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Analysis of the Distribution Pattern of Tuberculosis (Pulmonary TB) Patients Using an Autocorrelation Approach Lastria Kausesra; Endah Purwaningsih
Jurnal Kesehatan Cendikia Jenius Vol. 3 No. 1 (2025): Desember
Publisher : CV. CENDIKIA JENIUS INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70920/jenius.v3i1.314

Abstract

Pulmonary Tuberculosis (TB) remains a global health problem with high morbidity and mortality rates. In Padang Panjang City, TB cases increased significantly from 20 cases in 2020 to 126 cases in 2024. This study aims to analyze the spatial distribution patterns of pulmonary TB patients using a spatial autocorrelation approach and to map the vulnerability levels of urban villages based on environmental risk factors. This quantitative descriptive study was conducted in Padang Panjang City from May to July 2025, involving all pulmonary TB patients recorded in the medical records of Padang Panjang General Hospital in 2024. Data were analyzed using Global Moran’s I and Local Indicators of Spatial Association (LISA) with ArcGIS and GeoDa software, as well as overlay analysis of rainfall, population density, altitude, building density, ventilation, and building orientation. The results showed that the overall spatial distribution of TB was random, but the LISA analysis identified spatial outliers in Pasar Baru and Pasar Usang urban villages. Most areas (14 out of 16 villages) were categorized as high-risk zones, mainly influenced by building density and poor ventilation. In conclusion, the spread of pulmonary TB is strongly influenced by environmental factors. Local governments are advised to prioritize interventions in high-risk areas through ventilation improvement, building density control, and community education on air circulation and natural lighting.