A new oscillatory regime in two-strain epidemic models with partial cross-immunity
Nir Gavish

TL;DR
This paper uncovers a new oscillatory regime in two-strain epidemic models with partial cross-immunity, showing that sustained oscillations can occur under broader conditions than previously thought, even with weak cross-immunity and asymmetry.
Contribution
It reveals a novel oscillatory regime in two-strain epidemic models, challenging previous assumptions about the conditions needed for oscillations.
Findings
Oscillations occur even with weak cross-immunity.
Steady state of coexistence becomes unstable along specific parameter curves.
Numerical simulations confirm the existence of an unexpected oscillatory region.
Abstract
Infectious diseases often involve multiple strains that interact through the immune response generated after an infection. This study investigates the conditions under which a two-strain epidemic model with partial cross-immunity can lead to self-sustained oscillations, and reveals a new oscillatory regime in these models. Contrary to previous findings, which suggested that strong cross-immunity and significant asymmetry between strains are necessary for oscillations, our results demonstrate that sustained oscillations can occur even with weak cross-immunity and weak asymmetry. Using asymptotic methods, we provide a detailed mathematical analysis showing that the steady state of coexistence becomes unstable along specific curves in the parameter space, leading to oscillatory solutions for any value of the basic reproduction number greater than one. Numerical simulations support our…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical and Theoretical Epidemiology and Ecology Models · COVID-19 epidemiological studies · Mathematical Biology Tumor Growth
