(untitled) (Global Journal of Sciences, 2024)
We present a mathematical framework for the infection of Neisseria gonorrhea in this article. Compared to a number of earlier models in the literature, the new model is more comprehensive and covers a wide range of concepts. The local and global stability, sensitivity analysis, of the model are examined. The results are illustrated with algorithmic experiments. A computational analysis of the model is examined. highlighting the impact of different values of parameters on the model’s dynamics and offering potential avenues for further research. In this article, we present a robust mathematical framework for modeling the infection dynamics of Neisseria Gonorrhoea. Unlike earlier models in the literature, our approach is more comprehensive, integrating a wide array of concepts related to the infection process. We conduct an in-depth analysis of both local and global stability, along with a sensitivity analysis of the model parameters. The results are supported by algorithmic experiments that illustrate the model’s behavior under varying conditions. Additionally, we perform a thorough computational analysis, emphasizing how different parameter values influence the model’s dynamics. This work not only enhances our understanding of gonorrhea transmission but also identifies potential avenues for further research in this critical area of public health. Keywords: Neisseria Gonorrhea, Stability analysis, Numerical simulation, Sensitivity analysis