Unknown Ethnicity 1 1%
Total 150 100%
Gender (all) # %
Female 34 23%
Male 115 77%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 1 1%
Total 150 100%*
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 47 31%
Domestic Violence 3 2%
HIV AIDS 2 1%
Mental Health Issue 32 21%
Physical Disability 51 34%
PTSD 25 17%
Substance Abuse 40 27%
Page | 152
Traumatic Brain Injury 24 16%
Developmental Disability 23 15%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses) 77 51% Veterans 27 18%
First Time Homeless (self-report) 44 29%
Pet Owner 25 17%
Foster Care Experience 0 0%
Formerly Incarcerated 11 7%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 31 21%
Jail Release 7 5%
Lack of Income 42 28%
Medical Discharge 3 2%
Mental Illness 3 2%
Runaway 1 1%
Substance Abuse 5 3%
Unemployment 21 14%
Other 30 20%
Living Situation - Night before the Count (interview) # % Abandoned Building 11 7%
Bus Station 1 1%
Encampment 17 11%
Park 6 4%
Street 40 27%
Tent/Shed 21 14%
Tiny Home (without basic amenities) 0 0%
Under Bridge 0 0%
Vehicle 46 31%
Other 8 5%
Total 150 100%
NA: Age category for seniors 60+ is not collected by observational survey *Percentages do not add up to 100% due to rounding
Page | 153
VETERANS
Table below includes actual count numbers not extrapolated numbers (146) UNSHELTERED (interview only)
Unsheltered 77
Sheltered 49
Total 126
Category # % of Group
Count
Interviewed 77 100%
Observed NA
Age (all) # %
Adults (25 - 59) 50 65%
Children (≤17) 0 0%
Seniors (≥ 60) 27 35%
Youth (18-24) 0 0%
Unknown Ages 0 0%
Total 77 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 6 8%
Asian, Asian American 1 1%
Black, African American, African 19 25%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 8 10%
White 38 49%
Unknown Race 5 6%
Total 77 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 19 25%
Non- Hispanic 58 75%
Unknown Ethnicity 0 0%
Total 77 100%
Gender (all) # %
Female 6 8%
Male 70 91%
No Single Gender 0 0%
Questioning 0 0%
Transgender 0 0%
Unknown Gender 1 1%
Total 77 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 18 23%
Domestic Violence 0 0%
HIV AIDS 1 1%
Mental Health Issue 23 30%
Physical Disability 21 27%
Page | 154
PTSD 27 35%
Substance Abuse 26 34%
Traumatic Brain Injury 26 34%
Developmental Disability 10 13%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless generated based on qualifying responses)
43 56%
Veterans 77 100%
First Time Homeless (self-report) 20 26%
Pet Owner 9 12%
Foster Care Experience 0 0%
Formerly Incarcerated 12 16%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 18 23%
Jail Release 6 8%
Lack of Income 17 22%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 0 0%
Substance Abuse 5 6%
Unemployment 13 17%
Other 13 17%
Living Situation - Night before the Count (interview) # % Abandoned Building 4 5%
Bus Station 1 1%
Encampment 9 12%
Park 1 1%
Street 25 32%
Tent/Shed 13 17%
Tiny Home (without basic amenities) 0 0%
Under Bridge 0 0%
Vehicle 19 25%
Other 5 6%
Total 77 100%*
NA: Veteran status not collected by observational survey *Percentages do not add up to 100% due to rounding
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SUB-POPULATIONS OF INTEREST
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CHRONICALLY HOMELESS
UNSHELTERED
Unsheltered 560
Sheltered 256
Total 816
Category # % of Group
Count
Interviewed 560 100%
Observed NA
Age (all) # %
Adults (25-59) 458 82%
Children (≤17) 0 0%
Seniors (≥ 60) 77 14%
Youth (18-24) 25 4%
Unknown Ages 0 0%
Total 560 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 26 5%
Asian, Asian American 3 1%
Black, African American, African 65 12%
Native Hawaiian, Pacific Islander 3 1%
Multiple Races 66 12%
White 362 65%
Unknown Race 35 6%
Total 560 100%*
Ethnicity (all) # %
Hispanic, Latin(o), (a), (x) 201 36%
Non- Hispanic 358 64%
Unknown Ethnicity
1 0%
Total 560 100%
Gender (all) # %
Female 151 27%
Male 401 72%
