Persistent and emerging tuberculosis notification burden across 514 districts and cities in Indonesia, 2021–2025: a nationwide spatiotemporal study for public health prioritisation

Background Indonesia carries a substantial tuberculosis (TB) burden, but national notification totals conceal geographic variation and reflect both disease occurrence and the capacity to detect and report cases. This study identified districts with persistent or emerging burden to support surveillance and programme review. Methods Annual notified TB counts from 514 Indonesian districts and cities during 2021–2025 were analysed (2,570 district-year observations) using Bayesian spatiotemporal disease mapping with annual expected counts as an offset. The primary model included Besag–York–Mollié 2 spatial effects, first-order random-walk temporal effects, an unstructured district-year effect, population density, poverty, Puskesmas availability, and general hospital availability. Posterior relative risks (RRs), 95% credible intervals (CrIs), and exceedance probabilities classified burden trajectories. Sensitivity analyses varied the likelihood, neighbourhood graph, study period, and exceedance thresholds. Results National notifications increased from 443,249 in 2021 to 867,480 in 2025, while Moran’s I rose from 0.147 to 0.255 (all p < 0.001). Population density (rate ratio 1.287, 95% CrI 1.212–1.367) and Puskesmas availability (1.188, 1.132–1.247) were positively associated with notification burden. Poverty showed an inverse ecological association (0.835, 0.795–0.877), whereas general hospital availability showed no clear association (0.986, 0.955–1.019). Among 514 districts, 133 had persistent high burden, six had emerging high burden, and 84 were assigned to Tier 1, the study’s highest priority category. Conclusions TB notification burden became more geographically clustered during 2021–2025. Persistent and emerging burden was concentrated in a subset of districts, while the positive association with Puskesmas availability was consistent with notifications reflecting both epidemiological burden and detection capacity. Trajectory mapping may support targeted surveillance and programme review when interpreted alongside local diagnostic and health-service information.