Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe
Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe
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DOI：
10.4081/gh.2015.348
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发表时间：
2015-01-01
影响因子：
1.7
通讯作者：
Hendrickx, Guy
中科院分区：
文献类型：
--
作者：
Ducheyne, Els;Charlier, Johannes;Hendrickx, Guy
需要一个统一的采样方法结合空间建模，以更新目前的知识，在欧洲的奶牛肝片吸虫病。在欧盟GLOWORM项目的范围内，从比利时、德国、爱尔兰、波兰和瑞典849个城市的3 359个随机选择的农场收集了样本，并使用间接散装罐奶（BTM）酶联免疫吸附试验（ELISA）评估了它们的感染状况。当光密度比（ODR）超过0.3临界值时，奶牛场被视为接触。两个整体建模技术，随机森林（RF）和提升回归树（BRT），被用来获得接触肝片吸虫的概率的空间分布，使用遥感环境变量（1公里的空间分辨率）和气象站的插值作为预测。比利时、德国、爱尔兰、波兰和瑞典南部的ODR中位数分别为0.31、0.12、0.54、0.25和0.44。使用0.3的阈值，571个城市被归类为积极的，429个为消极的。RF被视为能够预测暴露的空间分布，受试者操作特征（ROC）曲线下面积（AUC）为0.83（BRT为0.96）。这两个模型都将降雨量和温度确定为影响接触概率的最重要因素。这两种模式都确定了高和低接触的地区，快速公交系统更善于区分低概率和高概率接触;因此，这种模式在实践中可能更有用。鉴于一个统一的采样策略，它应该是可能的，以产生强大的空间模型，在欧洲的奶牛肝片吸虫病作为输入的时间模型和检测基线概率的偏差。需要对所调查的生态气候范围以外地区的模型输出进行进一步研究。
A harmonized sampling approach in combination with spatial modelling is required to update current knowledge of fasciolosis in dairy cattle in Europe. Within the scope of the EU project GLOWORM, samples from 3,359 randomly selected farms in 849 municipalities in Belgium, Germany, Ireland, Poland and Sweden were collected and their infection status assessed using an indirect bulk tank milk (BTM) enzyme-linked immunosorbent assay (ELISA). Dairy farms were considered exposed when the optical density ratio (ODR) exceeded the 0.3 cut-off. Two ensemble-modelling techniques, Random Forests (RF) and Boosted Regression Trees (BRT), were used to obtain the spatial distribution of the probability of exposure to Fasciola hepatica using remotely sensed environmental variables (1-km spatial resolution) and interpolated values from meteorological stations as predictors. The median ODRs amounted to 0.31, 0.12, 0.54, 0.25 and 0.44 for Belgium, Germany, Ireland, Poland and southern Sweden, respectively. Using the 0.3 threshold, 571 municipalities were categorized as positive and 429 as negative. RF was seen as capable of predicting the spatial distribution of exposure with an area under the receiver operation characteristic (ROC) curve (AUC) of 0.83 (0.96 for BRT). Both models identified rainfall and temperature as the most important factors for probability of exposure. Areas of high and low exposure were identified by both models, with BRT better at discriminating between low-probability and high-probability exposure; this model may therefore be more useful in practise. Given a harmonized sampling strategy, it should be possible to generate robust spatial models for fasciolosis in dairy cattle in Europe to be used as input for temporal models and for the detection of deviations in baseline probability. Further research is required for model output in areas outside the eco-climatic range investigated.