No Single Gender 4 1%
Questioning 0 0%
Transgender 2 0%
Unknown Gender 2 0%
Total 560 100%
Challenges / Barriers (interview, not mutually exclusive) # % Chronic Health Issue 156 28%
Domestic Violence 42 8%
HIV AIDS 12 2%
Mental Health Issue 252 45%
Physical Disability 179 32%
PTSD 224 40%
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Substance Abuse 360 64%
Traumatic Brain Injury 137 24%
Developmental Disability 121 22%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 0 0%
Chronically Homeless (generated based on qualifying responses)
560 100%
Veterans 43 8%
First Time Homeless (self-report) NA 0%
Pet Owner 101 18%
Foster Care Experience 11 2%
Formerly Incarcerated 118 21%
Reasons for Homelessness (interview, not mutually exclusive) # % Family Disruption 218 39%
Jail Release 19 3%
Lack of Income 87 16%
Medical Discharge 5 1%
Mental Illness 19 3%
Runaway 19 3%
Substance Abuse 61 11%
Unemployment 44 8%
Other 73 13%
Living Situation - Night before the Count (interview) # % Abandoned Building 31 6%
Bus Station 3 1%
Encampment 99 18%
Park 17 3%
Street 199 36%
Tent/Shed 88 16%
Tiny Home (without basic amenities) 2 0%
Under Bridge 8 1%
Vehicle 81 14%
Other 32 6%
Total 560 100%*
NA: Chronic Homelessness is not collected by observational survey *Percentages do not add up to 100% due to rounding
Page | 158
FIRST TIME HOMELESS
UNSHELTERED
Unsheltered 423
Sheltered 0
Total 423
Category # % of Group
Count
Interviewed 423 100%
Observed NA
Age (all) # %
Adults (25 - 59) 341 81%
Children (≤17) 1 0%
Seniors (≥ 60) 44 10%
Youth (18-24) 37 9%
Unknown Ages 0 0%
Total 423 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 19 4%
Asian, Asian American 7 2%
Black, African American, African 54 13%
Native Hawaiian, Pacific Islander 4 1%
Multiple Races 52 12%
White 240 57%
Unknown Race 47 11%
Total 423 100%
Ethnicity (all) # %
Hispanic, Latin(o) (a), (x) 197 47%
Non-Hispanic 220 52%
Unknown Ethnicity 6 1%
Total 423 100%
Gender (all) # %
Female 122 29%
Male 294 70%
No Single Gender 4 1%
Questioning 0 0%
Transgender 1 0%
Unknown Gender 2 0%
Total 423 100%
Challenges / Barriers (interview not mutually exclusive) # % Chronic Health Issue 83 20%
Domestic Violence 22 5%
HIV AIDS 4 1%
Mental Health Issue 106 25%
Physical Disability 78 18%
PTSD 110 26%
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Substance Abuse 141 33%
Traumatic Brain Injury 59 14%
Developmental Disability 52 12%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 7 2%
Chronically Homeless (generated based on qualifying responses)
174 41%
Veterans 20 5%
First Time Homeless (self-report) 423 100%
Pet Owner 70 17%
Foster Care Experience 11 3%
Formerly Incarcerated 88 21%
Reasons for Homelessness (interview not mutually exclusive) # % Family Disruption 127 30%
Jail Release 13 3%
Lack of Income 83 20%
Medical Discharge 6 1%
Mental Illness 11 3%
Runaway 16 4%
Substance Abuse 29 7%
Unemployment 44 10%
Other 77 18%
Living Situation - Night before the Count (interview) # % Abandoned Building 26 6%
Bus Station 3 1%
Encampment 70 17%
Park 19 4%
Street 117 28%
Tent/Shed 71 17%
Tiny Home (without basic amenities) 3 1%
Under Bridge 3 1%
Vehicle 78 18%
Other 31 7%
Unknown 2 0%
Total 423 100%
NA: First Time Homeless data is not collected by observational survey
Page | 160
FORMERLY INCARCERATED
UNSHELTERED
Unsheltered 209
Sheltered 0
Total 209
Category # % of Group
Count
Interviewed 209 100%
Observed NA
Age (all) # %
Adults (25 - 59) 186 89%
Children (≤17) 0 0%
Seniors (≥ 60) 11 5%
Youth (18-24) 12 6%
Unknown Ages 0 0%
Total 209 100%
Race (all) # %
American Indian, Alaskan Native, Indigenous 11 5%
Asian, Asian American 2 1%
Black, African American, African 24 11%
Native Hawaiian, Pacific Islander 1 0%
Multiple Races 26 12%
White 130 62%
Unknown Race 15 7%
Total 209 100%*
Ethnicity (all) # %
Hispanic, Latin(o) (a), (x) 94 45%
Non-Hispanic 112 54%
Unknown Ethnicity 3 1%
