Can You Save 1,000 Lives?

Bend the Curve · Washington Overdose Model

Overdose deaths • 2018 — 2025*
— — Total deaths
V2/V1 OD deaths (growth-rate period)
V2 — — —

V1 — — —
time to double
— years
Calculated from State data • —
Actual 2025* • projection start
— — 2025*
Est. 2026 • current slider settings
— — Est. 2026
Predicted 2027 • current slider settings
— — Pred. 2027
Growth rate from observed period:
Chooses the V1–V2 date range that sets the natural (no-policy) annual growth rate, time to double or half-life of the modeled series. Projections always start from the actual 2025* count. *2025 is preliminary DOH data.
OD Cause
Switches the model (baseline, projections, t-double or half-life, chart, lives saved) between total, fentanyl, opiate, stimulant, oxycodone (Rx opioid), heroin, cocaine, and alcohol poisoning deaths. Stimulant = DOH psychostimulants category, mostly methamphetamine (excludes cocaine). Alcohol poisoning = DOH alcohol poisoning category: deaths where acute alcohol poisoning was a cause; does not include alcohol-related crashes, falls, or liver disease.

Policy Levers

Discourage Addict Migration / Inflow
Reduce net arrival of active users
0 %
0% (status quo)
100% (strong discouragement)
Criminalize Use & Distribution
Enforcement + deterrence impact
0 %
0% (current approach)
100% (strong enforcement)
Projection horizon
6 years (2026–2029)

Default: 4 years (2026–2029); maximum 10. Beyond a few years the lines show what pure compounding implies, not a forecast.

HOW THE MODEL WORKS
Growth comes from two drivers:
• Inflow/migration of new users (35% of growth)
• Lethality + distribution among existing users (65%)

Sliders reduce the compounding growth rate in proportion to those shares; both at 100% turn growth into a decline. Projections start from the actual 2025 count (preliminary).
t-double or half-life = ln(2) / |growth rate|, per the equations.
BASELINE (no change)
—
Projected deaths in —
WITH POLICY CHANGES
—
Projected deaths in —
LIVES SAVED
—
cumulative vs. baseline trajectory
BASELINE t-double
— years
time to double (t-double > 0 when V₂/V₁ > 1)
POLICY — t-Double or Half-Life
—
—
Projected OD Deaths
Observed years, then projection
Observed
Baseline
With policies
Year-by-year: observed, then projected
Scroll for more years →
Year Baseline With Policies Difference T_d / Half-life
(observed: from first row · projected: from 2025)
This is a simplified exponential model for illustrative purposes. Real-world outcomes depend on many variables including supply, treatment access, and enforcement consistency.