GEOSPATIAL ANALYSIS TO IDENTIFY TUBERCULOSIS HOTSPOTS IN BANYUMAS REGENCY (2023) THROUGH SPATIAL AUTOCORRELATION: Analisis Geospasial untuk Mengidentifikasi Titik Rawan Tuberkulosis di Kabupaten Banyumas (2023) Melalui Autokorelasi Spasial - Daniswara, Sabrina; Muh, Fauzi; Adi, Mateus Sakundarno; Martini, Martini; Sutiningsih, Dwi; Rahayu, Misti (Jurnal Berkala Epidemiologi, 2025)
Background: Banyumas Regency had the second-highest number of TBC cases in Central Java Province in 2023, totaling 7,060 cases. The incidence of TBC increased by approximately 27.27% from 2022 to 2023. Despite various TB control efforts, conventional epidemiological methods often fail to capture the spatial patterns of disease transmission, making it challenging to identify localized hotspots and effectively allocate resources. Purpose: This study aimed to analyze the spatial relationship between HIV prevalence, population density, healthy living behaviors, and housing conditions in relation to TBC incidence. Additionally, it sought to identify tuberculosis hotspots in Banyumas Regency. Methods: The data were obtained from the Banyumas Tuberculosis System Information in August 2024. Total of 4,853 registered patients who sought treatment and resided in Banyumas Regency in 2023 was assessed. TBC distribution patterns were analyzed using the spatial autocorrelation method through the Moran Index and Local Indicators of Spatial Associations (LISA). Results: The analysis revealed significant clustering of TBC incidence with HIV prevalence, clean and healthy living behavior, and population density. The significant dispersion was noted with healthy houses. Notably, six 27 subdistricts—Kembaran, North Purwokerto, South Purwokerto, East Purwokerto, Sokaraja, and Sumbang—demonstrated significant local spatial autocorrelation. Conclusion: The study found TBC incidence was clustered in areas with high HIV prevalence, poor living conditions, and high population density, while healthy houses showed a dispersed pattern, highlighting the importance of prioritizing interventions, policy changes, and resource allocation.