How can contemporary climate research help to understand epidemic dynamics? -- Ensemble approach and snapshot attractors

TL;DR

This paper applies climate research concepts like snapshot attractors and ensemble analysis to epidemic models, revealing complex transient dynamics and variability that traditional single-trajectory approaches may overlook.

Contribution

It introduces the use of snapshot attractors from climate research to analyze epidemic models under changing parameters, highlighting transient chaos and ensemble effects.

Findings

Transient chaos influences epidemic outbreaks.

Ensemble analysis reveals variability unseen in single trajectories.

Snapshot attractors help understand epidemic dynamics under seasonal forcing.

Abstract

Standard epidemic models based on compartmental differential equations are investigated under continuous parameter change as external forcing. We show that seasonal modulation of the contact parameter superimposed a monotonic decay needs a different description than that of the standard chaotic dynamics. The concept of snapshot attractors and their natural probability distribution has been adopted from the field of the latest climate-change-research to show the importance of transient effect and ensemble interpretation of disease spread. After presenting the extended bifurcation diagram of measles, the temporal change of the phase space structure is investigated. By defining statistical measures over the ensemble, we can interpret the internal variability of the epidemic as the onset of complex dynamics even for those values of contact parameter where regular behavior is expected. We argue that anomalous outbreaks of infectious class cannot die out until transient chaos is presented for various parameters. More important, that this fact becomes visible by using of ensemble approach rather than single trajectory representation. These findings are applicable generally in nonlinear dynamical systems such as standard epidemic models regardless of parameter values.