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Communication dans un congrès Année : 2023

Exploring and optimising infectious disease policies with a stylised agent-based model

Résumé

The quantitative study of the spread of infectious diseases is a crucial aspect to design health policies and foster responsiveness, as the recent COVID-19 pandemic showed at an unprecedented scale. In-between abstract theoretical models and large-scale data driven microsimulation models lie a broad set of modelling tools, which may suffer from various issues such as parameter uncertainties or the lack of data. We introduce in this paper a stylised ABM for infectious disease spreading, based on the SIRV compartmental model. We account for a certain level of geographical detail, including commuting modes and workplaces. We apply to it a set of model validation methods, including global sensitivity analysis, surrogates, and multi-objective optimisation. This shows how such methods could be a new tool for more robust design and optimisation of infectious disease policies.
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Dates et versions

hal-04428487, version 1 (31-01-2024)

Licence

Paternité - CC BY 4.0

Identifiants

Citer

Jeonghwa Kang, Juste Raimbault. Exploring and optimising infectious disease policies with a stylised agent-based model. French Regional Conference on Complex Systems, May 2023, Le Havre, France. pp.179-196, ⟨10.5281/zenodo.7957531⟩. ⟨hal-04428487⟩
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Dernière date de mise à jour le 28/04/2024
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