Loice-vanessa/AI-EPSIMES

Epidemic Spread Simulation System for Rwanda — React/TS frontend + FastAPI backend # Epidemic Spread Simulation System An AI-driven epidemic spread simulation platform for public health planning and outbreak preparedness. Frontend design generated by Magic Patterns (source design); backend built to give the core flow (auth, disease parameters, SEIR simulation) a real implementation instead of mock data. - `src/` — React + TypeScript + Tailwind frontend - `backend/` — FastAPI + SQLAlchemy backend (see `backend/README.md`) ## Running locally **Backend** (terminal 1): ```bash cd backend python -m venv venv ./venv/Scripts/activate pip install -r requirements.txt cp .env.example .env uvicorn app.main:app --reload --port 8000 ``` **Frontend** (terminal 2): ```bash npm install npm run dev ``` Open `localhost`. Sign in with one of the demo accounts shown on the login screen (click one to autofill) — these are real accounts, seeded into the backend database on first run. ## What's real vs. mock | Module | Status | | ------------------------------------ | -------------------------------------------------------------- | | Auth (register/login/session) | **Real** — JWT, bcrypt, persisted users | | RBAC | **Real** — enforced server-side, matches `src/lib/rbac.ts` | | Disease parameter presets | **Real** — served from the backend, seeded on first run | | SEIR simulation | **Real** — SciPy `solve_ivp` ODE integration, persisted runs | | Everything else (Population, Agent-Based, Interventions, Geographic, Healthcare Capacity, Scenario Comparison, Reports, Admin/Officer/Policy dashboards) | Frontend mock data from the original Magic Patterns export | See `backend/README.md` for API details and how to extend further modules.