Abstract : Dengue is one of the most common tropical diseases affecting humans. The incidence of dengue and dengue hemorrhagic fever (DF/DHF) has increased significantly over the last decades. The aim of this study is to detect the spatio-temporal clustering of dengue hemorrhagic fever in the period of from June to July 2023, in Ho Chi Minh city, Vietnam, based on Local Indicators of Spatial Autocorrelation (LISA). Descriptive statistics were first used to study the data distribution. The global Moran’s I statistic, Moran’s I scatterplot and LISA were then employed to investigate the spatio-temporal clustering of dengue hemorrhagic fever in these four months. More specifically, spatial clusters (high-high and low-low) and spatial outliers (low-high and high-low) of dengue hemorrhagic fever in Ho Chi Minh city were detected based on the local Moran’s I statistic. It was found that DHF infection rates tends to increase steadily during the period of from June to July in 2023 in Ho Chi Minh city. Although spatial clustering of DHF infection rates, has changed quickly, high-high spatial clustering of DFH infection rates were mainly detected in urban districts and in the city center. Findings in this study revealed that an evidence of statistically significant spatial clusters of DHF was found in Ho Chi Minh City. The results of this study also demonstrate the confirmation of LISA in the study of spatial clustering of infectious diseases in general and DHF in particular. Findings in this study provide an insight into the understanding of the spread of DHF.