The Cost of
Doing Nothing

QuietCost helps municipal decision-makers understand the long-term fiscal consequences of delaying supportive housing interventions for people experiencing chronic homelessness.

11

Datasets Registered

1,000

Monte Carlo Runs

10 yrs

Simulation Horizon

6

Markov States

Net Present Cost of Delay

$12.4M – $18.7M

80% CI · 3-yr delay scenario

Population at Year 10

1,420 – 2,140

Chronic homeless, mid estimate

Intervention Savings

$6.1M – $9.3M

vs. Do Nothing scenario

Projected Annual System Cost — 10yr

2025
$52M
2026
$58M
2027
$65M
2028
$72M
2029
$78M
2030
$83M
Sample Output · 3-Year Delay Scenario

How QuietCost Works

A transparent, auditable simulation stack built on peer-reviewed methods — not a black box.

Markov Simulation

6-state discrete-time model with 1,000 Monte Carlo runs — never a single-point forecast.

Cost of Inaction

Quantifies the net present cost of delaying PSH interventions across shelter, healthcare, and justice.

Data Health

Auto-discovers 11 registered datasets. Monitors drift, staleness, and missingness in real time.

Responsible AI

Human-in-the-loop by design. Hard bypasses for stale data. No automated policy decisions.

Range Estimates

All outputs shown as probability ranges — never exact. Invisible population multipliers surfaced.

Decision Briefs

AI-generated plain-language summaries help non-technical policymakers understand the model output.

Responsible AI by Design

QuietCost does not make policy decisions or determine individual eligibility. All projections include uncertainty ranges. The simulator disables itself when data is older than 18 months, missingness exceeds 25%, or population falls below 100. Humans remain responsible for all final decisions.

Read Methodology →