Novel iterative method for the approximation of fixed point of a class of generalized ($$\alpha ,\beta$$)-nonexpansive mapping with applications to seir epidemic model

In this paper, we construct a novel iterative scheme for approximating fixed points of generalized [Formula: see text]-nonexpansive mappings in the setting of a real Banach space. The proposed scheme not only generalizes but also unifies and extends several well-known fixed point iterative processes available in the literature. We establish both weak and strong convergence results under appropriate conditions. Furthermore, a comparative analysis of the rate of convergence is carried out using a carefully chosen numerical example, with the outcomes demonstrated through both tabular and graphical illustrations.In addition to convergence properties, we derive a data dependence result, offering insights into the stability of the proposed scheme with respect to perturbations in the underlying mapping. We further prove that the scheme satisfies [Formula: see text]-stability and almost [Formula: see text]-stability criteria, thereby enhancing its robustness in practical applications. To demonstrate the applicability of our results, we provide significant application of the analysis to a SEIR epidemic model governed by a Caputo-type fractional differential equation, showcasing the utility of the proposed method in the context of real-world dynamical systems. Our findings contribute to the advancement of fixed point theory and its applications in mathematical modeling, offering a flexible and powerful tool for analyzing complex nonlinear problems.