{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/epidemiological-agent-based-modelling","title":"Epidemiological Agent-Based Modelling Software (Epiabm)","arxiv_id":"2212.04937","date":"2022-12-07","proceeding":null,"authors":["Kit Gallagher","Ioana Bouros","Nicholas Fan","Elizabeth Hayman","Luke Heirene","Patricia Lamirande","Annabelle Lemenuel-Diot","Ben Lambert","David Gavaghan","Richard Creswell"],"abstract":"Epiabm is a fully tested, open-source software package for epidemiological agent-based modelling, re-implementing the well-known CovidSim model from the MRC Centre for Global Infectious Disease Analysis at Imperial College London. It has been developed as part of the first-year training programme in the EPSRC SABS:R3 Centre for Doctoral Training at the University of Oxford. The model builds an age-stratified, spatially heterogeneous population and offers a modular approach to configure and run epidemic scenarios, allowing for a broad scope of investigative and comparative studies. Two simulation backends are provided: a pedagogical Python backend (with full functionality) and a high performance C++ backend for use with larger population simulations. Both are highly modular, with comprehensive testing and documentation for ease of understanding and extensibility. Epiabm is publicly available through GitHub at https://github.com/SABS-R3-Epidemiology/epiabm.","url_abs":"https://arxiv.org/abs/2212.04937v1","url_pdf":"https://arxiv.org/pdf/2212.04937v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"epidemiological-agent-based-modelling","repo_url":"https://github.com/SABS-R3-Epidemiology/epiabm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"epidemiology","task_name":"Epidemiology"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}