A Python Dash-based pandemic and epidemic simulation application that integrates with the Pandemic Exercise Simulator backend engine to model epidemics within all 50 US states + DC.
- Multiple Models
- Deterministic and stochastic compartmental, mechanistic models (SEIR, SEIRS, and SEATIRD)
- Interactive Controls
- Configure disease parameters and initial cases for every county and age group
- Interventions
- Model non-pharmaceutical interventions and vaccination across age groups
- US Counties
- Interactive maps with county-level visualizations
- Realistic Subgroups
- Population data from 2023 census stratified by age and high & low risk of severe outcome
- Real-time Simulation
- Live epidemic progression visualized on map and in time series
- Docker Ready
- Complete containerized deployment
- Docker and Docker Compose
- 8GB+ RAM recommended
- Ports 8000, 8050, 6379, 27017 available
Ensure the Docker application is running in the background.
git clone https://github.com/saroshaprasla/PandemicExerciseTool-Dash.git
cd /your/path/to/PandemicExerciseTool-Dash
docker-compose -f docker-compose-dash.yml up --build -dor using the Makefile
make start- Main Application: http://localhost:8050
- Backend API: http://localhost:8000
- click
api/petto see parameters sent to backend engine each run
- click
To check logs of containers find the container name or id, then print logs to your terminal window.
The -f flag will allow you to watch a log live. Ctrl+C will exit the log.
docker ps
docker logs <container_name_or_id>
docker logs -f <container_name_or_id>make stopwhich is equivalent to running
docker compose -f docker-compose.yml down
- dash-frontend (Port 8050): Python Dash web application
- django-backend (Port 8000): REST API and data management
- celery-worker: Background simulation processing with backend engine
- mongo-db (Port 27017): Simulation data storage
- redis (Port 6379): Celery message broker and caching