Modelling COVID-19 Ripple Effect and Global Supply Chain Productivity Impacts Using a Reaction-Diffusion Time-Space SIS Model - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

Modelling COVID-19 Ripple Effect and Global Supply Chain Productivity Impacts Using a Reaction-Diffusion Time-Space SIS Model

Morteza Davari
  • Fonction : Auteur
  • PersonId : 1172336
Aseem Kinra
  • Fonction : Auteur

Résumé

As the COVID pandemic shows, infection spreads widely across regions, impacting economic activity in unforeseen ways. We represent here how the geographic spread of the pandemic, by reducing the workers’ participation to economic life, undermines the ability of firms and as a result the entire supply networks to satisfy customers’ demands. We model the spatio-temporal dynamics of the propagation of Covid-19 infection on population, transport networks, facilities and population flows. The mathematical models will enable prospective analyses to be performed reliably. Such models will be used in what-if scenarios to simulate the impact on both populations and supply chain activities in case of future pandemics. The outcome should be useful tools for policymakers and managers. Results from this research will help in understanding the impact and the spread of a pandemic in a particular region and on supply chains. The data will be from European regions and the expected models will have validity in Europe.
Fichier principal
Vignette du fichier
520761_1_En_1_Chapter.pdf (529.48 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03806518 , version 1 (07-10-2022)

Licence

Paternité

Identifiants

Citer

Morteza Davari, Aseem Kinra, Davide La Torre, Xavier Brusset. Modelling COVID-19 Ripple Effect and Global Supply Chain Productivity Impacts Using a Reaction-Diffusion Time-Space SIS Model. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.3-12, ⟨10.1007/978-3-030-85910-7_1⟩. ⟨hal-03806518⟩
26 Consultations
2 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More