基于ENSO预测的亚洲H5禽流感综合区域特定建模
Yinghui Su1, Ruoxuan Wu1, Pengfei Liu1
1State Key Laboratory of Veterinary Public Health and Safety, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
One health (Amsterdam, Netherlands)
|January 22, 2026
概括
高致病性禽流感 (HPAI) 在亚洲家禽中的爆发在厄尔尼诺条件下下降 (高MEI). 野生鸟类HPAI动态显示了复杂的反应,预计东亚的流行病压力将持续.
科学领域:
- 兽医流行病学 兽医流行病学
- 气候科学 气候科学
- 公共卫生 公共卫生
背景情况:
- 高致病性禽流感 (HPAI) 对亚洲的家禽,野生动物和人类健康构成重大威胁.
- 厄尔尼诺-南方振荡 (ENSO) 是全球气候变化的主要驱动因素.
- 了解气候对HPAI的影响对于有效的疾病控制至关重要.
研究的目的:
- 量化ENSO对亚洲不同地区和东道国的H5 HPAI动态的影响.
- 开发一个基于气候信息的框架,用于预测HPAI事件的频率和强度.
- 支持H5 HPAI的早期预警系统和有针对性的预防策略.
主要方法:
- 用区域和宿主分层的通用添加模型 (GAM) 来分析HPAI事件数据.
- 多变量ENSO指数 (MEI) 作为ENSO影响的主要预测指标.
- 经常性神经网络 (RNN) 用于MEI趋势预测和集成到GAM中.
主要成果:
- 在东亚和南亚的家禽中观察到MEI和HPAI频率之间的负相关性.
- 野生鸟类对MEI的HPAI反应是不规则的,并且特定于阶段.
- 预测显示,东亚野生鸟类的流行病压力持续,其他地区的趋势稳定或下降.
结论:
- 恩索显著影响HPAI动态,在家禽和野生鸟类中具有明显的模式.
- 使用统计和深度学习模型进行基于气候的预测可以提高HPAI准备.
- 该框架支持有针对性的干预措施,以减轻HPAI风险并防止动物传播.
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