Identification of spatial clusters and spatial outliers of HIV/AIDS using local Moran's I statistic

Background: Human immunodeficiency virus (HIV) remains a major global public health issue, having claimed 40.4 million lives so far with ongoing transmission in all countries globally; with some countries reporting increasing trends in new infections when previously on the decline. This study aims to use the local Moran’s I statistic to investigate the spatial clusters and spatial outliers of HIV/AIDS cases 63 provinces/cities in Vietnam in 2017.

Methods: The local Moran’s I statistic is first employed to measure spatial auto-correlation between the number of HIV/AIDS cases in each province/city, and then identify the spatial clusters and spatial outliers of HIV/AIDS cases. Spatial distribution of HIV/AIDS clusters and outliers will be mapped with the help of a GIS. Finally, the main findings will be discussed and summarised.

Results: High numbers of HIV/AIDS cases were mainly concentrated in the provinces of the north central region, Da Nang and provinces in the south of Vietnam. Low numbers of HIV/AIDS cases were detected in the northeastern provinces, central and southeastern provinces of Vietnam. Specifically, one high-high cluster and six low-low spatial clusters, and four low-high and high-low spatial outliers of HIV/AIDS cases were successfully detected. Whereas, the only high-high spatial cluster was discovered in Binh Duong province with 3598 HIV/AIDS cases.

Conclusions: Local Moran’s I statistic can help to effectively identify spatial clusters and spatial outlier of HIV/AIDS. Findings in this study provide an insight into how to use spatial statistics to study the spread of HIV/AIDS.