School of Medical Laboratory Sciences, Institute of Health, Jimma University, Jimma, Oromia, Ethiopia.
Federal Ministry of Health, Addis Ababa, Ethiopia.
BMC Public Health. 2024 Oct 21;24(1):2913. doi: 10.1186/s12889-024-20343-w.
Smear-positive TB patients greatly contribute to community-level transmission of this disease. Locating hotspots would make it easier to prioritize and target control interventions. This study aimed to assess the spatial distribution of smear-positive index TB cases and their secondary cases and the predictors of clustering of smear-positive TB cases.
This study was conducted in the Silti Zone of Central Ethiopia from 2020 to 2022. The data of smear-positive index TB patients were collected from the unit TB registries of healthcare facilities. Contacts of all index TB patients were screened in the community and tested to identify secondary TB patients. We performed spatial analysis, including Moran's I statistic, the Getis-Ord Gi* statistic and geographically weighted regression (GWR), to assess the global distribution, local clustering and predictors of clustering of smear-positive TB patients, respectively. Additionally, we used inverse distance weighting (IDW) interpolation to predict the distribution of smear-positive TB cases and develop a continuous raster map for places with no data.
Spatial autocorrelation analysis revealed that the distribution of smear-positive TB patients exhibited significant clustering (Moran's I = 0.70029; p value < 0.000). The Getis-Ord Gi* output indicated the presence of statistically significant hotspots as well as cold spots in the study area. Significant hotspots were found in 11 Kebeles of the Silti, Dalocha and Misrak Silti districts. Significant coldspots were also found in five kebeles of the Silti and Misrak districts. GWR analysis revealed that no education, primary education, family size and thatched roof houses were significant predictors of the spatial clustering of smear-positive TB cases. We also found that the majority of the secondary TB cases were found in hotspots identified through spatial analysis.
The study revealed a heterogenous distribution of smear positive TB in the study area and it could act as a model that can be replicated in other regions. The identified hotspots of TB could be targeted through location-based interventions such as systematic active screening in the form of outreach programs to improve the performance of TB prevention and control, including reducing the transmission of TB. Educational status, family size and housing type were some of the factors that significantly influenced the spatial distribution of smear-positive TB in the study area. The distribution of secondary TB cases found through household contact screening coincided with the identified hotspots, indicating greater transmission of the disease in these places.
涂阳结核病患者极大地促成了该疾病在社区层面的传播。确定热点地区将更容易确定和优先考虑控制干预措施的重点。本研究旨在评估涂阳指数结核病病例及其继发病例的空间分布，以及涂阳结核病病例聚集的预测因素。
本研究于 2020 年至 2022 年在埃塞俄比亚中部的西尔提地区进行。涂阳指数结核病患者的数据从医疗机构的单位结核病登记处收集。对所有指数结核病患者的接触者在社区进行筛查，并进行检测以确定继发结核病患者。我们分别进行了空间分析，包括 Moran's I 统计、Getis-Ord Gi*统计和地理加权回归（GWR），以评估涂阳结核病患者的全局分布、局部聚集和聚集的预测因素。此外，我们使用反距离加权（IDW）插值来预测涂阳结核病病例的分布，并为没有数据的地方开发连续的栅格地图。
空间自相关分析显示，涂阳结核病患者的分布表现出显著的聚集性（Moran's I=0.70029；p 值<0.000）。Getis-Ord Gi*结果表明，研究区域存在具有统计学意义的热点和冷点。西尔提、达洛查和米斯拉提区的 11 个 Kebeles 发现了显著的热点。西尔提和米斯拉提区的 5 个 Kebeles 也发现了显著的冷点。GWR 分析表明，未受教育、小学教育、家庭规模和茅草屋顶房屋是涂阳结核病病例空间聚集的显著预测因素。我们还发现，大多数继发结核病病例都出现在通过空间分析确定的热点中。
本研究揭示了研究区域涂阳结核病的异质分布，可为其他地区提供可复制的模式。确定的结核病热点可以通过基于位置的干预措施进行靶向治疗，例如以外展计划形式进行系统主动筛查，以提高结核病预防和控制的效果，包括减少结核病的传播。教育程度、家庭规模和住房类型是影响研究区域涂阳结核病空间分布的一些因素。通过家庭接触筛查发现的继发结核病病例的分布与确定的热点相吻合，表明这些地方的疾病传播更为严重。
