Data

Tools

Indexes

Applications

Experiments

Open Source Science

stars-reproduce-anagnostou-2022

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

https://github.com/pythonhealthdatascience/stars-reproduce-anagnostou-2022

Science Score: 77.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 9 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ✓
    Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (12.4%) to scientific vocabulary

Keywords

covid-19 discrete-event-simulation hospital-admissions icu intensive-care intensive-care-unit intensive-care-units nhs open-science python quarto reproducibility reproducible-research simpy simulation

Keywords from Contributors

simulation-model
Last synced: 4 months ago · JSON representation ·

Repository

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

Basic Info
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 3
Topics
covid-19 discrete-event-simulation hospital-admissions icu intensive-care intensive-care-unit intensive-care-units nhs open-science python quarto reproducibility reproducible-research simpy simulation
Created over 1 year ago · Last pushed 12 months ago
Metadata Files
Readme Changelog Contributing License Citation

README.md

Anagnostou et al. 2022 computational reproducibility assessment STARS

DOI

This repository forms part of work package 1 on the project STARS: Sharing Tools and Artefacts for Reproducible Simulations. It assesses the computational reproducibility of:

Anagnostou, A. Groen, D. Taylor, S. Suleimenova, D. Abubakar, N. Saha, A. Mintram, K. Ghorbani, M. Daroge, H. Islam, T. Xue, Y. Okine, E. Anokye, N. FACS-CHARM: A Hybrid Agent-Based and Discrete-Event Simulation Approach for Covid-19 Management at Regional Level. 2022 Winter Simulation Conference (WSC), Singapore, pp. 1223-1234. (2022). https://doi.org/10.1109/WSC57314.2022.10015462.

Note: This reproduction just focuses on the "CHARM" model from this paper.

Website

Click here to check out the website for this repository

This website is created using Quarto and hosted using GitHub Pages. It shares everything from this computational reproducibility assessment.

Protocol

The protocol for this work is summarised in the diagram below and archived on Zenodo:

Heather, A., Monks, T., Harper, A., Mustafee, N., & Mayne, A. (2024). Protocol for assessing the computational reproducibility of discrete-event simulation models on STARS. Zenodo. https://doi.org/10.5281/zenodo.12179846.

Workflow

Repository overview

bash .github workflows ... evaluation ... logbook ... original_study ... quarto_site ... reproduction ... .gitignore CHANGELOG.md CITATION.cff CONTRIBUTING.md LICENSE README.md _quarto.yml citation_apalike.apa citation_bibtex.bib index.qmd requirements.txt

Key sections: These folders have all the content related to the original study and reproduction...

  • original_study/ - Original study materials (i.e. journal article, supplementary material, code and any other research artefacts).
  • reproduction/ - Reproduction of the simulation model. Once complete, this functions as a research compendium for the model, containing all the code, parameters, outputs and documentation.
  • evaluation/ - Quarto documents from the evaluation of computational reproducibility. This includes the scope, assessment of reproduction success, and comparison of the original study materials against various guidelines, and summary report.
  • logbook/ - Daily record of work on this repository.

Other sections: The remaining files and folders support creation of the Quarto site to share the reproduction, or are other files important to the repository (e.g. README, LICENSE, .gitignore)...

  • .github/workflows/ - GitHub actions.
  • quarto_site/ - A Quarto website is used to share information from this repository (including the original study, reproduced model, and reproducibility evaluation). This folder contains any additional files required for creation of the site that do not otherwise belong in the other folders.
  • .gitignore - Untracked files.
  • CHANGELOG.md - Description of changes between GitHub releases and the associated versions on Zenodo.
  • CITATION.cff - Instructions for citing this repository, created using CFF INIT.
  • CONTRIBUTING.md - Contribution instructions for repository.
  • LICENSE - Details of the license for this work.
  • README.md - Description for this repository. You'll find a seperate README for the model within the reproduction/ folder, and potentially also the original_study/ folder if a README was created by the original study authors.
  • _quarto.yml - Set-up instructions for the Quarto website.
  • citation_apalike.bib - APA citation generated from CITATION.cff.
  • citation_bibtex.bib - Bibtex citation generated from CITATION.cff.
  • index.qmd - Home page for the Quarto website.
  • requirements.txt - Environment for creation of Quarto site (used by .github/workflows/quarto_publish.yaml).

