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基于集合建模算法的小反刍兽疫病毒(PPRV)当前和未来分布的全球生态位建模。

Global ecological niche modelling of current and future distribution of peste des petits ruminants virus (PPRv) with an ensemble modelling algorithm.

机构信息

Sekota Dryland Agricultural Research Center, Sekota, Ethiopia.

School of Veterinary Medicine, Woldia University, Woldia, Ethiopia.

出版信息

Transbound Emerg Dis. 2021 Nov;68(6):3601-3610. doi: 10.1111/tbed.13967. Epub 2021 Jan 7.

Abstract

Peste des petits ruminants (PPR) is a highly contagious transboundary viral disease of sheep and goats that negatively impacted the farmers and pastoralists' livelihood in Africa and Asia. To overcome the disease's consequences, the OIE and FAO are collaborating efforts to eradicate the disease once and for all. We developed a predictive model that delineates suitable territories for the virus globally in support of this eradication programme. To achieve this, we used an ecological niche modelling with an ensemble algorithm. AUC-ROC curve, true skill statistics (TSS) and Kappa values were used to evaluate the model's performance. A TSS value greater than 0.7 was used to pool outputs of the nine model. The ensemble model has better performance than individual models by every evaluation metrics (Kappa = 0.82, TSS = 0.88 and ROC = 0.99). Annual minimum temperature (24.92%), annual maximum temperature (21.37%), goat density (18.03%) and solar radiation (14.04%) have the highest overall contribution in the ensemble model. The model indicates that India, Mongolia, Iraq, Iran, Afghanistan, Nepal, Tanzania, Uganda, Kenya, Sudan, Angola, Nigeria, DRC, Ghana, Sierra Leon, Southern Spain, France, Albania, Montenegro, Macedonia, Italy, Armenia and Azerbaijan are highly suitable for PPRv. In 2040, suitable territories for PPRv will diminish, indicating the odds are with us in eradicating disease by 2030. We believe that this model can be used as an epidemiological tool to facilitate the global eradication programme of the disease set by the OIE and FAO.

摘要

小反刍兽疫(PPR)是一种高传染性的跨边界病毒性疾病,对非洲和亚洲的农民和牧民的生计产生了负面影响。为了克服该疾病的后果,国际兽疫局和粮农组织正在合作努力,以期一劳永逸地消灭该疾病。我们开发了一个预测模型,在全球范围内划定适合病毒的区域,以支持这一消灭计划。为了实现这一目标,我们使用了一种基于集合算法的生态位建模方法。AUC-ROC 曲线、真实技能统计(TSS)和 Kappa 值用于评估模型的性能。TSS 值大于 0.7 时,用于汇集九个模型的输出。与个别模型相比,集合模型在每个评估指标上都表现出更好的性能(Kappa=0.82、TSS=0.88 和 ROC=0.99)。在集合模型中,年最低温度(24.92%)、年最高温度(21.37%)、山羊密度(18.03%)和太阳辐射(14.04%)的总贡献最高。该模型表明,印度、蒙古、伊拉克、伊朗、阿富汗、尼泊尔、坦桑尼亚、乌干达、肯尼亚、苏丹、安哥拉、尼日利亚、刚果民主共和国、加纳、塞拉利昂、西班牙南部、法国、阿尔巴尼亚、黑山、马其顿、意大利、亚美尼亚和阿塞拜疆是 PPRv 的高度适宜地区。到 2040 年,PPRV 的适宜地区将减少,这表明到 2030 年我们有很大的机会消灭这种疾病。我们相信,该模型可作为一种流行病学工具,以促进国际兽疫局和粮农组织制定的全球消灭疾病计划。

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