Spatial analysis of tuberculosis based on geographic information systems in Sleman district, Special Region Yogyakarta

Abstract

The number of tuberculosis cases continues to rise annually, with Sleman Regency recording 2,372 cases in 2024, making it one of the highest in the Special Region of Yogyakarta Province. This study aims to analyze spatial autocorrelation and spatial relationships of tuberculosis cases in Sleman Regency in 2024 using geographic information systems (GIS) and spatial analysis. A quantitative cross-sectional design was applied to 1,406 tuberculosis cases across 86 villages. Bivariate local indicators of spatial association (LISA) analysis were performed using GeoDa software, while geographically weighted regression (GWR) in R Studio examined local environmental influences. Bivariate LISA results showed no significant spatial autocorrelation for population density, air temperature, air humidity, precipitation, and altitude (p-values: 0.173, 0.265, 0.138, 0.312, and 0.401, respectively). GWR revealed negative correlations between these variables and tuberculosis cases. Findings highlight spatial patterns and inform targeted interventions, recommending enhanced tuberculosis awareness and treatment access in low-density, high-incidence areas, along with public education on ventilation and preventive measures during colder seasons, and strengthened prevention in high-risk lowland villages.