Cluster formation for multi-strain infections with cross-immunity

DOI10.1016/J.JTBI.2004.09.016zbMath1442.92157OpenAlexW2044411186WikidataQ54313972 ScholiaQ54313972MaRDI QIDQ781187

Andrei Korobeinikov, Vincent Calvez, Philip K. Maini

Publication date: 16 July 2020

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://ora.ox.ac.uk/objects/uuid:8702ca55-509d-451b-8e24-0f563f953c64

zbMATH Keywords

clustermathematical modellinginfectious diseasecross-immunityself-organisation

Mathematics Subject Classification ID

Epidemiology (92D30) Stability of solutions to ordinary differential equations (34D20)

Related Items (10)

An age-structured multi-strain epidemic model for antigenically diverse infectious diseases: a multi-locus framework ⋮ On the dynamics of matrix models for immune clonal networks ⋮ Chimera states in multi-strain epidemic models with temporary immunity ⋮ Antigenic distance and cross-immunity, invasibility and coexistence of pathogen strains in an epidemiological model with discrete antigenic space ⋮ Mathematical analysis of a multiple strain, multi-locus-allele system for antigenically variable infectious diseases revisited ⋮ Bifurcation, stability, and cluster formation of multi-strain infection models ⋮ Analysis of symmetries in models of multi-strain infections ⋮ Cross-immunity, invasion and coexistence of pathogen strains in epidemiological models with one-dimensional antigenic space ⋮ Analysis of the multistrain asymmetric SI model for arbitrary strain diversity ⋮ A continuous phenotype space model of RNA virus evolution within a host

Cites Work

• The dynamics of cocirculating influenza strains conferring partial cross-immunity
• A status-based approach to multiple strain dynamics
• The onset of oscillatory dynamics in models of multiple disease strains
• Dynamics of two mutually coupled slow inhibitory neurons
• Dynamics of influenza A drift: The linear three-strain model
• Partial Synchronization in a Network of Neural Oscillators
• Nonlinear dynamics of chaotic and stochastic systems. Tutorial and modern developments
• Analysis of clustered firing patterns in synaptically coupled networks of oscillators

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