Routes to extreme events in forced-transmission eco-epidemic model: A dynamical-systems perspective

We employ a seasonally forced eco-epidemiological predator–prey model to investigate how periodic transmission shapes population dynamics and rare outbreaks. Through numerical simulations supported by bifurcation diagrams, Lyapunov-exponent spectra, and fractal-dimension analysis, we identify transitions between periodic, chaotic, and intermittent extreme-event regimes as forcing amplitude and frequency vary. A rigorous extreme-value framework, combining Generalized Pareto Peak Over Threshold (POT) fits of threshold exceedances with Gamma-distributed Inter-Spike-Interval (ISI) analysis, confirms that both amplitude and temporal outliers are accurately captured. Results indicate that high-frequency forcing enhances chaotic irregularity while inhibiting extreme peaks, whereas low-frequency forcing promotes sporadic large-amplitude events. Global elasticity indices under ±20% parameter perturbations reveal that these dynamical regimes persist under ecological uncertainty. These findings highlight the pivotal role of seasonality in disease-driven ecological dynamics and offer quantitative tools for forecasting and mitigating rare outbreaks.