Citation

Please cite the archived version of this repository on Zenodo:

Heather, A., Monks, T., & Harper, A. (2025). Anagnostou et al. 2022 computational reproducibility assessment. Zenodo. https://doi.org/10.5281/zenodo.13306159

You can also cite the repository on GitHub. Please refer to the citation file CITATION.cff, and the auto-generated alternatives citation_apalike.apa and citation_bibtex.bib.

License

This repository is licensed under the BSD 3-Clause License.

This is aligned with the original study, who also licensed their work under the BSD 3-Clause License.

Funding

This work is supported by the Medical Research Council [grant number MR/Z503915/1].

Owner

  • Name: pythonhealthdatascience
  • Login: pythonhealthdatascience
  • Kind: organization

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: 'Anagnostou et al. 2022 computational reproducibility assessment'
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Amy
    family-names: Heather
    email: a.heather2@exeter.ac.uk
    affiliation: University of Exeter Medical School, Exeter, UK
    orcid: 'https://orcid.org/0000-0002-6596-3479'
  - given-names: Thomas
    family-names: Monks
    email: t.m.w.monks@exeter.ac.uk
    affiliation: University of Exeter Medical School, Exeter, UK
    orcid: 'https://orcid.org/0000-0003-2631-4481'
  - given-names: Alison
    family-names: Harper
    email: a.l.harper@exeter.ac.uk
    affiliation: University of Exeter Business School, Exeter, UK
    orcid: 'https://orcid.org/0000-0001-5274-5037'
repository-code: >-
  https://github.com/pythonhealthdatascience/stars-reproduce-anagnostou-2022
abstract: >-
  This repository forms part of work package 1 on the project STARS: Sharing
  Tools and Artefacts for Reproducible Simulations. It assesses the
  computational reproducibility of: Anagnostou, A. Groen, D. Taylor, S.
  Suleimenova, D. Abubakar, N. Saha, A. Mintram, K. Ghorbani, M. Daroge, H.
  Islam, T. Xue, Y. Okine, E. Anokye, N. FACS-CHARM: A Hybrid Agent-Based and
  Discrete-Event Simulation Approach for Covid-19 Management at Regional Level.
  2022 Winter Simulation Conference (WSC), Singapore, pp. 1223-1234. (2022).
  https://doi.org/10.1109/WSC57314.2022.10015462.
license: BSD-3-Clause
# TODO: Manually update with each GitHub release (start with 0.1.0)
version: '1.0.0'
date-released: '2025-01-09'

GitHub Events

Total
  • Release event: 1
  • Push event: 6
  • Create event: 1
Last Year
  • Release event: 1
  • Push event: 6
  • Create event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 74
  • Total Committers: 2
  • Avg Commits per committer: 37.0
  • Development Distribution Score (DDS): 0.095
Past Year
  • Commits: 74
  • Committers: 2
  • Avg Commits per committer: 37.0
  • Development Distribution Score (DDS): 0.095
Top Committers
Name Email Commits
amyheather a****2@e****k 67
cffconvert GitHub Action c****t 7
Committer Domains (Top 20 + Academic)
exeter.ac.uk: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Dependencies

.github/workflows/cff_convert.yaml actions
  • actions/checkout v4 composite
  • citation-file-format/cffconvert-github-action 2.0.0 composite
.github/workflows/cff_validation.yaml actions
  • actions/checkout v3 composite
  • dieghernan/cff-validator v3 composite
.github/workflows/docker_ghr.yaml actions
  • actions/checkout v3 composite
  • docker/login-action v1 composite
.github/workflows/quarto_publish.yaml actions
  • actions/checkout v4 composite
  • actions/setup-python v4 composite
  • quarto-dev/quarto-actions/publish v2 composite
  • quarto-dev/quarto-actions/setup v2 composite
original_study/charm/Dockerfile docker
  • python 3.9-slim-buster build
original_study/charm/requirements.txt pypi
  • simpy *
requirements.txt pypi
  • jupyter ==1.0.0
  • matplotlib ==3.9.1
  • pandas ==2.2.2
  • plotly ==5.22.0
  • tenacity ==8.3.0