Dynamic system of tuberculosis elimination modelling in Indonesia: A study in Kuningan, West Java, Indonesia

Tuberculosis (TB) remains a major public health burden in Indonesia, which currently ranks second worldwide in TB incidence. This study aimed to develop and validate a dynamic systems model to simulate TB elimination strategies at the district level in Kuningan, West Java. We conducted a cross-sectional study involving 30 TB patients, complemented with retrospective data from Ciniru Health Center, the national TB surveillance system (SITB), and Minimal Standard of Services (2019–2023). Patient-level data were collected using structured questionnaires on adherence, beliefs, and knowledge, as well as household environmental assessments. A system dynamics model was constructed using Powersim Studio 10 Academic to simulate the transmission and control of TB. Model validation against historical data showed strong predictive accuracy (absolute mean error <5%). Simulation of two scenarios—Moderate and extreme—revealed substantial differences in outcomes by 2040. Under the Moderate scenario, improvements in lifestyle, nutrition, and adherence reduced the number of TB cases from 82 to 55, and suspects treated decreased from 702 to 614. Under the extreme scenario, further reductions were observed, with TB cases declining to 10 and suspects treated to 612. Key determinants influencing TB burden included nutrition, lifestyle, household environment, and management of drug side effects. This dynamic modeling framework provides valuable insights for localized TB control strategies. It emphasizes that elimination efforts should go beyond biomedical interventions by addressing behavioral, environmental, and psychosocial determinants. The model offers a practical tool to guide district-level planning and supports the national TB elimination agenda. • A dynamic model simulates TB elimination in Kuningan city, Indonesia • This study elaborated the clinical, behavioral, and environmental data from TB patients • Increased drug side effects were found to reduce medication adherence and increase TB incidence. • The dynamic model shows TB prevalence could be halted by 2040 through optimized interventions • The model offers valuable insights for local TB control strategies, emphasizing the role of behavioral and environmental improvements