February 2026
Modeling Solutions to Homelessness in Oakland
Technical explainer for system modeling analysis in the Homelessness
Strategic
Action
Plan
Overview All Home’s Solutions Modeling is a system modeling tool designed to estimate the additional
investment
and
inventory
requirements
needed
to
achieve
homelessness
reduction
goals.
It
produces
a
high-level
roadmap
for
reducing
unsheltered
homelessness
through
a
strategy
of
concurrent
investments
in
targeted
homelessness
prevention,
permanent
housing
solutions,
and
interim
housing.
In 2024-2025, All Home’s technical assistance team worked in close collaboration with
Oakland’s
Housing
and
Community
Development
(HCD)
department
to
gather
a
variety
of
Oakland-specific
data
inputs
to
incorporate
into
the
analysis
and
to
refine
the
system
performance
assumptions
and
strategic
goals
informing
the
modeling
outputs.
In
2025,
Oakland’s
newly
formed
Office
of
Homelessness
Solutions
reviewed
system
analysis
results
and
confirmed
the
City’s
interest
in
utilizing
these
results
to
inform
the
5-year
Homelessness
Strategic
Action
Plan
(HSAP).
This report describes the methods, key assumptions, and data sources used to produce
the
Solutions
Modeling
estimates
produced
for
Oakland’s
Homelessness
Strategic
Action
Plan.
It
also
describes
the
motivation
behind
the
distinguishing
characteristics
of
the
model,
chief
among
these
being
the
ability
to
link
reduced
new
entries
into
homelessness
to
expanded
investment
in
targeted
homelessness
prevention,
a
research-based
best
practice
and
cost-effective
solution
for
reducing
overall
homelessness.
Understanding what it will take to rapidly and substantially reduce homelessness is
a
crucial
step
toward
actually
achieving
this
goal.
In
addition
to
informing
local
strategy
and
investment
priorities,
the
estimates
produced
hopefully
support
1 advocacy for increased new funding. Perhaps most importantly, the findings help demonstrate
that
when
the
scale
of
investment
matches
the
scale
of
the
crisis
we
face,
real
change
is
possible.
Similarly,
the
estimates
help
us
understand
our
limited
recent
progress
despite
increased
(though
still
insufficient)
new
funding
and
policy
change.
The report begins by briefly highlighting the major motivations that informed the design
of
the
Solutions
Modeling
tool,
calling
attention
to
characteristics
that
distinguish
the
model
from
comparable
systems
modeling
tools.
It
then
describes
the
process,
data,
and
assumptions
used
to
estimate
the
need
for
additional
homelessness
prevention
assistance,
permanent
housing
solutions,
and
interim
housing,
along
with
the
associated
costs.
After
acknowledging
several
limitations
of
the
model,
the
report
concludes
by
noting
that
Oakland
inventory
and
investment
goals
should
be
updated
and
informed
by
the
system
modeling
informing
the
forthcoming
Home
Together
2030
strategic
plan
to
end
homelessness
in
Alameda
County.
Model Design Motivation
The projections generated by the Solutions Modeling tool are associated with the implementation
of
a
particular
homelessness
reduction
strategy.
Specifically,
the
analysis
is
guided
by
the
Regional
Action
Plan’s
strategic
framework,
characterized
by
concurrent
investments
in
three
core
solutions:
homelessness
prevention,
permanent
housing
solutions,
and
interim
housing.
1 In
system
performance
terms,
the
modeling
is
based
on
a
strategy
of
reducing
new
incidence
of
homelessness
while
simultaneously
expanding
the
available
array
of
exits
to
permanent
housing,
and
expanding
interim
housing
inventory
to
facilitate
exits
to
housing
and
mitigate
the
trauma
of
living
unsheltered
long-term.
This
strategy
provides
the
most
cost-effective
path
to
achieving
meaningful
and
lasting
reductions
in
unsheltered
homelessness.
It
does
so
by
building
a
balanced
response
system
able
to
more
rapidly
meet
distinct
needs
of
the
unhoused
population
while
promoting
improved
program
outcomes
and
systemwide
efficiencies.
Permanent housing, interim housing, and new homelessness prevention depend on
one
another
to
succeed,
and
the
required
investments
in
each
category
are
interdependent.
If
we
invest
heavily
in
prevention,
for
example,
less
permanent
housing
and
interim
housing
will
likely
be
needed
in
the
future
because
fewer
people
will
lose
housing
in
the
first
place.
Similarly,
creating
more
permanent
1 Full Regional Action Plan available at www.allhomeca.org/regionalactionplan/ 2 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
housing solutions reduces the number of new interim housing units required to reach
unsheltered
reduction
goals,
since
people
will
be
able
to
exit
homelessness
more
rapidly
(and
thereby
open
up
existing
units
of
interim
housing
to
accommodate
others).
