<p>Data-driven mathematical models are recognized as a significant tool for understanding infectious disease dynamics and have been valuable in public health research for an extended period of time. In this paper, we develop an SEIRV model that includes susceptible, exposed, infectious, and vaccinated populations to investigate the dynamics of the SARS-CoV-2 virus. We incorporate a Holling type-II functional response in our model, which has been widely useful in studying ecological systems. This approach enables us to conduct comprehensive analysis by integrating analytical, computational, and statistical tools, providing a deeper understanding of the spread of SARS-CoV-2. We derive a closed-form mathematical expression to compute the basic reproduction number, calculate predictive intervals for it, and analyze the sensitivity of some parameters to understand the spread of the disease.</p>