Abstract
Tuberculosis (TB) transmission frequently occurs in a household or group within a population, resulting in a variety of spatial patterns. However, the apparent spatial clustering of TB may represent the ongoing transmission or co-location of associated risk factors, which can vary significantly based on the type of data available, the analysis methods used, and the dynamics of the underlying population. This study aims to review the spatial analyses used for monitoring the trends involving and associations between risk factors and TB cases by applying the concept of spatial epidemiology. The role of the Geographic Information System in spatial epidemiology is discussed. Previous studies involving spatial analysis of TB cases - which include kriging, spatial autocorrelation, kernel density estimation, hotspot analysis, and regression analysis - are reviewed. The type of analysis was chosen based on the purpose of each study, which could explain the role of the transmission to reactivation of the disease as a driver of TB spatial distribution. In diverse situations, a number of different spatial analysis techniques were used, with all the studies demonstrating significant heterogeneity in terms of the spatial distribution of TB. Future research is needed to determine the best methods to use in different situations and, where possible, consider unreported cases when using notification data. A combination of genotypic, molecular, and geospatial approaches to examine epidemiologically related cases could improve TB control and provide significant contributions to the current knowledge.
Published Version
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