The Solutions Modeling tool was designed to draw attention to the interdependency
of
homelessness
prevention,
permanent
housing
solutions,
and
interim
housing,
and
the
unmet
need
for
each
program
type.
It
makes
this
connection
most
apparent
by
linking
projected
new
entries
into
homelessness
to
investments
in
expanded
homelessness
prevention
assistance.
This
link
in
the
analysis
is
perhaps
the
most
important
distinguishing
design
characteristic
of
the
model,
and
is
a
step
that
has
historically
been
overlooked
in
approaches
to
homelessness
system
modeling.
Despite
the
formidable
assumptions
required,
we
think
it
is
important
to
include
this
linkage
in
the
modeling
to
demonstrate
the
potential
impact
of
reducing
new
incidence
of
homelessness,
and
to
ensure
that
homelessness
prevention
programming
does
not
go
unaddressed
in
policy
debates
and
budgetary
considerations.
Calculating New Interventions and Units Required Solutions Modeling estimates the additional housing inventory and assistance required
to
reduce
unsheltered
homelessness
by
a
designated
goal,
and
assumes
that
currently
operating
programs
in
the
city’s
homelessness
response
system
remain
in
operation.
Funding
requirements
are
in
addition
to
current
baseline
spending.
In consultation with HCD staff, we established a target of reducing unsheltered homelessness
in
Oakland
by
50 percent
over
five
years.
Estimates
for
the
inventory
needed
to
reach
this
goal
are
calculated
through
three
broad
analytical
steps
which
determine:
1. the total population needing housing assistance to achieve the unsheltered
reduction
goal,
including
expectations
for
how
many
people
will
become
newly
homeless
each
year
after
accounting
for
the
impact
of
increased
investment
in
homelessness
prevention
;
2. the number and types of new permanent housing solutions required to meet
yearly
goals;
and,
3. the number of additional interim housing units required to facilitate exits to housing
and
provide
short
term/transitional
options
in
the
absence
of
sufficient
affordable
permanent
housing.
3 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
This section describes how the modeling approaches each of these tasks, noting for each the key assumptions and data sources used. Figure 1 visualizes these major components of the model and their relationship. Figure 1. Modeled solutions and system flow
Dynamic Population Projections and Prevention Impact The population of people experiencing homelessness is dynamic. Each year, roughly
1,500
people
in
Oakland
move
out
of
homelessness
and
into
housing.
At
the
same
time,
however,
2,500
people
also
become
homeless
for
the
first
time
4 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
each year, while still others return to homelessness after resolving a previous experience.
The
Solutions
Modeling
analysis
accounts
for
this
dynamic
nature
of
the
homeless
population
by
including
both
those
currently
homeless
and
those
projected
to
become
homeless
in
calculating
the
need
for
additional
housing
assistance.
The number of people currently experiencing homelessness is derived from the most
recent
Point-in-Time
(PIT)
count
data
available.
Despite
shortcomings
resulting
in
what
is
widely
acknowledged
as
an
undercount,
2 PIT
data
serves
as
the
most
reliable,
regularly
reported
proxy
available
for
estimating
the
number
of
people
currently
living
in
unsheltered
settings.
To project the number of people likely to become homeless in a given year, we accessed
Homeless
Management
Information
System
(HMIS)
data
restricted
to
programs
operating
within
Oakland.
3 With
assistance
from
the
Alameda
County
Department
of
Housing
and
Homelessness
Services
Department,
we
used
this
Oakland-specific
HMIS
data
to
estimate
annual
“first-time
homelessness”
as
defined
by
the
U.S.
Department
of
Housing
and
Urban
Development
(HUD).
4 “First-time”
is
a
somewhat
misleading
term,
since
in
actuality
it
includes
only
people
who
enroll
in
a
homelessness
assistance
program
and
who
have
no
record
of
having
enrolled
in
such
a
program
in
the
previous
two
years.
So,
someone
who
stayed
in
a
shelter
three
years
earlier,
for
example,
will
be
counted
as
homeless
for
the
first
time.
It
also
counts
as
homeless
for
the
first
time
anyone
who
experienced
homelessness
previously
but
did
not
engage
the
response
system
for
some
form
of
assistance.
The HUD SPM for first-time homelessness also only includes people enrolled in “residential”
programs,
including
emergency
shelters,
transitional
housing,
rapid
rehousing,
and
other
permanent
housing
assistance.
This
means
that
this
estimate
does
not
include
people
experiencing
homelessness
but
who
engage
with
response
systems
only
through
street
outreach,
for
example.
While
certainly
an
undercount,
this
measure
provides
the
best
apparent
proxy
for
the
number
of
people
requiring
housing
assistance
to
exit
homelessness.
