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寨卡病毒的时空分布及其与环境的空间异质性关系。

Spatiotemporal Distribution of Zika Virus and Its Spatially Heterogeneous Relationship with the Environment.

机构信息

State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.

State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.

出版信息

Int J Environ Res Public Health. 2021 Jan 2;18(1):290. doi: 10.3390/ijerph18010290.

DOI:10.3390/ijerph18010290
PMID:33401753
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7795554/
Abstract

Infectious diseases have caused some of the most feared plagues and greatly harmed human health. However, despite the qualitative understanding that the occurrence and diffusion of infectious disease is related to the environment, the quantitative relations are unknown for many diseases. Zika virus (ZIKV) is a mosquito-borne virus that poses a fatal threat and has spread explosively throughout the world, impacting human health. From a geographical perspective, this study aims to understand the global hotspots of ZIKV as well as the spatially heterogeneous relationship between ZIKV and environmental factors using exploratory special data analysis (ESDA) model. A geographically weighted regression (GWR) model was used to analyze the influence of the dominant environmental factors on the spread of ZIKV at the continental scale. The results indicated that ZIKV transmission had obvious regional and seasonal heterogeneity. Population density, GDP per capita, and landscape fragmentation were the dominant environmental factors affecting the spread of ZIKV, which indicates that social factors had a greater influence than natural factors on the spread of it. As SARS-CoV-2 is spreading globally, this study can provide methodological reference for fighting against the pandemic.

摘要

传染病造成了一些最可怕的瘟疫,极大地危害了人类健康。然而,尽管人们从质的角度理解到传染病的发生和传播与环境有关,但对于许多疾病,其定量关系仍不清楚。寨卡病毒(ZIKV)是一种蚊媒病毒,它构成致命威胁,并在全球范围内迅速传播,影响人类健康。从地理角度来看,本研究旨在使用探索性特殊数据分析(ESDA)模型了解 ZIKV 的全球热点以及 ZIKV 与环境因素之间的空间异质性关系。使用地理加权回归(GWR)模型分析了在大陆尺度上主要环境因素对 ZIKV 传播的影响。结果表明,ZIKV 的传播具有明显的区域和季节性异质性。人口密度、人均 GDP 和景观破碎度是影响 ZIKV 传播的主要环境因素,这表明社会因素对 ZIKV 的传播影响大于自然因素。由于 SARS-CoV-2 在全球范围内传播,本研究可为抗击大流行提供方法学参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/8a2955ae7735/ijerph-18-00290-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/4cdd89cbdc5c/ijerph-18-00290-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/a402a74f9e1c/ijerph-18-00290-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/b01d8e57fa33/ijerph-18-00290-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/defed667daaa/ijerph-18-00290-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/7d56be501424/ijerph-18-00290-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/8102c05669e1/ijerph-18-00290-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/c84f88a8f05b/ijerph-18-00290-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/8a2955ae7735/ijerph-18-00290-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/4cdd89cbdc5c/ijerph-18-00290-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/a402a74f9e1c/ijerph-18-00290-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/b01d8e57fa33/ijerph-18-00290-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/defed667daaa/ijerph-18-00290-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/7d56be501424/ijerph-18-00290-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/8102c05669e1/ijerph-18-00290-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/c84f88a8f05b/ijerph-18-00290-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae6b/7795554/8a2955ae7735/ijerph-18-00290-g008.jpg

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