Exploring and optimising infectious disease policies with a stylised agent-based model - IRISA Accéder directement au contenu
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.
Fichier principal
Vignette du fichier
FRCCS2023_Kang-Raimbault.pdf (826.05 Ko) Télécharger le fichier
O4_2815_Juste_Raimbault.pdf (1.35 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Format : Présentation
Commentaire : Slides

Dates et versions

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

Licence

Paternité

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⟩
19 Consultations
12 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More