4 System Performance Measure data and reference material are available at https://www.hudexchange.info/programs/coc/system-performance-measures/
3 HMIS
data
is
tracked
county-wide,
and
while
calculating
city-specific
measures
was
required
for
this
analysis,
doing
so
inherently
introduces
additional
limitations
and
imprecision
to
the
data.
2 Kim Hopper et al., “Estimating Numbers of Unsheltered Homeless People Through Plant-Capture
and
Postcount
Survey
Methods,”
American
Journal
of
Public
Health
98,
no.
8 (August
2008):
1438–42,
https://doi.org/10.2105/AJPH.2005.083600;
Monika
Schneider,
Daniel
Brisson,
and
Donald
Burnes,
“Do
We
Really
Know
How
Many
Are
Homeless?:
An
Analysis
of
the
Point-In-Time
Homelessness
Count,”
Families
in
Society
97,
no.
4 (October
1,
2016):
321–29,
https://doi.org/10.1606/1044-3894.2016.97.39.
5 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
Our baseline projection for “first-time homelessness” as defined by HUD averages three
years
of
HMIS
data
(2021-2023).
To
this
number,
we
add
the
anticipated
number
of
people
returning
to
homelessness
each
year
after
a
recent
exit
to
housing.
Again,
since
we
are
utilizing
data
solely
from
programs
operating
in
Oakland,
estimated
returns
do
not
include
individuals
who
enroll
in
a
homeless
assistance
program
outside
of
Oakland
after
a
successful
permanent
housing
“exit”
from
a
program
within
the
city.
The best way to reduce new entries and returns to homelessness is to maximize the
use
of
targeted
homelessness
prevention.
By
focusing
on
the
population
at
highest
risk
of
homelessness
and
providing
prevention
services
including
rapid
flexible
financial
assistance,
housing
stabilization
services,
and
legal
services
as
needed,
we
can
prevent
people
from
losing
housing
in
the
first
place.
This
tactic
prevents
people
from
experiencing
the
trauma
and
destabilizing
effects
caused
by
homelessness.
As
research
on
the
costs
of
homelessness
have
shown,
it
is
also
far
more
economically
efficient
to
prevent
entries
into
homelessness
than
to
serve
people
once
they
are
homeless.
5 In a financially constrained environment, investing in targeted homelessness prevention
is
essential
to
meeting
the
15 percent
“new
homelessness
reduction
goal”
set
in
consultation
with
Oakland
HCD.
Reducing
the
new
incidence
of
homelessness
by
this
rate
would
require
substantially
scaling
up
Oakland’s
existing
targeted
homelessness
prevention
assistance.
6 The
15 percent
reduction
target—an
undeniably
aspirational
goal—is
in
line
with
assumptions
incorporated
in
system
modeling
conducted
for
the
Los
Angeles
Homeless
Services
Authority,
for
example,
which
assumes
expanded
prevention
assistance
could
reduce
the
need
for
interim
housing
by
20 percent.
7 Successful homelessness prevention programs require efficiently identifying and serving
people
who
would
have
become
homeless
without
assistance.
Many
people
who
apply
for
services
would
benefit
from
financial
support,
but
would
not
be
pushed
into
homelessness
if
they
are
not
served.
Existing
evidence-based
risk
assessments
help
target
resources
toward
the
highest
need
individuals,
but
it
remains
impossible
to
perfectly
predict
who
will
and
will
not
be
pushed
into
7 See Homeless Services System Analysis: Envisioning an Optimal System in Los Angeles , Los
Angeles
Homeless
Services
Authority,
2020.
https://www.lahsa.org/documents?id=4311-homeless-services-system-analysis-envis ioning-an-optimal-system-in-los-angeles.pdf
.
6 Keep
People
Housed
-
Oakland
represents
the
most
established
targeted
homelessness
prevention
program
in
Oakland
at
this
time.
5 See Do Homelessness Prevention Programs Prevent Homelessness? Evidence from a Randomized
Controlled
Trial
(2025).
https://direct.mit.edu/rest/article-abstract/107/5/1187/116185/Do-Homelessness-Pr evention-Programs-Prevent
6 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
homelessness. “Targeting efficiency” means the percent of households receiving prevention
assistance
who
would
have
become
homeless
without
it.
In
the
modeling,
we
peg
prevention
targeting
efficiency
at
15 percent,
meaning
between
six
and
seven
households
will
need
to
be
served
to
reduce
projected
new
homelessness
by
one.
The current homeless population plus the number of individuals projected to become
homeless
each
year
(after
the
baseline
is
reduced
to
meet
new
homelessness
reduction
goals
achieved
through
expanded
prevention
assistance)
constitutes
our
estimate
for
the
total
population
requiring
housing
assistance.
8 The
five-year,
50 percent
reduction
target
is
broken
into
annual
progress
benchmarks,
which
determine
the
number
of
individuals
matched
with
housing
assistance
in
each
year
of
the
modeled
strategy.
