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首页> 外文期刊>Frontiers in Medicine >Identification of Risk Areas for Intestinal Schistosomiasis, Based on Malacological and Environmental Data and on Reported Human Cases
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Identification of Risk Areas for Intestinal Schistosomiasis, Based on Malacological and Environmental Data and on Reported Human Cases

机译:基于疾病环境数据和报告人类病例,鉴定肠血吸虫病风险区域

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摘要

The aim of the present study was to use an integrated approach for the identification of risk areas for Schistosoma mansoni transmission in an area of low endemicity in Minas Gerais, Brazil. For that, areas of distribution of Biomphalaria glabrata 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 Biomphalaria . Molecular analyses identified the presence of different species of Biomphalaria , including B. glabrata . None of the snails eliminated S. mansoni cercariae. The distribution of B. glabrata 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.
机译:本研究的目的是利用综合方法来识别巴西Minas Gerais的低流行性地区的血吸虫曼逊传播风险区域。为此,鉴定了生物pharariaBlabrata的分布区域,并与环境变量和社区有关,报告的血吸虫病病例有关,以确定通过预测模型的空间分析感染的风险。该研究是在Alvorada De Minas的市中进行的,其中包括2017年和2019年之间的数据,包括在内。谷歌地球发动机用于获得地质气候变量(温度,降水,植被指数和数字海拔模型),R软件来确定Pearson的相关性和最大软件以获得生态模型。 ArcGIS软件用于使用缓冲模型(直径:500,1000和1,500米)和Cokriging来创建具有数据时空化和风险地图的地图。在整个市内,评估了46个收集点。其中,14种鼻子的生物骨盆属的蜗牛。分子分析确定了不同物种的生物骨髓,包括B.Glabrata。没有蜗牛消除了S. Mansoni Cercariae。 B.Glabrata的分布在天然植被(森林和Cerrado)的地区更丰富,并且对于空间分析(缓冲区),主要风险领域被确定在主要城市地区,并朝着市政府的北部和东部扩展。蜗牛的分布与温度和降水相关,后者是生态模型的主要变量。此外,从恶性肿瘤调查,环境特征,粪便污染和数据与确认人类病例中的数据集成的整合,揭示了市政北部和东部地区感染潜在风险的领域。在本研究中,信息综合了血吸虫病的流行病学方面,传播和风险地区,其小农村城市,具有低流行性。已经提出了这种综合方法作为创建血吸虫病传输风险地图的重要工具,作为其他社区的示例,可以用于当地卫生当局的控制行动,例如,指示卫生措施的优先部门。

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