ArticlePopulation health metrics2026
Spatiotemporal epidemiology and associated risk factors of tuberculosis incidence and mortality in Indonesia 2017-2022: a nationwide space-time hierarchical analysis.
Article in Population health metrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Strengthening geospatial surveillance for malaria control and elimination in Indonesia: a meeting report.Malaria journal · 2026Article
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6 authors.
Funding
Abstract
backgroundIndonesia is the second-highest contributor to global tuberculosis (TB) cases, accounting for 10% of the total. While previous studies have explored TB patterns in specific regions, a comprehensive nationwide analysis at a fine spatial scale is lacking. This study investigated spatiotemporal patterns of TB incidence and mortality, identified geographical hotspots, and examined their association with risk factors to inform public health policy.
methodsThis retrospective study analyzed notified TB cases and deaths during treatment from Indonesia's National Tuberculosis Surveillance System across 514 districts between 2017 and 2022. Spatiotemporal Bayesian hierarchical modeling was employed to identify high-risk areas and assess associations with potential risk factors. The best-fitting model was determined by evaluating various spatial and temporal random effect structures and likelihood assumptions.
resultsTB incidence fluctuated with a trough during the COVID-19 pandemic and an overall increase, while mortality increased over time. Incidence hotspots clustered in urbanized areas, while mortality hotspots were scattered across the country. The best-fitting model to estimate risk factors for both outcomes was Poisson likelihood. This indicated that TB incidence was spatiotemporally positively linked to better healthcare access (RR: 1.016; 95% CI: 1.007-1.025) and higher municipal human development index (MHDI, RR: 1.062; 95% CI: 1.049-1.075). Mortality was associated with low treatment coverage (RR: 0.610; 95% CI: 0.552-0.674) and success rates (RR: 0.595; 95% CI: 0.491-0.721).
conclusionsFluctuating TB incidence, hotspots concentrated in urbanized areas with better healthcare access and higher MHDI as well as increasing mortality linked to poor treatment outcomes underscore the need for targeted public health interventions to expand access to care, improve treatment adherence, and address the socioeconomic disparities driving TB mortality.
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