Spatial Clustering Analysis Of Dengue Hemorrhagic Fever In The First 9-Monthsof 2023 In Ho Chi Minh City, Vietnam

Abstract

Background: Dengue hemorrhagic fever is a notable vector-borne viral disease, currently becoming the most dreaded worldwide health problem in terms of the number of people affected. The objective of this study is to investigate spatial clustering of dengue hemorrhagic fever incidence in the first 9-months of 2023 in Ho Chi Minh city, Vietnam. Methods: the global Moran’s I statistic, Moran’s I scatterplot and local statistic were employed to spatial clusters (high-high and low-low) and spatial outliers (low-high and high-low) in the study area of Ho Chi Minh city. The first and third order of contiguity were used to constructe spatial weight matrix. Results: it was found from a case study of the first 9-months of 2023 in Ho Chi Minh city, a total of four high-high clusters, two low-low spatial clusters were detected in urban area and rural areas in the north and south of the Ho Chi Minh city, respectively when using the first order contiguity (statistically significance at the 0.05 level). For the case of using the third order of contiguity, a total of six high-low, two low-high spatial clusters and one low-low spatial cluster were successfully identified. Conclusions: the study results has proven the effective use of the global Moran’s I statistic, Moran’s I scatterplot and local Moran’s I statistic in the identification of spatial clustering of dengue hemorrhagic fever incidence.