[Slide 1]{.underline}

**Conducting Homeless Point-in-time Surveys**

Tracy D'Alanno

Colorado Department of Human Services

Supportive Housing and Homeless Programs

Phone: 3 0 3, 8 6 6, 7 3 6 1

E-mail: tracy.dalanno@state.co.us

[Slide 2]{.underline}

**Homeless Point-in-time Survey: Why Do It**

HUD requires sheltered and unsheltered census counts in their annual
Continuum of Care application

A point-in-time survey may be used to produce an estimate of the "point
prevalence" of homelessness in a community or region either in
conjunction with, or when there is not an active HMIS

Point prevalence is the number of cases observed at a particular point
in time or the number of homeless persons on a given day or night

[Slide 3]{.underline}

**Benefits**

May be used for estimating population size, distinguishing demographics,
and identifying needs

Provides useful information for public education about homelessness

Helps agencies with grant applications

Helps direct public policy planning and development

Provides information to communities for service planning

Helps HUD Consolidated Planning Jurisdictions with completing their
plans

Provides the information needed to complete Exhibit 1 of the Continuum
of Care application

[Slide 4]{.underline}

**Limitations**

Undercounting is the primary limitation of this method. Counting persons
who are homeless is not an exact science. Limiting the methodology to a
specific point in time makes it difficult to capture all potential
cases.

It requires a lot of coordination with participating agencies.

A lack of full participation from all homeless providing agencies could
lead to a significant undercount and bad data.

[Slide 5]{.underline}

**Step 1: Who and Where**

Determine Whom You Want to Count

Single individuals

Families

Youth on their own

Veterans

Sheltered

Unsheltered

Chronically homeless

Where: Continuum of Care jurisdiction, multiple COC's, statewide

[Slide 6]{.underline}

**Step 2: When**

Pick a Date

Recommend last week of January 2005

> Posted in HUD 2005 Exhibit 1

Publicize the date frequently to homeless providers

> Backup timeline activities: survey development English and Spanish,
> copying, distribution, training, volunteer coordinators

[Slide 7]{.underline}

**Step 3: How**

Determine How You Want to Count

Self-reported surveys

Interviews

Combination interview and self-reported

Street outreach

Survey Distribution: all shelters, day shelters, soup kitchens,
transitional housing programs, county social services, jails, prisons,
hotels slash motels, shelter help lines

[Slide 8]{.underline}

**Steps 4: What**

Determine What You Want to Know

How many persons

> Type of population: singles, families, veterans, special needs, youth,
> seniors, chronic homelessness

Important demographics: age, gender, race, ethnicity

> Important special need indicators: mental illness, substance abuse,
> HIV slash Aids

Last permanent address

[Slide 9]{.underline}

**Steps 4: What**

Determine What You Want to Know

Where persons are staying: shelter, streets, transitional housing

Length slash frequency

Reasons for homelessness

Education

Income

Employment status

[Slide 10]{.underline}

**Step 5: Survey Instrument**

Make it as short as possible

Use checkboxes as much as possible

Code instrument for easier data entry

Use of identifiers for de-duplication: parts of name, date of birth,
gender, age, and potentially Social Security number

See handout instrument

[Slide 11]{.underline}

**Step 5: Survey Instrument**

Homeless qualifier

Are you homeless

> Do you have a permanent place to live. If yes, match with where they
> spent last night

Spanish version, question mark

Provider buy-in through participation

Form a committee to oversee process

Point persons for multiple jurisdictions

Develop data entry rules: what to do with missing responses, why this
question, et cetera

[Slide 12]{.underline}

**Step 6: Get Help**

Who is taking a lead on organizing the project. Committees are great,
but you need someone to bring it all together

Research and data entry assistance: university, outside contractor,
researcher, State or local government, some combination, question mark

Homeless persons: usually the best at street outreach

Volunteers for each organization

Funding incentives: candy bars, soda, cash

Provider participation

[Slide 13]{.underline}

**Step 7: Training**

One week prior to count

Hold trainings for participating agencies

Large group

At each agency

Teleconference

Regional

Distribute forms

[Slide 14]{.underline}

**Step 8: Count Day**

Participating agencies collect surveys during the day and evening of the
point in time

Transitional housing providers may want to complete survey information
on behalf of their consumers over the course of that week

Be prepared for press calls: use these to your advantage

Set up process for collecting completed forms

[Slide 15]{.underline}

**Step 9: Data Entry and Cleaning: Where the Real Work Begins**

Clean paper forms and code

Spot check during data entry: look for errors, check every tenth record,
et cetera

Someone needs to be available to data entry clerks to answer questions

[Slide 16]{.underline}

**Step 10: Data Analysis and Findings**

Analyze Data

> In-house: large jurisdictions use something like SPSS; smaller
> jurisdictions probably could use Access or Excel

