Welcome

Author

Affiliation

Ms Amy Heather

Peninsula Collaboration for Health Operational Research and Data Science (PenCHORD), University of Exeter Medical School

This is a guide to writing discrete-event simulation (DES) models in Python and R which are reproducible and form a reproducible analytical pipeline (RAP).

It guides you through creating these models whilst meeting requirements from:

• 🌿 Heather et al. 2025 “On the reproducibility of discrete-event simulation studies in health research: an empirical study using open models”
• 🏥 The “Levels of RAP” framework from the NHS RAP Community of Practice

The models are created using:

• SimPy for Python - https://simpy.readthedocs.io/en/latest/.
• simmer for R - https://r-simmer.org/.

How to use this book?

• Go step-by-step. Follow the book from beginning to end to build a reproducible DES model from scratch; or-
• Pick and choose. Skip around and dive into sections that are most helpful for your RAP or project.

Note: Even though the main example is about healthcare simulation, the tips on reproducibility and coding practices apply to all kinds of models, fields, and analysis techniques.

It has been developed as part of the STARS project:

All code in this book is provided under the MIT licence. The accompanying text is licensed under a Creative Commons Attribution-ShareAlike 4.0 International license.