Assessing geographic and climatic variables to predict the potential distribution of the visceral leishmaniasis vector Lutzomyia longipalpis in the state of Espírito Santo, Brazil.
Assessing geographic and climatic variables to predict the potential distribution of the visceral leishmaniasis vector Lutzomyia longipalpis in the state of Espírito Santo, Brazil.
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DOI：
10.1371/journal.pone.0238198
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发表时间：
2020
期刊：
影响因子：
3.7
通讯作者：
Falqueto A
中科院分区：
文献类型：
--
作者：
Del Carro KB;Leite GR;de Oliveira Filho AG;Dos Santos CB;de Souza Pinto I;Fux B;Falqueto A
内脏利什曼病（Visceral leishmaniasis，VL）是由南美主要媒介长须路蝇（Lutzomyia longipalpis）引起的一种传染病。该病于1968年首次在巴西圣埃斯皮里图州（ES）被诊断出来。目前，这种疾病被认为在10个城市流行。此外，L.迄今为止尚未报告传播情况的其他八个城市也发现了长须症。在这项研究中，我们进行了物种分布模型（SDM），以确定新的和最有可能接受的领域VL传输ES。1986年至2017年期间，在ES的各个农村地区主动和被动收集白蛉。收集点使用全球定位系统装置进行了地理定位。气候数据取自WorldClim数据库，地理数据取自国家空间研究所和圣埃斯皮里图州地理空间基础综合系统。通过MIAmaxent R软件包使用最大熵算法来训练和测试L.长须的模型生成的主要贡献者是岩石露头，其次是温度季节性。SDM预测了L.该区域是Doce河谷的longipalpis易发区，限制了向流域外扩展的可能性。一旦预测出适合L.如果确定了长须蝽的发生情况，我们可以避免在没有发生病媒昆虫的地方进行犬血清学调查时低效地使用公共资源。
Visceral leishmaniasis (VL) is an infectious disease caused by the protozoa Leishmania chagasi, whose main vector in South America is Lutzomyia longipalpis. The disease was diagnosed in the Brazilian state of Espírito Santo (ES) for the first time in 1968. Currently, this disease has been considered endemic in 10 municipalities. Furthermore, the presence of L. longipalpis has been detected in eight other municipalities where the transmission has not been reported thus far. In this study, we performed species distribution modeling (SDM) to identify new and most likely receptive areas for VL transmission in ES. The sandflies were both actively and passively collected in various rural area of ES between 1986 and 2017. The collection points were georeferenced using a global positioning system device. Climatic data were retrieved from the WorldClim database, whereas geographic data were obtained from the National Institute for Space Research and the Integrated System of Geospatial Bases of the State of Espírito Santo. The maximum entropy algorithm was used through the MIAmaxent R package to train and test the distribution models for L. longipalpis. The major contributor to model generation was rocky outcrops, followed by temperature seasonality. The SDM predicted the expansion of the L. longipalpis-prone area in the Doce River Valley and limited the probability of expanding outside its watershed. Once the areas predicted suitable for L. longipalpis occurrence are determined, we can avoid the inefficient use of public resources in conducting canine serological surveys where the vector insect does not occur.
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影响因子：
3.8
作者：
Falcão de Oliveira E;Galati EAB;Oliveira AG;Rangel EF;Carvalho BM
通讯作者：
Carvalho BM
影响因子：
2.1
作者：
Arrivillaga, J;Mutebi, JP;Lanzaro, GC
通讯作者：
Lanzaro, GC
DOI：
10.1590/s0074-02762007000100001
发表时间：
2007-02-01
期刊：
Memórias do Instituto Oswaldo Cruz
影响因子：
--
作者：
Bauzer, Luiz GSR;Souza, Nataly A;Peixoto, Alexandre A
通讯作者：
Peixoto, Alexandre A
影响因子：
3.2
作者：
Chamaille, Lise;Tran, Annelise;Dedet, Jean-Pierre
通讯作者：
Dedet, Jean-Pierre
DOI：
10.1002/joc.5086
发表时间：
2017-10-01
期刊：
INTERNATIONAL JOURNAL OF CLIMATOLOGY
影响因子：
--
作者：
Fick, Stephen E.;Hijmans, Robert J.
通讯作者：
Hijmans, Robert J.