Addiction Treatment Pathway Simulator

Treatment Program Mix

Medication-Assisted Treatment 55%

Behavioral Therapy (CBT / group) 55%

Family & Peer Support 40%

Multidisciplinary Team Staffing 45%

Cohort State

Active Use — untreated

Engaged in Treatment

Stable Recovery

Active Use

In Treatment

Stable Recovery

Months Elapsed

How it works

Each of the 150 patients occupies one of three states — Active Use, Engaged in Treatment, or Stable Recovery — and every simulated month makes an independent random transition, exactly like a discrete-time Markov chain:

entry     P(Use → Treatment)      = 0.10 + 0.30·team
dropout   P(Treatment → Use)      = 0.12·(1 − 0.5·team − 0.25·fam)
complete  P(Treatment → Recovery) = 0.05 + 0.30·(0.45·mat + 0.35·cbt + 0.20·fam)
relapse   P(Recovery → Use)       = 0.05·(1 − 0.5·mat − 0.3·fam)

where mat, cbt, fam, team are the slider values scaled to 0–1. Medication-assisted treatment and family/peer support both suppress relapse; case-management staffing mainly drives outreach (entry) and retention (dropout); behavioral therapy and MAT together drive how fast an engaged patient reaches stable recovery. All rates are clamped to [0.005, 0.95] so no transition ever becomes impossible or certain.

Every 1.1 simulated seconds is one "month" tick — each patient rolls an independent uniform random number against the current rates and, on success, is reassigned a new target position near the corresponding station; positions ease toward their target every frame, so the cohort visibly migrates between the three stations as the program mix changes.

Active Use: 0

In Treatment: 0

Stable Recovery: 0

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