Abstract

Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) is a devastating and rapidly spreading disease. Despite years of scientific research and numerous efforts, it is still a major and resurgent health problem worldwide, with high mortality rates. Added to the concern is that TB persists as a latent infection, an occult face of TB, that becomes a potential reservoir for active tuberculosis. Since latent TB‐infected patients may eventually advance to the active form of TB, an accurate diagnosis and effective treatment of latent tuberculosis are essential for TB control. Latent tuberculosis infection (LTBI) treatment is a prominent component of TB control in low‐prevalence countries like the United States; however, its implication in high‐incidence countries like India is still challenging. Therefore, the present study aimed to evaluate the impact of implementing diagnosis and treatment of LTBI in high‐incidence countries using a mathematical model‐based approach. Through our model, we predicted the incidence rate based on the current treatment regimen in India for the year 2035, which is one of the milestones of WHO for a substantial reduction in TB incidence. We observed demographic variability in the effects of various parameters on the TB incidence rate. Finally, we formulated the putative treatment strategies to reduce the TB burden in high‐incidence scenarios. Further, we estimated the impact of these proposed treatment strategies on the drug‐resistant population in high‐incidence scenarios. The model predictions suggested molding the current treatment strategies and focused implementation of LTBI diagnosis and treatment in high‐incidence scenarios.

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