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3D topological modeling and multi-agent movement simulation for viral infection risk analysis

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  • Additional Information
    • Publication Date:
      2025
    • Collection:
      The University of Manchester: Research Explorer - Publications
    • Abstract:
      This paper introduces an integrated method that combines computer-aided modelling of indoor environments, multi-agent movement simulation and airborne viral transmission modelling to analyse how spatial design and occupant behaviour affect disease spread. Using TopologicPy, interior spaces are represented as connected networks that support navigation-graph generation and agent movement based on schedules, walking speeds and activities. Agents move incrementally along shortest paths, while the system calculates precise inter-agent distances and respects architectural constraints such as walls and doorways. Viral aerosol concentrations are modelled via a reaction-diffusion equation, and infection risk is estimated using an extended Wells–Riley model. By capturing detailed spatio-temporal and topological interactions, the framework offers realistic infection-risk assessments. The resulting tool serves as a rapid decision-support system for policymakers, facility managers and designers, enabling evaluation of mitigation strategies and informing future building design. A comparative study of cellular and open-plan offices demonstrates the method’s capabilities.
    • ISSN:
      0003-8628
      1758-9622
    • Relation:
      info:eu-repo/semantics/altIdentifier/pissn/0003-8628; info:eu-repo/semantics/altIdentifier/eissn/1758-9622
    • Accession Number:
      10.1080/00038628.2025.2603534
    • Online Access:
      https://research.manchester.ac.uk/en/publications/14622bad-0611-446c-9fa6-74a57e1c5363
      https://doi.org/10.1080/00038628.2025.2603534
      https://www.tandfonline.com/doi/full/10.1080/00038628.2025.2603534
    • Rights:
      info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/
    • Accession Number:
      edsbas.BF9EC983