利用莫兰指数分析影响登革热疫情的环境因素的空间自相关性：一项来自尼泊尔的研究（2020 - 2023年）

Spatial autocorrelation of environmental factors influencing dengue outbreaks using Moran's I: A study from Nepal (2020-2023).

作者信息

Mahato Roshan Kumar, Htike Kyaw Min, Sornlorm Kittipong, Koro Alex Bagas, Yadav Rajesh Kumar, Kafle Alok, Sharma Vijay

机构信息

Department of Health Management Innovative Technology, Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand.

Department of Public Health, LA GRANDEE International college, Pokhara University, Nepal.

出版信息

PLoS One. 2025 Jun 4;20(6):e0324798. doi: 10.1371/journal.pone.0324798. eCollection 2025.

DOI:10.1371/journal.pone.0324798

PMID:40465649

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12136339/

Abstract

BACKGROUND

Dengue fever, a mosquito-borne viral infection caused by the dengue virus, has become a significant global public health concern, especially in tropical and subtropical regions. Nepal, with its diverse geography and climate, has witnessed a rapid escalation in dengue cases in recent years, with the highest number of cases and fatalities reported in 2022.

OBJECTIVES

This study analyzed the spatial distribution of dengue in Nepal from 2020 to 2023, using Moran's I spatial statistics to explore the relationship between environmental factors (such as vegetation indices, land surface temperature and precipitation) and dengue incidence.

METHODS

By utilizing Geographic Information System (GIS) and spatial analysis techniques, the study seeks to identify high-incidence clusters and examine environmental factors contributing to the spread of dengue.

RESULTS

This study examined dengue incidence in Nepal from 2020 to 2023, uncovering significant variations in disease patterns and their environmental correlations. Dengue cases peaked in 2022 (Moran's I; 0.634, P-value; 0.001) before declining in 2023 (Moran's I; 0.144, P-value; 0.036), likely due to targeted public health interventions. Spatial analysis revealed no significant patterns in 2020 (Moran's I; -0.004, P-value; 0.288) and 2021 (Moran's I; 0.006, P-value; 0.186), however, a focused spatial distribution emerged in 2022 and 2023. Environmental factors showed evolving relationships with dengue transmission: NDVI and LST showed negative correlations in 2020-2021, while NDWI and precipitation shifted from negative to positive correlations over the study period.

CONCLUSION

The findings showed significant spatial clustering of dengue cases in urban areas with correlations between higher precipitation and increased dengue incidence. These results highlighted the importance of adaptive public health strategies that account for environmental factors.

摘要

背景

登革热是一种由登革病毒引起的蚊媒病毒感染，已成为全球重大的公共卫生问题，尤其是在热带和亚热带地区。尼泊尔地理和气候多样，近年来登革热病例迅速增加，2022年报告的病例和死亡人数最多。

目的

本研究分析了2020年至2023年尼泊尔登革热的空间分布，使用莫兰指数（Moran's I）空间统计方法探讨环境因素（如植被指数、地表温度和降水量）与登革热发病率之间的关系。

方法

通过利用地理信息系统（GIS）和空间分析技术，该研究旨在识别高发病集群，并研究导致登革热传播的环境因素。

结果

本研究调查了2020年至2023年尼泊尔的登革热发病率，发现疾病模式及其与环境的相关性存在显著差异。登革热病例在2022年达到峰值（莫兰指数；0.634，P值；0.001），然后在2023年下降（莫兰指数；0.144，P值；0.036），这可能是由于有针对性的公共卫生干预措施。空间分析显示，2020年（莫兰指数；-0.004，P值；0.288）和2021年（莫兰指数；0.006，P值；0.186）没有显著模式，然而，2022年和2023年出现了集中的空间分布。环境因素与登革热传播的关系不断演变：2020 - 2021年，归一化植被指数（NDVI）和地表温度（LST）呈负相关，而在研究期间，归一化水指数（NDWI）和降水量从负相关转变为正相关。