Ilham Saiful Fauzi, Nuning Nuraini, Arrofiatuz Zahra, Vuvut Selviana, Fathimatus Zahro Fazda Oktavia, Bony Wiem Lestari
The resurgence of TB cases following the COVID-19 pandemic has raised concerns about previously masked transmission driven by undetected and untreated infections resulting from disruptions in TB health services. Understanding post-pandemic transmission dynamics and identifying high-risk areas are therefore critical for effective TB control, particularly in high-burden settings. This study employed an ecological time-series design using TB notification data recorded in the national reporting system from January 2020 to October 2024 across all districts. A compartmental mathematical model incorporating vaccination, testing rates, detected and undetected infections, and multidrug-resistant TB was developed to characterize transmission dynamics and assess intervention impacts. Model simulations showed strong agreement with observed data, as indicated by a Pearson correlation of r=0.825. The estimated basic reproduction number was R0=3.999 (95% CI: 3.679 - 4.319), substantially exceeding the epidemic threshold and indicating sustained transmission potential. Sensitivity analysis identified the testing rate as a key determinant of transmission, accounting for a 19.9% reduction in R0, with numerical simulations demonstrating that increased testing significantly reduces undetected cases and TB-related mortality. Spatial analyses revealed a higher transmission risk in eight urban or suburban areas in the central and western regions, alongside persistent coldspot clusters in predominantly rural southeastern areas. Notably, despite higher incidence and infection rates, urban areas exhibited lower R0 values, likely reflecting more effective vaccination impact and better healthcare access. These findings provide empirical evidence supporting strengthened testing strategies, optimized vaccinations in high-density urban settings, and improved healthcare access in rural areas to reduce post-pandemic TB transmission. © 2026 Elsevier B.V.
Department of Accounting, Politeknik Negeri Malang, Malang, Indonesia; Department of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung, Indonesia; Center for Mathematical Modeling and Simulation, Institut Teknologi Bandung, Bandung, Indonesia; Department of Public Health, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia; Department of Internal Medicine, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, Netherlands