Mathematical modeling and optimization of monocyte-driven immune dynamics and treatment strategies in within-host Mycobacterium tuberculosis

Tuberculosis (TB) remains a major global health challenge, driven by complex within-host interactions between Mycobacterium tuberculosis (Mtb) and the host immune system. To better understand these dynamics, we develop a mathematical model that incorporates monocytes, macrophages, and T lymphocytes. Analytical results show that the basic reproduction number, [Formula: see text], depends on key infection and immune-response parameters and can exceed unity under biologically plausible conditions, leading to persistent infection. Bifurcation analysis reveals the occurrence of a backward bifurcation at [Formula: see text], indicating that reducing [Formula: see text] below unity may not be sufficient for disease eradication, as stable endemic equilibria can coexist with the disease-free equilibrium when [Formula: see text]. Numerical simulations under baseline parameter values demonstrate that enhancing immune response parameters substantially lowers bacterial burden, reducing bacterial populations by up to [Formula: see text] within 60 days, whereas increased infection rates accelerate disease progression, doubling bacterial populations in approximately half the time. Furthermore, an optimal control analysis suggests that, under representative treatment scenarios, intensified drug treatment can reduce bacterial loads by more than [Formula: see text] within 30 days; however, complete bacterial clearance may remain unattainable because of the backward bifurcation phenomenon. These findings underscore the importance of integrating immune enhancement with optimized treatment strategies and highlight that achieving [Formula: see text] alone may not guarantee eradication of TB infection.