ABSTRACT:

Background: Tuberculosis (TB) is regarded as one of the leading causes of death globally. It remains a significant cause of morbidity and mortality in Vietnam. This study aims to identify hotspots of TB using boxplot and Getis-Ord’s G_i^* statistic-based hotspot analysis.
Data used and Methods: A total of 101,438 TB cases in 2020 collected from 63 provinces/cities in Vietnam was used in study. Boxplot is first used to study distribution of TB cases. Getis-Ord’s G_i^* statistic was then employed to identify hotspots of TB cases. Finally, results and main findings will be discussed and concluded. Results: It was found that a total of 05 hotspots and 04 coldspots of TB cases were detected throughout Vietnam. Five hotspots were detected in 05 provinces in the northeastern region including Ha Nam, Nam Dinh, Hai Phong, Hai Duong, and Hung Yen. Whereas, four coldspots were mainly concentrated in 03 provinces in the northwest region (Cao Bang, Tuyen Quang and Son La), and Dak Lak in the central south region.
Conclusion: It can be concluded that the combination of boxplot and Getis-Ord’s G_i^* statistic can help to effectively detect hotspots of TB cases. Findings in this study provide an insight into how to used spatial statistics and spatial analysis in the study of TB distribution.

KEYWORDS:

Detection, Hotspot analysis, Spatial autocorrelation, Tuberculosis, Local Getis Ord’s statistic, Vietnam

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