A Mathematical Modeling Study of Tuberculosis Transmission in the Tea Garden Communities of Sylhet, Bangladesh

Tuberculosis (TB) remains a critical public health challenge in Bangladesh, with the Sylhet division experiencing an alarming increase in pediatric cases from 3.98% in 2021 to 8.66% in 2024. Tea garden communities in Moulvibazar are particularly affected, with 35% of patients being workers and child cases reaching 8% significantly higher than national averages. We developed a deterministic compartmental mathematical model incorporating malnutrition status, overcrowding-driven transmission, and delayed diagnosis to investigate TB dynamics in Sylhet's tea garden communities. The model stratifies the population into susceptible, low-risk latent, high-risk latent (malnourished), infectious, and recovered compartments. The basic reproduction number ​ was calculated using the next-generation matrix approach, and sensitivity analysis identified key parameters driving transmission. Model calibration to Sylhet-specific data yielded (95% CI: 1.98–2.70) in tea garden communities, substantially higher than regional estimates. Malnourished individuals exhibited 3.2-fold higher progression risk to active TB. Sensitivity analysis identified transmission rate fast progression rate , and malnutrition prevalence as the most influential parameters. The model successfully reproduced the observed pediatric case surge when simulating pandemic-related disruptions to nutrition programs and healthcare access. The dramatic increase in childhood TB in Sylhet's tea gardens is quantitatively explainable by the synergistic effects of overcrowding (increasing transmission), malnutrition (accelerating progression), and delayed diagnosis (prolonging infectiousness). Targeted interventions combining nutritional support, active case finding, and improved ventilation could reduce incidence by 32–42% over five years.