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Reproducible Healthcare Simulations in Python and R

For the UKRI-funded project STARS: Sharing Tools and Artefacts for Reproducible Simulations

STARS: Sharing Tools and Artefacts for Reproducible Simulations

STARS Framework

The STARS framework is a set of open practices, tools and learning materials to produce enhanced versions of research artefacts that intend to increase accessibility for others to (re)use, adapt and build on work.

Essential components of STARS framework (shaded in green below):

  • Open license
  • Dependency management
  • Model created using free and open-source software (FOSS)
  • Minimum documentation
  • Research artefact meta data (ORCID ID + citation information)
  • Remote code repository
  • Open science archive

Optional components of STARS framework (shaded in blue below):

  • Enhanced documentation
  • Documentation hosting
  • Online coding environment
  • Model interface
  • Web app hosting

STARS framework overview

Repositories

Several repositories are related to our recent paper 'Towards sharing tools and artefacts for reusable simulations in healthcare', which includes three examples of the implemented STARS framework in Python:

Repositories Description
stars-treat-sim STARS paper example 1. Implements essential components + annotated notebook to run code executable online with Binder
stars-simpy-example-docs

stars-streamlit-example
STARS paper example 2. Fully implements essential + optional components including enhanced documentation hosted online and web app
stars-ciw-example STARS paper example 3. Fully implements essential + optional components, but with different licence, documentation publishing software, web app framework and web app hosting

Subsequently, we have been developing similar examples in R, as well as looking at webassembly:

Repositories Description
stars-treat-simmer R simmer implementation of treatment simulation model
stars-shiny-simmer Template for shiny interface to simmer DES model
stars-stlite-example stlite template for SimPy models
stars-simpy-jupterlite JupyterLite template for SimPy models

As part of STARS, we are assessing the reproducibility of published simualation models, with related repositories as follows:

Repositories Description
stars-reproduction-protocol Latex files for reproduction protocol
stars-reproduce-allen-2020 Test run of reproducibility protocol on Allen et al. 2020
stars-reproduction-template Template for assessment of computational reproducibility
stars-reproduce-shoaib-2022 Reproduction study 1: Shoaib and Ramamohan 2022 (Python)
stars-reproduce-huang-2019 Reproduction study 2: Huang et al. 2019 (R)
stars-reproduce-lim-2020 Reproduction study 3: Lim et al. 2020 (Python)
stars-reproduce-kim-2021 Reproduction study 4: Kim et al. 2021 (R)
stars-reproduce-anagnostou-2022 Reproduction study 5: Anagnostou et al. 2022 (Python)
stars-reproduce-johnson-2021 Reproduction study 6: Johnson et al. 2021 (R)
stars-reproduce-hernandez-2015 Reproduction study 7: Hernandez et al. 2015 (Python model + R figures)
stars-reproduce-wood-2021 Reproduction study 8: Wood et al. 2021 (R)
stars_wp1_summary Summary of the eight computational reproducibility assessments conducted as part of STARS Work Package 1. These assessed discrete-event simulation papers with models in Python and R.

There is a tutorial on discrete-event simulation for the Operational Research Society Simulation Workshop 2025:

Repositories Description
intro-open-sim An introduction to Discrete-Event Simulation using Free and Open Source Software

Other repositories are:

Repositories Description
stars-publications List of all STARS publications
stars-logo SVG and PNG files with logo
stress_update A review and update of the Strengthening the Reporting of Empirical Simulation Studies guidelines for DES, SD, and ABS.
stars-eom-rcc Modifications to the "Exeter Oncology Model: Renal Cell Carcinoma edition (EOM-RCC)" as part of STARS work package 3.
stars_wp3_summary Reflections from prospective and retrospective application of the STARS framework

Team

Member ORCID GitHub
Thomas Monks ORCID: Monks https://github.com/TomMonks
Alison Harper ORCID: Harper https://github.com/AliHarp
Navonil Mustafee ORCID: Mustafee https://github.com/NavonilNM
Andrew Mayne ORCID: Mayne https://github.com/andy-mayne
Amy Heather ORCID: Heather https://github.com/amyheather

Popular repositories Loading

  1. stars-simpy-jupterlite stars-simpy-jupterlite Public template

    A template for Discrete-Event Simulation (DES) repositories that use JupyerLite and xeus-python to enable reproducible environments and models

    Jupyter Notebook 3

  2. stars-shiny-simmer stars-shiny-simmer Public

    WORK IN PROGRESS: An example R shiny interface to a simmer DES model.

