Spatio-Temporal Analysis of Tuberculosis Clusters in a Region of Topographic Diversity: A Case Study from West Sulawesi Province, Indonesia
Abstract
Introduction: Several studies on tuberculosis (TB) using spatial and time clustering analyses have been conducted in Indonesia, however none have specifically focused on regions characterized by diverse topography. This study aimed to identify geospatial clusters of TB cases in West Sulawesi Province, Indonesia, an area known for its topographic variability.
Methods: An ecological study design was employed. TB case data, including bacteriologically confirmed and clinically diagnosed cases, were obtained from the Tuberculosis Information System (Sistem Informasi Tuberkulosis, SITB) of the West Sulawesi Provincial Health Office, covering the period from January 1, 2020, to December 31, 2023. Spatial visualization was performed using QGIS version 3.40.0. Cluster detection and spatial pattern analysis were conducted using SaTScan version 10.2.5.
Results: TB cases in West Sulawesi formed clusters. A total of 17 clusters were identified—4 primary (most likely) clusters and 13 secondary clusters. In 2020, the primary cluster was located in Bambang Village, Bambang Subdistrict. In 2021, the primary cluster was in Lambanan Village, Mamasa Subdistrict. In 2022, the primary cluster was in Ulumambi Barat Village, Bambang Subdistrict, and in 2023, the primary cluster was again in Lambanan Village, Mamasa Subdistrict.
Conclusion: This study found that the most likely TB clusters from 2020 to 2023 were consistently located in the eastern part of West Sulawesi Province, specifically in Mamasa Regency, an area characterized by mountainous terrain. This suggests that various environmental, social, and economic factors unique to mountain communities may influence TB transmission dynamics. The findings highlight the need for geographically tailored intervention strategies, including mobile TB services, community-based education, enhanced surveillance systems, the establishment of local TB support networks, and improved healthcare infrastructure adapted to mountainous areas. Future research should consider integrating genotypic, molecular, and geospatial approaches to advance global TB control efforts.
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