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与中、西非罗阿罗阿丝虫传播媒介 Chrysops 属昆虫分布有关的环境因素:见树又见林。

Environmental factors associated with the distribution of Loa loa vectors Chrysops spp. in Central and West Africa: seeing the forest for the trees.

机构信息

Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, UK.

出版信息

Parasit Vectors. 2019 Feb 6;12(1):72. doi: 10.1186/s13071-019-3327-9.

DOI:10.1186/s13071-019-3327-9
PMID:30728063
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6366063/
Abstract

BACKGROUND

Loiasis is caused by the filarial parasite Loa loa, which is widespread through Central and West Africa and largely confined the tropical equatorial rainforests. The tabanid flies Chrysops silacea and Chrysops dimidiata are the main vectors driving transmission. This study aimed to better define the spatial distribution and ecological niche of the two vectors to help define spatial-temporal risk and target appropriate, timely intervention strategies for filariasis control and elimination programmes.

METHODS

Chrysops spp. distributions were determined by collating information from the published literature into a database, detailing the year, country, locality, latitude/longitude and species collected. Environmental factors including climate, elevation and tree canopy characteristics were summarised for each vector from data obtained from satellite modelled data or imagery, which were also used to identify areas with overt landcover changes. The presence of each Chrysops vector was predicted using a maximum entropy species distribution modelling (MaxEnt) method.

RESULTS

A total of 313 location-specific data points from 59 published articles were identified across seven loiasis endemic countries. Of these, 186 sites were included in the climate and elevation analysis, and due to overt landcover changes, 83 sites included in tree canopy analysis and MaxEnt model. Overall, C. silacea and C. dimidiata were found to have similar ranges; annual mean temperature (24.6 °C and 24.1 °C, respectively), annual precipitation (1848.6 mm and 1868.8 mm), elevation (368.8 m and 400.6 m), tree canopy cover (61.4% and 66.9%) and tree canopy height (22.4 m and 25.1 m). MaxEnt models found tree canopy coverage was a significant environmental variable for both vectors.

CONCLUSIONS

The Chrysops spp. database and large-scale environmental analysis provides insights into the spatial and ecological parameters of the L. loa vectors driving transmission. These may be used to further delineate loiasis risk, which will be important for implementing filariasis control and elimination programmes in the equatorial rainforest region of Central and West Africa.

摘要

背景

罗阿丝虫病由罗阿丝虫引起,该寄生虫广泛存在于中非和西非,主要局限于热带赤道雨林。舌蝇属的 Chrysops silacea 和 Chrysops dimidiata 是主要的传播媒介。本研究旨在更好地确定这两种媒介的空间分布和生态位,以帮助确定时空风险,并为控制和消除丝虫病规划提供及时的干预策略。

方法

通过将文献中的信息整理到一个数据库中,确定 Chrysops spp. 的分布情况,详细记录年份、国家、地点、纬度/经度和采集的物种。从卫星模型数据或图像中获取的环境因素,包括气候、海拔和树冠特征,用于总结每种舌蝇的信息。使用最大熵物种分布模型(MaxEnt)方法预测每种 Chrysops 媒介的存在。

结果

共从 7 个罗阿丝虫病流行国家的 59 篇已发表的文章中确定了 313 个特定地点的数据点。其中,186 个地点被纳入气候和海拔分析,由于明显的土地覆盖变化,83 个地点被纳入树冠分析和 MaxEnt 模型。总体而言,C. silacea 和 C. dimidiata 的分布范围相似;年平均温度(分别为 24.6°C 和 24.1°C)、年降水量(分别为 1848.6 毫米和 1868.8 毫米)、海拔(分别为 368.8 米和 400.6 米)、树冠覆盖率(分别为 61.4%和 66.9%)和树冠高度(分别为 22.4 米和 25.1 米)。MaxEnt 模型发现树冠覆盖率是这两种媒介的一个重要环境变量。

结论

Chrysops spp. 数据库和大规模环境分析为驱动传播的 L. loa 媒介的空间和生态参数提供了深入了解。这些可能用于进一步划定罗阿丝虫病风险,这对于在中非和西非的赤道雨林地区实施控制和消除丝虫病规划非常重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/3cfa39a385b2/13071_2019_3327_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/7ee931d300ad/13071_2019_3327_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/65103314216b/13071_2019_3327_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/d7dfaa5aea3d/13071_2019_3327_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/588faff95afd/13071_2019_3327_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/3cfa39a385b2/13071_2019_3327_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/7ee931d300ad/13071_2019_3327_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/65103314216b/13071_2019_3327_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/d7dfaa5aea3d/13071_2019_3327_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/588faff95afd/13071_2019_3327_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a05/6366063/3cfa39a385b2/13071_2019_3327_Fig5_HTML.jpg

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