Simulation based model for canine distemper virus in prey-predator dynamics

This study investigates the dynamic interactions of a prey-predator ecosystem infected with Canine Distemper Virus (CDV), focusing on predation and disease transmission. A deterministic model, coupled with Monte Carlo simulations (MCS), employed to capture both stochastic variability and environmental fluctuations. The findings indicate that classical prey-predator cycles provide the baseline for population dynamics, but the introduction of CDV and environmental noise fundamentally alters system behavior. Initially, populations exhibit oscillations that gradually stabilize into dynamic equilibria. However, the disease persists within both prey and predator populations, suggesting endemicity rather than extinction. Predation plays a dual role in disease dynamics, while it reduces prey abundance and can limit pathogen spread, it also exposes predators to infection through consumption of infected prey, thereby generating nonlinear feedbacks that affect population stability. Infection affects ecological linkages, diminishes predator viability, and increases volatility in interspecies interaction, as reflected in phase-space trajectories and weak correlations among population classes. These findings emphasize the critical interplay between predation, disease, and stochasticity in shaping long-term ecological outcomes and highlight the importance of integrating these factors into ecological models for accurate prediction of disease persistence and extinction risk.