Table 1a. Key Population and Prevention Assumptions Name Description Model Inputs Unsheltered Homelessness Reduction Goal
Target for the percent by which unsheltered homelessness will be reduced by year five. (Maintained for years 6-10.) 50%
Inflow Reduction Goal
Target for the percent of projected new homelessness (both “1st-time and returns) prevented from becoming homeless 15%
Annual change in Inflow
Projected annual change in “1st-time” homelessness 0%
Prevention Targeting Efficiency
Percent of households receiving prevention assistance projected to have become homeless without the assistance. (Used to calculate the number of interventions required to reduce new homelessness by one.) 15%
8 The modeling uses PIT data to approximate the number of “single adult households” and
“family
households”
requiring
assistance
to
reach
designated
reduction
goals,
which
informs
both
total
interventions
required
and
the
per-unit
program
costs
associated
with
each
household
type.
7 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
Table 1b. Key Population and Prevention Data Sources Measure Description Source Baseline unsheltered homelessness
Total number of people currently experiencing unsheltered homelessness Point-in-Time (PIT) Count data
Baseline new homelessness
Estimate for the number of people each year becoming homeless for the “first time,” as defined by HUD HUD System Performance Measure 5.2, calculated using HMIS data from programs operating within Oakland.
Returns to homelessness
Estimate for the percent of people projected to return to homelessness within two years of exiting to permanent housing.
HUD System Performance Measure 2, calculated using HMIS data from programs operating within Oakland.
Permanent Housing Solutions After determining the number of households requiring housing assistance to reach
annual
homelessness
reduction
benchmarks,
we
reduce
this
amount
by
what
we
term
“current
system
capacity”
which
we
define
as
the
number
of
households
for
whom
the
current
response
system
can
already
reliably
resolve
homelessness
with
housing
assistance
in
a
given
year.
To
set
this
baseline,
we
again
draw
on
Oakland-specific
HMIS
data,
this
time
indicating
total
individuals
exiting
to
positive
housing
destinations
from
city
programs.
The
modeled
current
system
capacity
for
Oakland
was
calculated
by
averaging
annual
total
exits
to
positive
destinations
(sometimes
referred
to
as
“permanent
housing
exits”)
for
three
years,
2021-2023.
After subtracting the current system capacity from the total housing assistance required
for
a
given
year,
the
model
calculates
the
number
and
type
of
additional
interventions
or
units
required
to
meet
that
year’s
remaining
unmet
needs.
Four
broad
categories
of
permanent
housing
solutions
are
included
in
the
model:
● Short-term assistance - a general category including one-time or time-limited
financial
or
rental
assistance
and
problem-solving
support.
● Ongoing Rental Subsidy - comparable to housing choice vouchers, which provide
subsidies
to
households
renting
housing
on
the
private
market.
8 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
● New Dedicated Affordable Housing Units - newly developed, deeply affordable
housing
units
with
dedicated,
ongoing
funding
for
operations,
and
targeted
to
people
exiting
homelessness.
● New Permanent Supportive Housing (PSH) Units - newly developed, deeply
affordable
housing
units
requiring
additional
funding
to
provide
ongoing
mental
health
and
other
supportive
services
for
residents
requiring
more
support
to
maintain
housing
stability.
The added ongoing rental subsidies and new affordable units are serving essentially
the
same
needs
and
purpose:
expanding
the
amount
of
housing
affordable
to
households
with
extremely-low-incomes.
The
model
includes
both
categories
to
acknowledge
that,
while
we
won’t
need
to
build
a
new
unit
for
all
households
served
by
these
programs,
we
also
can’t
achieve
our
goal
solely
by
expanding
rental
subsidies.
A
full
spectrum
of
housing
assistance–
including
both
expanded
rental
assistance
and
expanding
upon
the
existing
stock
of
deeply
affordable
rental
housing–is
required
to
achieve
an
effective
and
enduring
reduction
of
homelessness
in
Oakland.
Our approach to determining how we distribute the total need for new housing support
across
these
four
categories
strives
to
match
approximate
levels
of
need
among
the
population
with
appropriate
housing
solutions
while
simultaneously
acknowledging
constraints
in
developing
new
units.
Beginning
with
the
currently
homeless
population,
the
number
of
new
permanent
supportive
housing
(PSH)
units
needed
is
estimated
based
on
the
proportion
of
people
experiencing
chronic
homelessness
(as
determined
by
most
recent
PIT
data).
9 Thus,
rates
of
chronic
homelessness
are
used
as
a
proxy
for
the
need
for
supportive
housing.
10 After
accounting
for
the
number
of
new
PSH
units
needed,
the
remaining
permanent
housing
solutions
required
are
distributed
among
the
other
three
categories.
