The influence of a transport process on the epidemic threshold.

Diffusive transport Epidemics on networks Mean-field model Multiplex network model

Journal

Journal of mathematical biology
ISSN: 1432-1416
Titre abrégé: J Math Biol
Pays: Germany
ID NLM: 7502105

Informations de publication

Date de publication:
28 10 2022
Historique:
received: 09 12 2021
accepted: 05 07 2022
revised: 27 04 2022
entrez: 28 10 2022
pubmed: 29 10 2022
medline: 2 11 2022
Statut: epublish

Résumé

By generating transient encounters between individuals beyond their immediate social environment, transport can have a profound impact on the spreading of an epidemic. In this work, we consider epidemic dynamics in the presence of the transport process that gives rise to a multiplex network model. In addition to a static layer, the (multiplex) epidemic network consists of a second dynamic layer in which any two individuals are connected for the time they occupy the same site during a random walk they perform on a separate transport network. We develop a mean-field description of the stochastic network model and study the influence the transport process has on the epidemic threshold. We show that any transport process generally lowers the epidemic threshold because of the additional connections it generates. In contrast, considering also random walks of fractional order that in some sense are a more realistic model of human mobility, we find that these non-local transport dynamics raise the epidemic threshold in comparison to a classical local random walk. We also test our model on a realistic transport network (the Munich U-Bahn network), and carefully compare mean-field solutions with stochastic trajectories in a range of scenarios.

Identifiants

pubmed: 36307593
doi: 10.1007/s00285-022-01810-7
pii: 10.1007/s00285-022-01810-7
pmc: PMC9616790
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

62

Informations de copyright

© 2022. The Author(s).

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Auteurs

Christian Kuehn (C)

Department of Mathematics, Technical University of Munich, Boltzmannstraße 3, 85748, Garching bei München, Germany.
Complexity Science Hub Vienna, Josefstädter Straße 39, 1080, Vienna, Austria.

Jan Mölter (J)

Department of Mathematics, Technical University of Munich, Boltzmannstraße 3, 85748, Garching bei München, Germany. jan.moelter@tum.de.

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