Pulmonary tuberculosis (PTB) remains a major public health challenge in Indonesia, with substantial geographical disparities in disease burden across regions. Understanding the spatial structure of PTB distribution is essential for designing effective and geographically targeted control strategies. This study aims to examine the spatial epidemiological patterns of PTB in Indonesia from 2000 to 2023 using a Geographic Information System (GIS) based approach. Secondary data on annually reported PTB cases at the provincial level were obtained from official national sources and analyzed using spatial autocorrelation techniques. Global Moran’s Index was applied to assess overall spatial dependence, while Local Indicators of Spatial Association (LISA) were used to identify statistically significant local clusters of PTB cases. Spatial analyses were conducted within a GIS environment to visualize national and regional distribution patterns. The results reveal a persistent, statistically significant, clustered spatial pattern of PTB throughout the study period. Global Moran’s I value consistently indicates positive spatial autocorrelation, confirming that the PTB distribution is not random. LISA analysis identifies stable High-High clusters concentrated in the densely populated provinces of Java and enduring Low-Low clusters predominantly located in Papua and parts of eastern Indonesia. These findings demonstrate pronounced regional contrasts in PTB burden over time. In conclusion, PTB transmission in Indonesia exhibits strong spatial dependence shaped by regional connectivity and structural disparities, and integrating spatial analysis into national tuberculosis control programs can support more targeted, equitable, and effective public health interventions.
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