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

Huong-Giang Nguyen, Thi-Tuyet-Mai Nguyen
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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.
2023年前9个月越南胡志明市登革出血热的空间聚类分析
背景:登革出血热是一种显著的媒介传播病毒性疾病,就感染人数而言,目前已成为最可怕的世界卫生问题。本研究的目的是调查2023年前9个月越南胡志明市登革热出血热发病的空间聚类。方法:采用全球Moran’s I统计量、Moran’s I散点图和局部统计量对胡志明市研究区域的空间聚类(高-高和低-低)和空间异常值(低-高和高-低)进行分析。利用一阶和三阶相邻度构造空间权重矩阵。结果:以胡志明市2023年前9个月为例,采用一阶连续度分析,胡志明市北部城区和南部农村共发现4个高-高集聚区和2个低-低集聚区(在0.05水平上具有统计学意义)。对于使用三阶连续度的情况,共识别出6个高-低、2个低-高和1个低-低空间集群。结论:本研究结果证明了全球Moran’s I统计量、Moran’s I散点图和局部Moran’s I统计量在登革热出血热发病空间聚类识别中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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