Consultants

Universities

Government agencies

Distribute Findings

All participating agencies should get a copy of the findings

[Slide 17]{.underline}

**Distribution and Use of Data**

Release results through press conference

Consolidated plan jurisdictions

Continuum of Care and grant applications

Researchers

Schools, colleges, and universities

Special queries

Trend analysis

Policy development: local, State, national

[Slide 18]{.underline}

**Data Example: How Many People Were Homeless on January Twenty-seventh,
2003: Total Persons Counted and Surveyed**

A table and a bar graph both present the following information:

Single Adult Individuals, 21 years and older: 2,813

Adults or Youth-headed Families: 3,452

Children in Families under 18 years: 3,059

Single Youths Not in Families, 9 to 21 years: 401

Total Unduplicated Persons Counted: 9,725

[Slide 19]{.underline}

**Data Example: Persons Counted as Homeless, 1998 to 2003**

A table and a bar graph both present the following information. Single
Adult Individuals aged 21 years and older numbered 2,514 in 1998, 2,722
in 2000, 3,024 in 2001, and 2,813 in 2003. Adults or Youth-headed
Families numbered 1,150 in 1998, 1,938 in 2000, 2,728 in 2001, and 3,452
in 2003. Children in Families under 18 years numbered 1,931 in 1998,
2,745 in 2000, 3,522 in 2001, and 3,059 in 2003. Single Youths Not in
Families aged 9 to 21 years numbered 197 in 1998, 284 in 2000, 396 in
2001, and 401 in 2003. Total Unduplicated Persons Counted numbered 5,792
in 1998, 7,689 in 2000, 9,670 in 2001, and 9,725 in 2003.

[Slide 20]{.underline}

**Data Example: What Are the Age Breakdowns for Homeless Populations**

On a table labeled Age, each row represents data for a different age
group. The column labeled Frequency gives 1,599 for ages 0 to 5, 1,342
for ages 6 to 14, 458 for ages 15 to 17, 595 for ages 18 to 20, 1,501
for ages 21 to 30, 1,542 for ages 31 to 40, 1,499 for ages 41 to 50, 739
for ages 51 to 64, 63 for ages 65 to 75, 16 for ages more than 75, 371
not answered, and 9,725 total. The column labeled Percent gives 16.4 for
ages 0 to 5, 13.8 for ages 6 to 14, 4.7 for ages 15 to 17, 6.1 for ages
18 to 20, 15.4 for ages 21 to 30, 15.9 for ages 31 to 40, 15.4 for ages
41 to 50, 7.6 for ages 51 to 64, 0.6 for ages 65 to 75, 0.2 for ages
more than 75, 3.8 not answered, and 100 total. The column labeled Valid
Percent gives all the same percentages. The column labeled Cumulative
Percent gives 16.4 for ages 0 to 5, 30.2 for ages 6 to 14, 35.0 for ages
15 to 17, 41.1 for ages 18 to 20, 56.5 for ages 21 to 30, 72.4 for ages
31 to 40, 87.8 for ages 41 to 50, 95.4 for ages 51 to 64, 96.0 for ages
65 to 75, 96.2 for ages more than 75, and 100 not answered.

[Slide 21]{.underline}

**Data Example: Age: Children Equal 35 Percent of Population**

A pie graph indicates 17.1 percent for 0 to 5; 14.3 percent for 6 to 14;
16.0 percent for 21 to 30; 16.5 percent for 31 to 40; 16.0 percent for
41 to 50; and unspecified smaller percentages, in descending order, for
51 to 64, 18 to 20, 15 to 17, 65 to 75, and 75 plus.

[Slide 22]{.underline}

**Data Example: Individual Age** **Breakdown**

On a table labeled Age, each row represents data for a different age
group. The column labeled Frequency gives 4 for ages 6 to 14, 54 for
ages 15 to 17, 260 for ages 18 to 20, 501 for ages 21 to 30, 695 for
ages 31 to 40, 967 for ages 41 to 50, 582 for ages 51 to 64, 32 for ages
65 to 75, 7 for ages more than 75, 112 not answered, and 3,214 total.
The column labeled Percent gives 0.1 for ages 6 to 14, 1.7 for ages 15
to 17, 8.1 for ages 18 to 20, 15.6 for ages 21 to 30, 21.6 for ages 31
to 40, 30.1 for ages 41 to 50, 18.1 for ages 51 to 64, 1.0 for ages 65
to 75, 0.2 for ages more than 75, 3.5 not answered, and 100 total. The
column labeled Valid Percent gives all the same percentages. The column
labeled Cumulative Percent gives 0.1 for ages 6 to 14, 1.8 for ages 15
to 17, 9.9 for ages 18 to 20, 25.5 for ages 21 to 30, 47.1 for ages 31
to 40, 77.2 for ages 41 to 50, 95.3 for ages 51 to 64, 96.3 for ages 65
to 75, 96.5 for ages more than 75, and 100 not answered.

A bar graph labeled Age illustrates the Percent column.