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开发和应用基于WebGIS的预测系统,用于对猪肉病的多标准决策分析
Tao Liu1,2, Lei Cao1,2, Hao Rang Wang1,2
1College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China.
Scientific reports
|September 10, 2024
概括
预测中国的猪肉病风险区域对于养猪至关重要. 一个使用多标准决策分析 (MCDA) 的新模型确定了关键地区,帮助疾病控制工作.
科学领域:
- 兽医流行病学 兽医流行病学
- 空间分析 空间分析
- 传染病建模 传染病建模
背景情况:
- 由Pasteurella multocida (P. multocida) 引起的猪病对全球猪产业构成重大威胁.
- 动物疾病传播的早期检测对于公共卫生和有效的疾病管理策略至关重要.
- 评估疾病风险区域对于实施有针对性的预防措施和控制策略至关重要.
研究的目的:
- 开发和验证一个预测模型,用于识别中国大陆猪肉病高风险地区.
- 通过使用多标准决策分析 (MCDA) 评估猪巴氏菌病风险的空间分布.
- 为疾病预防和控制当局提供决策支持系统.
主要方法:
- 主要成分分析 (PCA) 用于确定七个空间风险因素的权重.
- 模糊的会员函数被用来标准化风险因素.
- 使用加权线性组合方法生成风险图,使用不确定性图进行灵敏度分析.
主要成果:
- 该研究预测,中国大陆中南部的猪肉病高风险地区包括四川,重庆,广东和广西.
- 预测模型表现中等,曲线下的面积 (AUC) 为0.80 (95% CI 0.75-0.84).
- 不确定性图显示最大标准偏差低于0.01,表明模型稳定性.
结论:
- 与WebGIS技术集成的多标准决策分析 (MCDA) 提供了一个可靠的系统,用于预测猪肉病风险区域.
- 开发的系统通过定期更新为疾病预防和控制提供了有价值的决策支持.
- 准确的风险区域预测对于保护猪业和公共健康至关重要.
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