Total 209 100%
Gender (all) # %
Female 46 22%
Male 158 76%
No Single Gender 1 0%
Questioning 1 0%
Transgender 1 0%
Unknown Gender 2 1%
Total 209 100%*
Challenges / Barriers (interview not mutually exclusive) # % Chronic Health Issue 52 25%
Domestic Violence 10 5%
HIV AIDS 4 2%
Mental Health Issue 64 31%
Physical Disability 44 21%
PTSD 60 29%
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Substance Abuse 109 52%
Traumatic Brain Injury 39 19%
Developmental Disability 24 11%
Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 1 0%
Chronically Homeless (generated based on qualifying responses)
118 56%
Veterans 12 6%
First Time Homeless (self-report) 88 42%
Pet Owner 23 11%
Foster Care Experience 6 3%
Formerly Incarcerated 209 100%
Reasons for Homelessness (interview not mutually exclusive) # % Family Disruption 77 37%
Jail Release 16 8%
Lack of Income 20 10%
Medical Discharge 4 2%
Mental Illness 6 3%
Runaway 4 2%
Substance Abuse 27 13%
Unemployment 19 9%
Other 33 16%
Living Situation - Night before the Count (interview) # % Abandoned Building 17 8%
Bus Station 0 0%
Encampment 33 16%
Park 10 5%
Street 82 39%
Tent/Shed 33 16%
Tiny Home (without basic amenities) 1 0%
Under Bridge 1 0%
Vehicle 14 7%
Other 18 9%
Total 209 100%
NA: Formerly Incarcerated data is not collected by observational survey *Percentages do not add up to 100% due to rounding
Page | 162
COUCH SURFERS
UNSHELTERED
Category # % of Group
Count
Interviewed 31 100%
Observed NA
Age (all) # %
Adults (25-59) 13 42%
Youth (18-24) 12 39%
Children (≤17) 3 10%
Seniors (≥ 60) 3 10%
Unknown Ages 0 0%
Total 31 100%*
Race (all) # %
American Indian, Alaskan Native, Indigenous 1 3%
Asian, Asian American 0 0%
Black, African American, African 4 13%
Native Hawaiian, Pacific Islander 0 0%
Multiple Races 9 29%
White 13 42%
Unknown Race 4 13%
Total 31 100%*
Ethnicity (all) # %
Hispanic, Latino (a), (x) 22 71%
Non- Hispanic 9 29%
Unknown Ethnicity 0 0%
Total 31 100%
Gender (all) # %
Female 9 29%
Male 21 68%
No Single Gender 0 0%
Questioning 0 0%
Transgender 1 3%
Unknown Gender 0 0%
Total 31 100%
Challenges / Barriers (interview not mutually exclusive) # % Chronic Health Issue 3 10%
Domestic Violence 2 6%
HIV AIDS 0 0%
Mental Health Issue 11 35%
Physical Disability 7 23%
Post-Traumatic Stress 7 23%
Substance Abuse 9 29%
Traumatic Brain Injury 3 10%
Developmental Disability 6 19%
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Special Interest Questions (interview, not mutually exclusive) # % Families’ w/ Children 1 3%
Chronically Homeless (generated based on qualifying responses)
13 42%
Veterans 3 10%
First Time Homeless (self-report) 12 39%
Pet Owner 4 13%
Foster Care Experience 7 23%
Formerly Incarcerated 3 10%
Reasons for Homelessness (interview not mutually exclusive) # % Family Disruption 14 45%
Jail Release 1 3%
Lack of Income 4 13%
Medical Discharge 0 0%
Mental Illness 0 0%
Runaway 1 3%
Substance Abuse 1 3%
Unemployment 2 6%
Other 6 19%
Living Situation - Night before the Count (interview) # % Other: Couch or doubled up 31 100%
What person had to give to be able to couch surf # %
Money 4 13%
Work / Help Chores 2 6%
Other: Sex 0 0%
Other: Drugs 0 0%
NA: Couch surfing is not collected by observational survey and not included in unsheltered count. *Percentages do not add up to 100% due to rounding
Page | 164
APPENDIX B:
2022 Point-in-Time Count Survey Questions
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2022 Point-in-Time Count Survey Questions
» Surveyor Name
» Surveyor Phone Number
» Are you able to survey this Person?
» Hello, my name is ________________. Today we are conducting a survey to better understand a person's housing status. It is up to you whether you want to participate, and your answers will not be shared with anyone outside of our team. For your assistance, we have an incentive bag with goodies after you complete the survey.