Population
shares
matched
with
each
housing
solutions
were
determined in consultation with HCD staff, and are reported in table 2a below. For the newly homeless population, we generally assume a lower level of need for PSH,
as
the
significant
expansion
of
new
housing
resources
should
reduce
the
length
of
time
most
individuals
experience
homelessness.
11 11
The
proportions
of
newly
homeless
households
matched
with
these
four,
broad
categories
of
housing
support
will
not–and
probably
should
not–match
the
interventions
deemed
most
appropriate
for
households
currently
served
by
homelessness
response
systems.
Given
the
current
scarcity
of
resources
to
provide
housing
solutions,
those
who
are
currently
prioritized
to
receive
assistance
represent
10 For HUD’s official definition of chronic homelessness, see: https://www.hudexchange.info/homelessness-assistance/coc-esg-virtual-binders/c oc-esg-homeless-eligibility/definition-of-chronic-homelessness/
9 For their California Homeless Housing Needs Assessment, the Corporation for Supportive
Housing
assumed
that
90 percent
of
those
experiencing
chronic
homelessness,
and
10 percent
of
all
other
individuals
experiencing
homelessness,
would
be
best
served
with
permanent
supportive
housing.
9 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
In light of severe racial disparities among Oakland’s unhoused population, and as required
by
the
City
of
Oakland’s
Racial
Equity
Impact
Analysis
(REIA)
process,
All
Home
and
the
City
of
Oakland
researched
the
characteristics
of
the
city’s
Black
unhoused
population
to
ensure
that
modeled
inventory
goals
aligned
with
housing
needs.
Reducing
unsheltered
homelessness
in
Oakland
requires
deliberately
addressing
racial
disparities
in
who
becomes
homeless
in
Oakland.
City
investments
must
account
for
racially-correlated
differences
indicating
program
models
and
per-unit
costs
associated
with
meeting
various
needs
of
different
racial
or
ethnic
groups.
Local
data
and
external
academic
research
were
used
to
estimate
the
proportion
of
Black
unhoused
Oaklanders
best
matched
with
each
permanent
housing
model
(i.e.,
time-limited
subsidies,
permanent
rental
vouchers,
dedicated
affordable
housing,
and
permanent
supportive
housing)
and
to
calibrate
modeled
inventory
needs.
12 Assigning the approximate level of need for each of the four housing solutions is a
distinct
process
from
that
of
determining
how
many
units
can
feasibly
be
produced
in
a
given
year.
To
determine
this
“baseline
production
limit,”
we
draw
on
data
from
the
California
Department
of
Housing
and
Community
Development
on
the
number
of
deeply
affordable
units
completed
in
recent
years.
Oakland’s
baseline
production
limit
is
calculated
by
averaging
the
number
of
new
housing
units
affordable
to
households
with
very-low
incomes
(or
VLI
units)
completed
over
the
last
five
years.
13 This
baseline–which
includes
both
new
construction
and
acquisition/rehab
and
reuse
projects–determines
the
number
of
new
units
that
can
be
completed
in
year
one
of
the
modeled
strategy.
Based
on
production
pipeline
data
provided
by
HCD
(while
acknowledging
a
significant
influx
in
required
new
funding),
we
assume
production
capacity
will
increase
incrementally,
reaching
150%
of
baseline
levels
by
year
five.
This
represents
an
aspirational
level
of
new
state,
local
and
federal
funding.
However,
with
this
added
funding,
Oakland’s
housing
pipeline
and
the
existing
infrastructure
of
nonprofit
developers
and
City
oversight
could
feasibly
deliver
the
units.
Production
limits
are
divided
evenly
between
the
new
affordable
housing
and
new
PSH
categories.
13 While
the
bulk
of
the
units
required
would
qualify
as
units
affordable
to
households
with
extremely-low
incomes
(or
ELI
units,
dedicated
to
households
earning
below
30 percent
area
median
income),
data
for
this
category
of
housing
has
until
recently
been
subsumed
under
the
very-low
income
(VLI)
category,
representing
housing
affordable
to
households
earning
under
50 percent
area
median
income.
12 Racially
disaggregated
data
and
associated
implications
for
policy
and
program
design
are
discussed
in
greater
detail
in
the
Homelessness
Strategic
Action
Plan
Racial
Equity
Impact
Analysis,
with
recommendations
incorporated
into
the
Homeless
Strategic
Action
Plan.
the most vulnerable subset of the broader homeless population, and require a higher level
of
support
(on
average)
than
would
be
required
by
those
served
by
an
optimal,
better
balanced
response
system.
10 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
When the projected need for new permanent housing options surpasses a given year’s
production
limit,
the
resulting
gap
informs
decisions
about
the
number
of
new
interim
housing
units
required,
as
discussed
below.
