Identification of infectious disease spatial clusters based on local Moran’s I statistic: A case study of dengue hemorrhagic fever

Abstract

Background: One of the most prevalent tropical illnesses that impact people is dengue. Dengue and dengue hemorrhagic fever (DF/DHF) have become much more common within the past few decades. The purpose of this study is to use the local Moran's I statistic to identify any spatial clustering of dengue hemorrhagic fever in Ho Chi Minh City, Vietnam, during the months of June through July of 2023. Methods: The data distribution was first examined using descriptive statistics. The spatial clustering of dengue hemorrhagic fever over these four months was then examined using the global Moran's I statistic, Moran's I scatterplot, and local Moran's I statistic. More precisely, using the local Moran's I statistic, dengue hemorrhagic fever clusters (high-high and low-low) and geographical outliers (low-high and high-low) were found in Ho Chi Minh City. Results: It was discovered that DHF infection rates in Ho Chi Minh City likely to rise gradually between June and July of 2023. High-high spatial clustering of DHF infection rates was primarily found in urban areas and the city centre, despite the fact that this pattern has rapidly changed. Conclusions: The results of this investigation showed that Ho Chi Minh City has statistically significant spatial clusters of DHF. The findings of this investigation further show that local Moran's I statistic is validated in the context of studying the spatial clustering of infectious diseases in general and DHF in particular. The research findings offer valuable insights into the knowledge of the dissemination of DHF.