Assessing the hotspot analysis and spatial clustering for pulmonary tuberculosis from 2019 to 2023 in Mysuru district, India

<h2>ABSTRACT</h2><h3>Background</h3> Pulmonary Tuberculosis (PTB) remains a major cause of morbidity in India despite progress in TB elimination, accounting for roughly 25% of global TB cases. Ongoing spatial and demographic disparities hinder further reduction. The study aims to assess PTB syndemic profiles, spatial distribution, and persistent hotspots in a high-burden Indian district from 2019 to 2023 using geospatial analytics to inform precision public health policies. <h3>Methods</h3> A retrospective cross-section analysis of 10,201 PTB cases in Mysuru district used ArcGIS and Google Earth Pro to examine point density by age, gender, HIV status, and diabetes. Spatial autocorrelation (Moran's I, Getis-Ord Gi*) identified hotspot clusters, while chi-square tests evaluated demographics and comorbidity trends. <h3>Results</h3> Between 2019 and 2023, PTB cases declined by 7.7% (from 2,245 to 2,029). Cases among individuals aged 0-18 and 19-44 fell by 22% and 22.3%, respectively. Both male and female cases dropped by about 9.5%, while diabetes cases rose by 10% and non-diabetes cases fell by 6.5%. HIV-positive cases declined by 52.6%. A Moran's Index of 0.381799, z-score of 31.45, and p-value <0.001 indicate strong, statistically significant spatial clustering. <h3>Conclusion</h3> Despite the overall decline in disease burden, persistent urban PTB clusters continue to affect the elderly and individuals with diabetes. While TB-HIV comorbidity has significantly decreased, the enduring Diabetes-TB overlap highlights the need for integrated, geospatially targeted interventions and continuous GIS-based surveillance to address high-risk clusters and advance TB elimination in urban areas.