Table 2a. Permanent Housing Solutions Assumptions Name Description Model Input New Unit Production Capacity Change
Number of new housing units (as a percentage of the baseline production limit) that can be produced in a given year. Used to inform incremental increases in production capacity. 150% by year 5.
Percent assigned PSH
Percent of population matched with PSH as their permanent housing solution (for both currently homeless population and those projected to become homeless in future years.) Current: 30% New: 20%
Percent assigned newly constructed affordable units Percent of population matched with newly constructed affordable units as their permanent housing solution.
Current: 21% New: 24%
Percent assigned ongoing rental subsidy
Percent of population matched with full rental subsidy as their permanent housing solution.
Current: 28% New: 32%
Percent assigned short-term assistance
Percent of population matched with short-term assistance as their permanent housing solution.
Current: 21% New: 24%
11 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
Table 2b. Permanent Housing Solutions Data sources Measure Description Source Current System Capacity
Projected number of people to be housed via current system (i.e., not requiring additional investment). Total exits to positive destinations from programs within Oakland.
HMIS data for programs operating within Oakland
Chronic homelessness rate
Percent of the currently homeless population experiencing chronic homelessness, as defined by HUD. Used to determine PSH needs.
PIT count data.
New Production Baseline limit
Average number of VLI units completed over the last five years. Used to establish annual production thresholds for new units produced in year one.
HCD Housing Element Implementation and APR Data Dashboard
Interim Housing Calculating the number of new interim housing units needed is an undeniably contentious
and
deceptively
complicated
task.
14 In
response,
we
have
developed
a
relatively
conservative
yet
grounded
approach
to
the
challenge.
Our
estimates
for
interim
housing
are
based
on
the
program
serving
two
strategic
purposes:
● Short stays for stabilizing and facilitating exits to housing - We assume that
a
majority
of
households
exiting
into
permanent
housing
in
a
given
year
will
stay
in
interim
housing
prior
to
that
exit.
For
them,
we
set
an
aspirational
duration
of
stay
in
interim
housing
of
several
months.
These
short
stays
create
opportunities
for
connecting
to
supportive
services,
facilitate
the
process
of
collecting
documentation
required
to
access
most
14 Recent efforts to estimate regional or statewide need for added interim housing are often
static
and
do
not
incorporate
dynamic
variables
that
demonstrate
the
interconnection
between
prevention,
interim
housing,
and
permanent
housing.
Other
approaches
underestimate
the
true
need
for
interim
housing
by
basing
estimates
on
survey
data
indicating
low
portions
of
people
experiencing
homelessness
expressing
interest
in
available
shelter
options.
When
the
interim
housing
aligns
with
All
Home’s
Interim Housing Principles, we believe a larger share of individuals are likely to embrace
the
opportunity
for
dignified,
supported
interim
options,
a
perspective
supported
by
recent research comparing interim housing models in Portland. 12 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
subsidized housing options, and reduce the added traumas and adverse health
impacts
associated
with
living
in
unsheltered
settings.
● Longer stays when new housing needed exceeds production limits - Especially
in
the
early
years
of
implementing
the
strategy,
we
assume
there
will
be
a
gap
between
the
permanent
housing
needed
and
what
can
be
completed
and
made
available.
In
such
cases,
we
add
additional
interim
units
equivalent
to
this
gap.
This
decision
follows
a
philosophical
view
that
the
street
should
not
serve
as
the
waiting
room
for
the
housing
we
cannot
yet
build
fast
enough.
The total new interim housing units added for a given year adds the number of units
required
to
accommodate
the
short
stays
(in
which
each
unit
will
accommodate
multiple
households
over
a
year)
and
longer
stays
(in
which
each
unit
is
dedicated
to
one
household
to
be
prioritized
for
new
housing
the
following
year).
Short
stay
durations
of
just
several
months
are
aspirational,
and
achieving
them
will
likely
require
both
expanding
permanent
housing
availability
as
well
as
pursuing
a
number
of
other
strategies
to
improve
program
performance.
Given
the
speed
with
which
many
modular
or
acquisition
and
rehab
projects
have
come
online,
we
do
not
include
production
limits
for
interim
housing
in
the
model.
15 Table 3a. Interim Housing Assumptions
Name Description Model Input
Percent w/ short stay in Interim Housing
Percent of households staying in new interim housing units prior to exiting to permanent housing (by permanent housing assigned). -50% (short-term assistance) -70% (ongoing subsidy) -70% (new affordable unit) -80% (new PSH unit) Average short stay duration in new interim housing Anticipated average duration of stay in interim housing for households exiting to housing in a given year (by permanent housing assigned). -2 months (short-term assistance & ongoing subsidy) -3 months (new affordable & PSH units) Exit to Housing Rate
Projected percentage of households with longer stay in interim housing projected to exit to permanent housing. (Remaining percent included in next year’s projections for returns to homelessness.) 75%
15 Given the significant expansion of permanent housing solutions included in the modeling,
we
allow
a
portion
(10%)
of
a
system’s
current
interim
housing
to
accommodate
a
small
share
of
the
modeled
additional
need
for
interim
housing,
thereby
reducing
the
estimate
for
total
new
interim
housing
units
required.
