# Chimera states in multi-strain epidemic models with temporary immunity

**Authors:** Larissa Bauer (1), Jason Bassett (1), Philipp H\"ovel (1, 2), Yuliya, N. Kyrychko (3), Konstantin B. Blyuss (3) ((1) Institut f\"ur Theoretische, Physik, Technische Universit\"at Berlin, Germany, (2) Bernstein Center for, Computational Neuroscience Berlin, Humboldt-Universit\"at zu Berlin, Germany,, (3) Department of Mathematics, University of Sussex, Brighton, United, Kingdom)

arXiv: 1705.03395 · 2018-05-21

## TL;DR

This paper explores how time delays and cross-immunity influence the complex dynamics of multi-strain epidemic models, revealing phenomena like chimera states and various synchronization patterns.

## Contribution

It introduces a comprehensive analysis of delay-induced bifurcations and the emergence of chimera states in multi-strain epidemic models with different coupling topologies.

## Key findings

- Delay causes Hopf and saddle-node bifurcations affecting disease dynamics.
- Cross-immunity induces complex behaviors like traveling waves and chimera states.
- Chimera states occur with narrower cross-immunity kernels, impacting disease spread understanding.

## Abstract

We investigate a time-delayed epidemic model for multi-strain diseases with temporary immunity. In the absence of cross-immunity between strains, dynamics of each individual strain exhibits emergence and anni- hilation of limit cycles due to a Hopf bifurcation of the endemic equilibrium, and a saddle-node bifurcation of limit cycles depending on the time delay associated with duration of temporary immunity. Effects of all-to-all and non-local coupling topologies are systematically investigated by means of numerical simulations, and they suggest that cross-immunity is able to induce a diverse range of complex dynamical behaviors and synchro- nization patterns, including discrete traveling waves, solitary states, and amplitude chimeras. Interestingly, chimera states are observed for narrower cross-immunity kernels, which can have profound implications for understanding the dynamics of multi-strain diseases.

## Full text

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## Figures

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## References

62 references — full list in the complete paper: https://tomesphere.com/paper/1705.03395/full.md

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Source: https://tomesphere.com/paper/1705.03395