    JavaScript 3

  3. stars-eom-rcc stars-eom-rcc Public

    Forked from nice-digital/NICE-model-repo

    Modifications to the "Exeter Oncology Model: Renal Cell Carcinoma edition (EOM-RCC)" as part of STARS work package 3.

    R 3

  4. stars-publications stars-publications Public

    A list of all STARS publications including journals articles, conference papers, book chapters, pre-prints and presentations

    2

  5. stars-treat-simmer stars-treat-simmer Public

    R Simmer implemention of the treatment simulation model

    R 2

  6. stars-logo stars-logo Public

    STARS branding

    2

Repositories

Showing 10 of 34 repositories
  • rap_template_python_des Public template

    Template reproducible analytical pipeline (RAP) for simple python discrete-event simulation (DES) model.

    pythonhealthdatascience/rap_template_python_des’s past year of commit activity
    Jupyter Notebook 2 MIT 0 0 0 Updated Dec 20, 2024
  • pythonhealthdatascience/stars-treat-simmer-quarto-wasm’s past year of commit activity
    Lua 0 MIT 0 0 0 Updated Dec 12, 2024
  • rap_des Public

    Documentation supporting template reproducible analytical pipelines (RAP) for simple python and R discrete-event simulation (DES) models.

    pythonhealthdatascience/rap_des’s past year of commit activity
    0 MIT 0 0 0 Updated Dec 10, 2024
  • stars_wp1_summary Public

    Summary of the eight computational reproducibility assessments conducted as part of STARS Work Package 1. These assessed discrete-event simulation papers with models in Python and R.

    pythonhealthdatascience/stars_wp1_summary’s past year of commit activity
    TeX 1 CC-BY-4.0 0 0 0 Updated Dec 10, 2024
  • rap_template_r_des Public template

    Template reproducible analytical pipeline (RAP) for simple R discrete-event simulation (DES) model.

    pythonhealthdatascience/rap_template_r_des’s past year of commit activity
    0 MIT 0 0 0 Updated Dec 5, 2024
  • stars-eom-rcc Public Forked from nice-digital/NICE-model-repo

    Modifications to the "Exeter Oncology Model: Renal Cell Carcinoma edition (EOM-RCC)" as part of STARS work package 3.

    pythonhealthdatascience/stars-eom-rcc’s past year of commit activity
    R 3 MIT 2 0 0 Updated Nov 25, 2024
  • stars-reproduce-wood-2021 Public

    Assessing the computational reproducibility of Wood et al. 2021 as part of STARS.

    pythonhealthdatascience/stars-reproduce-wood-2021’s past year of commit activity
    TeX 0 GPL-3.0 0 0 0 Updated Nov 21, 2024
  • stars-reproduce-hernandez-2015 Public

    Assessing the computational reproducibility of Hernandez et al. 2015 as part of STARS.

    pythonhealthdatascience/stars-reproduce-hernandez-2015’s past year of commit activity
    TeX 0 MIT 0 0 0 Updated Nov 21, 2024
  • stars-reproduce-johnson-2021 Public

    Assessing the computational reproducibility of Johnson et al. 2021 as part of STARS.

    pythonhealthdatascience/stars-reproduce-johnson-2021’s past year of commit activity
    R 0 GPL-3.0 0 0 0 Updated Nov 21, 2024
  • stars-reproduce-anagnostou-2022 Public

    Assessing the computational reproducibility of Anagnostou et al. 2022 as part of STARS.

    pythonhealthdatascience/stars-reproduce-anagnostou-2022’s past year of commit activity
    Jupyter Notebook 0 BSD-3-Clause 0 0 0 Updated Nov 21, 2024

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