What is Optomitron?
Optomitron identifies which policies, budgets, and interventions actually minimize suffering, eradicate preventable disease, and extend healthy lives — using time series data and causal inference across 20+ countries.
Governments allocate trillions every year, but rarely know what works. We apply causal analysis to real-world policy outcomes — comparing jurisdictions, tracking natural experiments, and scoring interventions by their actual impact on human welfare.
At its core, Optomitron provides a universal causal inference engine that takes any two time series and answers: Does changing X cause Y to change? By how much? What's the optimal value of X?
The Problem
Preventable deaths
Millions die every year from diseases and conditions we know how to prevent or treat. Resources aren't allocated to what works — they're allocated to what's politically convenient.
Policy by anecdote
Governments allocate trillions based on ideology and negotiation, not evidence of what actually improves outcomes. Nobody systematically measures what works.
No feedback loop
When a policy works in one jurisdiction, there's no systematic way to identify it and replicate it elsewhere. Successes go unnoticed; failures get repeated.
Architecture
COLLECT
- Health data
- Preferences
- Outcomes
- Spending
- Policies
INFER
- Temporal alignment
- Bradford Hill
- Effect sizes
- PIS scoring
RECOMMEND
- Policy rankings
- Budget levels
- Preference weights
- Optimal values
📄 Papers
Every algorithm in this codebase is defined in a published paper with exact formulas, worked examples, and parameter justifications.
dFDA Specification
@optomitron/optimizer
PIS, temporal alignment, Bradford Hill, effect sizes
Read paper →Wishocracy
@optomitron/wishocracy
RAPPA pairwise preference aggregation, eigenvector weights
Read paper →Optimal Policy Generator
@optomitron/opg
Policy Impact Score, Causal Confidence Score, method weights
Read paper →Optimal Budget Generator
@optomitron/obg
Diminishing returns, Optimal Spending Level, Budget Impact Score
Read paper →Optimocracy
Shared
Two-metric welfare function (shared by OPG + OBG)
Read paper →📦 Packages
| Package | Description | Status |
|---|---|---|
| @optomitron/optimizer | Domain-agnostic causal inference engine | 🟡 Alpha |
| @optomitron/wishocracy | RAPPA preference aggregation | 🟡 Alpha |
| @optomitron/opg | Optimal Policy Generator | 🟡 Alpha |
| @optomitron/obg | Optimal Budget Generator | 🟡 Alpha |
| @optomitron/data | Data fetchers & loaders (OECD, World Bank, etc.) | 🟡 Alpha |
| @optomitron/web | This website | 🟢 Active |
| @optomitron/extension | Chrome extension for personal health | ⚪ Planned |
| @optomitron/chat-ui | Conversational chat UI | ⚪ Planned |
Coming Soon
Decentralized health data collection. Individuals contribute anonymized health outcomes to build the dataset from the ground up — accelerating disease eradication and suffering reduction. Your data stays on your device; the causal engine runs locally in your browser.
Star on GitHubMIT License © Mike P. Sinn