Model overview
MOOOD is an open-source discrete-event simulation developed by Richard Pilbery and colleagues. It follows callers after an NHS 111 primary-care disposition and represents subsequent contact with primary care, NHS 111, ambulance services and emergency departments. The Python and SimPy model compares the existing system with timely primary-care contact and reports activity across services and avoidable ED attendance.
The original data and parameters relate to callers registered with Bradford and Airedale GP practices, so reuse elsewhere requires local review and validation.
Session objectives and outline
This session will focus on obtaining the code and running the existing analysis. Participants will:
- clone the GitHub repository and identify the main execution and documentation files;
- create the Python environment and install the required dependencies;
- run the model and, where appropriate, its interactive application;
- reproduce an existing scenario and compare its behaviour with the published paper; and
- explore the current inputs and outputs while accounting for stochastic variation.
The aim is for participants to leave with a local copy of the repository, a working environment and a successful model run that they can continue to explore.
Actions for participants before the session
- Bring a laptop on which you can use GitHub and install or run Python.
- Clone or download the MOOOD repository.
- Follow the generated documentation and repository setup instructions as far as you can.
- Read the abstract and strengths and limitations in the BMJ Open paper.
Additional resources
- GitHub repository — model, application, tests, data and container configuration.
- Generated technical documentation — documentation for the codebase.
- BMJ Open paper — peer-reviewed methods, results and limitations.
- Full text in PubMed Central — alternative open-access version of the paper.