Spatial Analysis of Tuberculosis Cases Using QGIS for Early Detection of Transmission Risk in Bantul Regency

Abstract

Introduction: Tuberculosis (TB) remains a public health issue. The high number of cases highlights the need for early detection through spatial analysis.

Objective: This study aimed to analyze TB case distribution using QGIS as a basis for early detection of transmission risk in Bantul Regency.

Methods: This quantitative descriptive study used TB case data for 2022–2024 obtained from the Bantul District Health Office through the Tuberculosis Information System (SITB), comprising 4,052 cases. Preprocessing included data cleaning, data selection, data normalization, and data transformation before spatial analysis using QGIS. Spatial data were obtained from the Special Region of Yogyakarta Geoportal, which provides shapefiles of sub-district areas. Processed data were presented on a dashboard as tables, charts, and case distribution maps.

Results: A total of 4,052 TB cases were recorded from 2022 to 2024. Sewon had the highest number of cases, with 547 cases, followed by Bantul with 371 cases and Banguntapan with 363 cases. Cases were concentrated in the central to northern regions, with consecutive increases in Sewon, Banguntapan, and Bambanglipuro. The mapping results were developed into a web-based dashboard.

Conclusion: Spatial analysis using QGIS can illustrate TB case distribution patterns and help identify areas at risk of increased transmission.

Keywords: QGIS, spatial analysis, tuberculosis