(untitled) (Journal of Mathematical Modeling and Fractional Calculus, 2024)
Tuberculosis (TB) remains a significant public health challenge worldwide, exacerbated by the complex and persistent nature of Mycobacterium tuberculosis infection. Traditional integer order models provide insight into TB transmission and control but may fall short in capturing the nuances of disease progression and memory effects inherent in biological systems. This study presents a fractional-order mathematical model of TB dynamics to better reflect the complexities of TB infec tion, latency, and progression. Utilizing fractional calculus, the model introduces a novel approach that accounts for memory and hereditary properties, offering a more accurate representation of dis ease transmission and latency. Analytical methods are applied to explore the behavior of the disease dynamics. Numerical simulations validate the model’s effectiveness in describing TB dynamics. The fractional-order TB model has the potential to inform more effective intervention strategies and im prove predictions of long-term outcomes.