13 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
Table 3b. Interim Housing Data Sources Measure Description Source Existing shelter beds and Interim Housing Units
Total number of emergency shelter beds, transitional housing, safe haven beds currently in operation. Informs determination for the number of additional interim housing units required.
HUD Housing Inventory Count (HIC) for relevant projects operating within Oakland
Calculating Required Funding The modeling analysis provides estimates of the costs associated with providing the
assistance
and
adding/operating
the
new
housing
described
above.
However,
the
model
gives
no
indication
regarding
the
source
of
funds
or
which
level
of
government
(e.g.,
city,
county,
state)
bears
primary
responsibility
for
funding
any
particular
program
area.
Cost
estimates
thus
convey
total
investment
needs
.
In
practice,
city
budget
allocations
along
with
funds
originating
from
state,
federal,
and
county
sources
collectively
contribute
toward
achieving
target
investment
levels.
Per-unit costs for each of the inventories added in the modeling are included in Table 4a. All cost points were determined in consultation with HCD staff and through review of recently-funded projects in Oakland. Capital costs (associated with the development of new affordable and supportive housing
units
and
new
interim
housing)
are
one-time
costs
and
included
in
the
costs
for
the
year
in
which
the
new
units
come
online.
Capital
costs
for
new
dedicated
affordable
and
PSH
units
were
informed
by
a
review
of
recently-funded
development
projects.
Only
a
portion
of
total
per-unit
development
costs–about
40 percent–is
included
in
the
estimates
of
funding
required.
This
amount
($300k
in
the
model)
was
intended
to
reflect
the
high-end
of
city
share
of
costs
required
to
make
projects
competitive
for
tax
credits.
For
interim
housing,
the
full
per-unit
costs
are
included
in
the
modeling,
and
are
based
on
recently-funded,
well-performing
programs
in
the
city.
14 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
Operations and services costs represent the full funding requirements for prevention
programming,
short-term
assistance,
and
full
rental
subsidy
permanent
housing
solutions,
as
well
as
the
annual
ongoing
costs
associated
with
each
newly
constructed
dedicated
affordable,
PSH,
and
interim
unit.
The
costs
for
prevention
and
short-term
assistance
are
one-time
costs
for
providing
assistance
to
distinct
households.
Costs
for
ongoing
rental
subsidies
along
with
the
operations
and
services
costs
for
new
dedicated
affordable
housing,
PSH
and
interim
units
are
ongoing
and
persist
over
time.
For
these
programs,
yearly
costs
include
all
new
interventions
or
units
added
that
year
plus
all
those
added
in
previous
years.
For
newly
added
interim
housing
units,
operations
and
services
costs
are
only
calculated
for
units
remaining
in
operation,
excluding
new
units
created
but
decommissioned
in
later
years.
All baseline per-unit costs increase in the modeling by annual inflation rate of 3 percent.
Table 4a. Per-unit Cost Inputs Solution Program/Cost Type Cost Input Targeted Prevention
Financial assistance and support (services/ops)
$8,000-$9,000/household
Permanent Housing
Short-term assistance and support(services/ops)
$15,000-$18,000/household
Ongoing Rental Subsidy (services/ops)
$21,000/household
New Affordable/PSH Units (capital)
$300,000/unit
**Represents only city share/gap funding required. Total per-unit costs (incl. tax credits and mortgage) expected to be closer to $850k/unit.
New Affordable Housing Units (services/ops)
$16,500/unit
New PSH Units (services/ops)
$20,000/unit
Interim Housing
New Interim Units (capital)
$180,000/unit
New Interim Units (services/ops)
$40,000/unit
15 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
Table 4b. Per-unit Cost Data Sources and Informative References Solution Program/Cost Type Source/Reference Material Targeted Prevention Financial assistance
Based on records from Keep People Housing-Oakland. Total cost includes financial assistance (~75%), services (~15%) and administration (~10%).
Permanent Housing
Short-term assistance (services/ops)
Assumes half of households served receive rapid rehousing and half shallow subsidies. Based on currently operating city programs and on cost points included in Centering Racial Equity in Homeless System Design.
Ongoing Subsidy (services/ops)
Based on average Housing Choice Voucher amount for Oakland Housing Authority ($1732). Source: HUD HCV Data Dashboard New Affordable/PSH Units (capital)
HCD estimate based on review of recently funded projects, aiming for an estimate on the high end of city share of per-unit costs to project local investment required to successfully compete for state funds and federal tax credits.