» Can I have about 10 minutes of your time?
» Did another volunteer already ask you these same questions about where you stayed last night? » Where did you sleep last night (on the night of Tuesday, February 22, 2022)? o Couch surfing
▪ What do you have to exchange to stay there?
▪ Can you remain there for at least another 14 days?
» Including yourself (Person 1), how many adults are there in your (their) household, who are sleeping in the same location?
» How many children under 18 are there in your (their) household, who are sleeping in the same location?
Interview
» What is the first initial of your first name?
» What is the first initial of your last name?
» How are you related to Person 1?
» How old are you?
» Are you Hispanic or Latin(a)(o)(x)?
» What is your race?
» How would you define your gender?
» What CITY were you born in?
» What STATE were you born in?
» Did you become homeless for the first time during the past 12 months? » Have you been living in a shelter and/or on the streets, in abandoned buildings, or vehicle for the past year or more?
» Have you been living in a shelter and/or on the streets, in abandoned buildings, or vehicle at least 4 separate times during the last 3 years including now?
o If YES, was combined length of time 12 months or more? » Why did you become homeless?
» Do you have a companion animal living with you?
o If YES, how many?
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o If YES, if you had to leave your pet to go into housing or a treatment program, would you?
Youth (Under 25)
» FEMALE - Are you currently pregnant?
» MALE - Are you expecting to become a parent in the next 9 months? » Have you ever been placed in foster care or stayed in a group home? o If you left foster care/group home in the past 3 years, did anyone help you get housing? » Have you stayed overnight or longer in jail, prison, or a juvenile detention facility? o If you left jail/prison/juvenile detention facility in the past 3 years, did anyone help you get housing?
o Have you or your family experienced barriers to obtain housing due to your or your family’s history of incarceration?
» Have you stayed overnight or longer in a treatment or healthcare facility? o If you left treatment/healthcare facility in the past 3 years, did anyone help you get housing?
» What is your school experience?
» What is the highest level of schooling you completed? » In the past year, in what ways did you make money?
» Think about the last time you felt that you were living in stable housing, or housing where you felt safe. How long ago was that?
o What is the primary reason you left or lost your last stable housing situation? » In the past year, what services or supports, for example from government programs or charities, have you accessed?
Adult (18+)
» Have you ever served in the U.S. Armed Forces, Reserves, or National Guard? o When did you serve on active duty in the U.S. Armed Forces? » Were you recently released from jail or prison?
o If YES, were you released on probation or parole?
» Have you faced barriers in accessing housing as a result of your/your family members’ arrest or conviction record?
» Has a doctor or other medical professional ever told you that you may have a chronic health condition that is life-threatening such as heart, lung, liver, kidney or cancerous disease? » Do you have a long-lasting physical disability that makes it difficult for you to live independently? » Do you have a long-lasting developmental disability that makes it difficult for you to live independently?
» Do you have serious mental illness or emotional impairment that limits your ability to live independently?
» Do you have a substance use disorder that is ongoing and makes it difficult for you to live independently?
» Do you have AIDS or an HIV-related illness?
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» Do you have Post-Traumatic Stress Disorder or PTSD?
o If YES, does it keep you from holding a job or living in stable housing? » Have you ever had a serious injury to your brain?
o If YES, does it keep you from holding a job or living in stable housing? » Do you receive any disability benefits such as Social Security Income, Social Security Disability Income, or Veteran’s Disability Benefits?
» Employment Type
» How much is your monthly income?
» Are you experiencing homelessness because you are currently fleeing domestic violence, dating violence, sexual assault, or stalking?
Observation
Because this person is unable or unwilling to be interviewed, complete the following questions to the best of your ability based on what you can observe of the person and members of their household. Each household should be submitted as a separate survey.
» How many adults are there in the household, who are sleeping in the same location? » How many children are there in the household, who are sleeping in the same location? » Please indicate why you are using the observation tool » Is this person homeless?
» What is this person’s age?
» What is this person’s gender?
» What is this person’s race?
» What is this person’s ethnicity?
» Other Information or identifying characteristics
More Than a Count Initiative – Housing and Services Linkages » Would you like to request that a service provider follow up with you in the next 2 weeks to provide information about services that may be helpful to you?
o First name
o Last name
o Date of birth
o Last 4 digits of your social security number
o Phone number (including area code)
o Can this phone accept text messages?
o Email
o Do I have your permission to share your contact information only to our service provider to reach out to you?
o What services or information would you like assistance with?