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基于贝类学和环境数据以及报告的人类病例确定肠道血吸虫病的风险区域

Identification of Risk Areas for Intestinal Schistosomiasis, Based on Malacological and Environmental Data and on Reported Human Cases.

作者信息

Coelho Paulo R S, Ker Fabrício T O, Araújo Amanda D, Guimarães Ricardo J P S, Negrão-Corrêa Deborah A, Caldeira Roberta L, Geiger Stefan M

机构信息

Department for Parasitology, Federal University of Minas Gerais, Belo Horizonte, Brazil.

Oswaldo Cruz Foundation (Fiocruz), Research Group on Helminthology and Medical Malacology, René Rachou Institute, Belo Horizonte, Brazil.

出版信息

Front Med (Lausanne). 2021 Aug 6;8:642348. doi: 10.3389/fmed.2021.642348. eCollection 2021.

Abstract

The aim of the present study was to use an integrated approach for the identification of risk areas for transmission in an area of low endemicity in Minas Gerais, Brazil. For that, areas of distribution of were identified and were related to environmental variables and communities with reported schistosomiasis cases, in order to determine the risk of infection by spatial analyses with predictive models. The research was carried out in the municipality of Alvorada de Minas, with data obtained between the years 2017 and 2019 inclusive. The Google Earth Engine was used to obtain geo-climatic variables (temperature, precipitation, vegetation index and digital elevation model), R software to determine Pearson's correlation and MaxEnt software to obtain an ecological model. ArcGis Software was used to create maps with data spatialization and risk maps, using buffer models (diameters: 500, 1,000 and 1,500 m) and CoKriging. Throughout the municipality, 46 collection points were evaluated. Of these, 14 presented snails of the genus . Molecular analyses identified the presence of different species of , including . None of the snails eliminated cercariae. The distribution of was more abundant in areas of natural vegetation (forest and cerrado) and, for spatial analysis (Buffer), the main risk areas were identified especially in the main urban area and toward the northern and eastern extensions of the municipality. The distribution of snails correlated with temperature and precipitation, with the latter being the main variable for the ecological model. In addition, the integration of data from malacological surveys, environmental characterization, fecal contamination, and data from communities with confirmed human cases, revealed areas of potential risk for infection in the northern and eastern regions of the municipality. In the present study, information was integrated on epidemiological aspects, transmission and risk areas for schistosomiasis in a small, rural municipality with low endemicity. Such integrated methods have been proposed as important tools for the creation of schistosomiasis transmission risk maps, serve as an example for other communities and can be used for control actions by local health authorities, e.g., indicate priority sectors for sanitation measures.

摘要

本研究的目的是采用综合方法,确定巴西米纳斯吉拉斯州低流行地区的传播风险区域。为此,确定了[某种生物]的分布区域,并将其与环境变量以及报告有血吸虫病病例的社区相关联,以便通过预测模型进行空间分析来确定感染风险。该研究在阿尔沃拉达 - 德米纳斯市开展,数据采集时间跨度为2017年至2019年(含)。利用谷歌地球引擎获取地理气候变量(温度、降水、植被指数和数字高程模型),使用R软件确定皮尔逊相关性,并使用MaxEnt软件获得生态模型。运用ArcGis软件,通过缓冲模型(直径:500米、1000米和1500米)和协同克里金法创建数据空间化地图和风险地图。在整个城市共评估了46个采集点。其中,14个采集点发现了[某种属的]蜗牛。分子分析确定了[某种生物]不同物种的存在,包括[具体物种]。没有一只蜗牛逸出尾蚴。[某种生物]在自然植被区域(森林和塞拉多)分布更为丰富,在空间分析(缓冲区)中,主要风险区域尤其在主要城市区域以及城市的北部和东部延伸地带被确定。蜗牛的分布与温度和降水相关,降水是生态模型的主要变量。此外,将贝类学调查、环境特征、粪便污染数据以及确诊人类病例社区的数据整合后,揭示了该市北部和东部地区存在潜在感染风险区域。在本研究中,整合了一个小型农村低流行市血吸虫病的流行病学、传播和风险区域等方面的信息。这种综合方法已被提议作为创建血吸虫病传播风险地图的重要工具,为其他社区树立了榜样,可被当地卫生当局用于控制行动,例如指明卫生措施的优先部门。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e19/8377395/62e2397b2c15/fmed-08-642348-g0001.jpg

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