In this paper, we used the innovative wavelet technique known as the Genocchi wavelet collocation method to acquire the solution of the food chain ecoepidemic model. The outcomes obtained by the implemented scheme are compared with those of the \(2^{nd}\) - order Runge–Kutta and NDSolve methods. Different parameters are used to analyze the model’s nature, and the results are displayed in graphs and tables. The results indicate that the Genocchi wavelet collocation method provides a highly accurate approximation of the food chain ecoepidemic model. This enables researchers to gain a deeper understanding of predator–prey dynamics and disease transmission within ecosystems. Compared to traditional numerical methods, the Genocchi wavelet approach significantly reduces computational complexity. This will help to speed up simulations with less computational power, making it feasible to analyze large-scale ecological systems.
