Towards spatial predictions of disease transmission risk: classical scrapie spill-over from domestic small ruminants to wild cervids

IF 2.3 3区 环境科学与生态学 Q2 ECOLOGY Web Ecology Pub Date : 2024-07-04 DOI:10.5194/we-24-47-2024
Nuno Mouta, Leonor Orge, Joana Vicente, João Alexandre Cabral, José Aranha, João Carvalho, Rita Tinoco Torres, Jorge Pereira, Renata Carvalho, Maria Anjos Pires, Madalena Vieira-Pinto
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Abstract

Abstract. Spatial epidemiology tools play a critical role in effectively allocating resources to curb the spread of animal diseases. This study focuses on classical scrapie (CS), an animal prion disease identified in Portugal, which infects small ruminant flocks and has been shown to be experimentally transmissible to wild cervids. Utilising remote sensing technologies and semi-automatic classification models, we aimed to evaluate the risk of interspecies prion transmission from domestic small ruminants to wild cervids (hosts). To achieve this, we gathered data related to hosts and infected small ruminant flocks. Furthermore, we collected and processed freely available, medium-resolution satellite imagery to derive vegetative and biophysical spectral indices capable of representing the primary habitat features. By employing a pixel-based species distribution model, we integrated the compiled geographical distribution data and spectral data with five supervised classification algorithms (random forest, classification tree analysis, artificial neural network, generalised linear model, and generalised additive model). The consensus map allowed accurate predictions of spatialised regions exhibiting spectral characteristics similar to where CS and its hosts were initially identified. By overlapping suitable territories for disease and host occurrence, we created a spatially explicit tool that assesses the risk of prion spill-over from domestic small ruminants to wild cervids. The described methodology is highly replicable and freely accessible, thus emphasising its practical utility. This study underscores the substantial contribution of model-based spatial analysis to disease monitoring and lays the groundwork for defining populations at risk and implementing targeted control and prevention strategies, thus safeguarding both animal and public health.
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疾病传播风险的空间预测:从家养小反刍动物到野生颈鹿的典型痒病溢出效应
摘要空间流行病学工具在有效分配资源以遏制动物疾病传播方面发挥着至关重要的作用。本研究的重点是经典瘙痒病(CS),这是一种在葡萄牙发现的动物朊病毒疾病,它感染小反刍动物群,并被证明可通过实验传播给野生颈鹿。利用遥感技术和半自动分类模型,我们旨在评估朊病毒从家养小反刍动物传播到野生鹿科动物(宿主)的风险。为此,我们收集了与宿主和受感染小反刍兽群相关的数据。此外,我们还收集并处理了可免费获取的中分辨率卫星图像,以得出能够代表主要栖息地特征的植被和生物物理光谱指数。通过采用基于像素的物种分布模型,我们将汇编的地理分布数据和光谱数据与五种监督分类算法(随机森林、分类树分析、人工神经网络、广义线性模型和广义加法模型)进行了整合。该共识图能够准确预测与最初确定的 CS 及其宿主相似的光谱特征的空间化区域。通过重叠疾病和宿主发生的合适区域,我们创建了一个空间明确的工具,用于评估朊病毒从家养小反刍动物向野生颈鹿蔓延的风险。所描述的方法具有很强的可复制性,并且可以免费获取,因此强调了其实用性。这项研究强调了基于模型的空间分析对疾病监测的重大贡献,并为界定高危人群和实施有针对性的防控策略奠定了基础,从而保障了动物和公众的健康。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Web Ecology
Web Ecology Agricultural and Biological Sciences-Ecology, Evolution, Behavior and Systematics
CiteScore
4.60
自引率
0.00%
发文量
6
审稿时长
17 weeks
期刊介绍: Web Ecology (WE) is an open-access journal issued by the European Ecological Federation (EEF) representing the ecological societies within Europe and associated members. Its special value is to serve as a publication forum for national ecological societies that do not maintain their own society journal. Web Ecology publishes papers from all fields of ecology without any geographic restriction. It is a forum to communicate results of experimental, theoretical, and descriptive studies of general interest to an international audience. Original contributions, short communications, and reviews on ecological research on all kinds of organisms and ecosystems are welcome as well as papers that express emerging ideas and concepts with a sound scientific background.
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