Faculty of Public Health, University of Muhammadiyah Aceh, Banda Aceh, Aceh.
Provincial Health Office, North Sumatera.
Geospat Health. 2024 Sep 3;19(2). doi: 10.4081/gh.2024.1318.
The purpose of this study was to determine whether there were any TB clusters in Aceh Province, Indonesia and their temporal distribution during the period of 2019-2021. A spatial geo-reference was conducted to 290 sub-districts coordinates by geocoding each sub-district's offices. By using SaTScan TM v9.4.4, a retrospective space-time scan statistics analysis based on population data and annual TB incidence was carried out. To determine the regions at high risk of TB, data from 1 January 2019 to 31 December 2021 were evaluated using the Poisson model. The likelihood ratio (LLR) value was utilized to locate the TB clusters based on a total of 999 permutations were performed. A Moran's I analysis (using GeoDa) was chosen for a study of both local and global spatial autocorrelation. The threshold for significance was fixed at 0.05. At the sub-district level, the spatial distribution of TB in Aceh Province from 2019-2021 showed 19 clusters (three most likely and 16 secondary ones), and there was a spatial autocorrelation of TB. The findings can be used to provide thorough knowledge on the spatial pattern of TB occurrence, which is important for designing effective TB interventions.
本研究旨在确定印度尼西亚亚齐省是否存在结核病聚集区及其在 2019-2021 年期间的时间分布。通过地理编码每个分区办事处,对 290 个分区的坐标进行了空间地理参考。使用 SaTScan TM v9.4.4,对基于人口数据和年度结核病发病率的回顾性时空扫描统计分析进行了分析。为了确定结核病高风险地区,使用泊松模型评估了 2019 年 1 月 1 日至 2021 年 12 月 31 日的数据。利用总共进行了 999 次置换的似然比 (LLR) 值来定位结核病聚集区。选择 Moran's I 分析(使用 GeoDa)来研究局部和全局空间自相关。显著性阈值固定为 0.05。在分区级别,2019-2021 年亚齐省结核病的空间分布显示了 19 个聚集区(三个最可能的聚集区和 16 个次要聚集区),并且存在结核病的空间自相关。研究结果可用于提供结核病发生的空间模式的全面知识,这对于设计有效的结核病干预措施非常重要。