VISAVET Health Surveillance Center, Complutense University of Madrid, Madrid, Spain.
Department of Animal Health, Faculty of Veterinary, Complutense University of Madrid, Madrid, Spain.
Sci Rep. 2024 Mar 4;14(1):5312. doi: 10.1038/s41598-024-55828-6.
Classical swine fever has been spreading across the country since its re-emergence in Japan in 2018. Gifu Prefecture has been working diligently to control the disease through the oral vaccine dissemination targeting wild boars. Although vaccines were sprayed at 14,000 locations between 2019 and 2020, vaccine ingestion by wild boars was only confirmed at 30% of the locations. Here, we predicted the vaccine ingestion rate at each point by Random Forest modeling based on vaccine dissemination data and created prediction surfaces for the probability of vaccine ingestion by wild boar using spatial interpolation techniques. Consequently, the distance from the vaccination point to the water source was the most important variable, followed by elevation, season, road density, and slope. The area under the curve, model accuracy, sensitivity, and specificity for model evaluation were 0.760, 0.678, 0.661, and 0.685, respectively. Areas with high probability of wild boar vaccination were predicted in northern, eastern, and western part of Gifu. Leave-One-Out Cross Validation results showed that Kriging approach was more accurate than the Inverse distance weighting method. We emphasize that effective vaccination strategies based on epidemiological data are essential for disease control and that our proposed tool is also applicable for other wildlife diseases.
自 2018 年日本再次爆发古典猪瘟以来，该病已在全国范围内蔓延。岐阜县一直致力于通过针对野猪的口服疫苗传播来控制该疾病。尽管 2019 年至 2020 年在 14000 个地点喷洒了疫苗，但仅在 30%的地点确认了野猪摄入疫苗。在这里，我们根据疫苗传播数据通过随机森林模型预测了每个点的疫苗摄入率，并使用空间插值技术为野猪疫苗摄入概率创建了预测曲面。结果表明，疫苗接种点到水源的距离是最重要的变量，其次是海拔、季节、道路密度和坡度。模型评估的曲线下面积、模型准确性、灵敏度和特异性分别为 0.760、0.678、0.661 和 0.685。预测结果显示，岐阜县的北部、东部和西部为野猪疫苗接种的高概率区域。留一法交叉验证结果表明，克里金法比反距离权重法更准确。我们强调，基于流行病学数据的有效疫苗接种策略对于疾病控制至关重要，并且我们提出的工具也适用于其他野生动物疾病。
