It is shown that the relative transmission advantage of secondary infections fundamentally governs the onset of robust limit-cycle oscillations, extending previous narrow-borderline results and revealing a rich macroscopic landscape where small-amplitude local oscillations coexist with large-amplitude, recurrent outbreak cycles.
Abstract
Multi-strain epidemiological systems frequently exhibit self-sustained oscillations, yet severe algebraic complexity has long obstructed a complete analytical characterization of these dynamics. Seeking to bypass these barriers, we have identified a broad, analytically tractable class of two-strain models featuring asymmetric cross-immunity that precludes secondary infections for a single strain. This targeted structural simplification allows us to derive explicit expressions for coexistence equilibria and map their stability. We show that the relative transmission advantage of secondary infections fundamentally governs the onset of robust limit-cycle oscillations, extending previous narrow-borderline results. Crucially, numerical simulations reveal a rich macroscopic landscape where small-amplitude local oscillations coexist with large-amplitude, recurrent outbreak cycles. The structural robustness of these phenomena is confirmed by incorporating effects such as waning immunity and isolation and extending the framework beyond the analytically tractable class. These findings provide a clear mechanistic explanation for multi-strain epidemic cycles and offer a highly tractable baseline for future theoretical developments.
Abstract.
The foundational two-strain susceptible infectious recovered (SIR) model with lifelong partial cross-immunity has been analytically proven to be universally stable under weak, nearly symmetric cross-immunity. However, numerical observations in closely related models exhibit complex, oscillatory behavior...
N. Gavish· SIAM Journal on Life Science...· 1 citation· ⚡1
It is shown that the multiscale model with bidirectional coupling can change epidemic outcomes and produce more realistic predictions for control of chronic infections.
The central finding is that the interplay between vaccination and PIM can undermine control strategies based solely on reducing R0 below unity, highlighting the importance of incorporating post-infection health outcomes and their interaction with vaccination into epidemiological models to design robust and effective di...
Xing-Yu Wang, Jicai Huang, Min Lu et al.· Mathematical Biosciences· 0 citations
We incorporate stochastic fluctuations into an epidemic-behavior coevolution model and study its threshold dynamics and stationary distributions. By introducing the stochastic basic reproduction number R0σ, the behavioral threshold d, and two potential infection proportions RPσ,1 and RPσ,2, we establish conditions for...
Huan Yang, Sanyi Tang, Lin Wang· Journal of Theoretical Biolo...· 0 citations
This study proposes a susceptible-infectious-recovered (SIR) network model that incorporates a general recovery rate and a saturation treatment function, and establishes the well-posedness and global stability of the disease-free equilibrium in the model by employing semigroup theory and the standard comparison princip...
Jun-Yuan Yang, Maia Martcheva, Jun Zhang et al.· SIAM Journal on Applied Math...· 0 citations
A reduced macroscopic framework is introduced that changes the scale of epidemic description from individual-level transmission structure to effective population-level dynamics and supports the use of a macroscopic, scale-reduced representation for cross-calibration of heterogeneous surveillance signals and analytical...
D. Below, F. Mairanowski· medRxiv· 0 citations
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