New Affordable/PSH Units (services/ops)
Based on model R2H2 proposals, with costs including property management and supportive services. Services costs in PSH units are twice those assumed for dedicated affordable units, while property management costs held standard across the models. See the Terner Center's Permanent Supportive Housing as a Solution toHomelessness for comparison of PSH and general LIHTC costs.
Interim Housing
New Interim Units (capital)
Based on review of model R2H2, round 4 proposals. Assumes mix of acquisition & rehab and modular, but excludes less-optimal models like tough sheds.
New Interim Units (services/ops)
Based on review of model R2H2, round 4 proposals, current well-performing programs in the City, and interviews with providers on actual costs. 16 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
Limitations Like any attempt to model complex human systems, the Solutions Modeling tool is
not
a
perfect
representation
of
reality.
Many
broad
social
forces–fluctuations
in
the
economy
or
policy
decisions
made
at
the
state
or
federal
level–cannot
be
accounted
for
even
though
their
impact
on
homelessness
and
response
systems
is
undeniable.
The
high-level
estimates
the
model
produces
cannot
address
all
the
nuanced
details
required
in
the
process
of
implementing
such
a
strategy.
This
blueprint
provides
a
picture
of
what
we
will
need
to
build,
but
an
extraordinary
amount
of
decisions,
collaboration,
and
problem-solving
will
be
needed
to
make
it
a
reality.
There are several more specific limitations of the tool and estimates worth acknowledging,
several
with
important
implications
for
implementation.
First,
while
we
believe
that
we
are
drawing
on
the
best
available
data
to
serve
the
purposes
of
the
Solution
Modeling
tool,
data
sources
on
homelessness
are
notoriously
imprecise.
For
example,
available
data
for
the
number
of
households
both
experiencing
and
resolving
episodes
of
homelessness
in
a
given
year
are
indicative,
but
likely
both
undercounts.
Next, given the difficulty of accurately calculating current city and county spending
on
homelessness
programs,
it
can
be
difficult
to
contextualize
the
estimates
for
additional
funding
produced
by
the
model.
And
given
the
significant
fluctuation
of
homelessness
funding
from
state
and
federal
sources,
the
assumption
that
current
spending
will
remain
steady
is
anything
but
assured.
Our high-level modeling estimates—which lump solutions into broad categories—are
not
intended
to
imply
that
the
needs
of
people
experiencing
homelessness
are
homogenous.
The
programs
and
practices
required
to
best
assist
those
vulnerable
to
or
currently
experiencing
homelessness
are
more
nuanced
and
detailed
than
our
estimates
can
convey.
The
system
modeling
also
doesn’t
include
the
full
constellation
of
programs
or
supportive
services
that
play
an
important
role
in
getting
or
keeping
someone
stably
housed.
The
model’s
focus
on
housing
assistance–the
most
important
and
resource-intensive
form
of
assistance
for
preventing
and
resolving
homelessness–should
not
distract
from
the
important
role
played
by
other
efforts
like
job
training,
benefits
advocacy,
and
support
for
behavioral
health
needs.
A final limitation to note involves implementation considerations related to the model’s
estimates
for
newly
developed
housing
stock.
While
the
modeled
estimates
focus
solely
on
the
number
of
new
affordable
and
supportive
units
17 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND
needed for formerly homeless households, units serving this population are frequently
a
minority
of
the
total
units
in
a
new
development.
The
structure
of
state
and
federal
financing
means
buildings
serving
100%
people
exiting
homelessness
with
extremely
low
incomes
are
often
financially
and
operationally
unsustainable.
Implementing
the
strategy,
then,
would
likely
require
developing
additional
units
dedicated
to
a
larger
spectrum
of
low-income
households,
housing
for
which
there
is
also
an
urgent
need.
Looking Ahead Estimates produced through the Solutions Modeling analysis provide useful direction-setting
for
Oakland's
Homelessness
Strategic
Action
Plan.
Moving
forward,
these
targets
should
be
regularly
reassessed
to
reflect
the
changing
context
in
which
the
city
pursues
its
goals.
The
release
of
Alameda
County’s
Home
Together
2030
homelessness
strategic
plan–set
for
completion
later
in
2026–provides
perhaps
the
most
proximate
opportunity
to
update
investment
and
inventory
targets
so
they
better
align
with
the
more
recent,
countywide
system
modeling.
Doing
so
provides
the
city
and
county
the
opportunity
to
further
align
strategic
priorities
and
delineate
roles
and
responsibilities
in
pursuing
shared
goals
of
preventing
and
reducing
homelessness
and
closing
the
5-year
funding
gap
to
successfully
reduce
unsheltered
homelessness
in
Oakland
by
50 percent.
18 MODELING SOLUTIONS TO HOMELESSNESS IN OAKLAND