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应用SARIMA-LSTM模型来评估对内脏莱什曼病干预措施的有效性
Mengchen Han1, Chongqi Hao1, Zhiyang Zhao2
1School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Journal of infection in developing countries
|July 28, 2025
概括
一个新的SARIMA-LSTM模型准确地评估了中国的内脏莱什曼病控制. 该模型表明,预防和控制工作是有效的,实际病例比预测的要少.
科学领域:
- 流行病学 流行病学
- 计算生物学 计算生物学
- 公共卫生 公共卫生
背景情况:
- 内脏莱什曼病症构成了重大的公共卫生挑战.
- 对控制策略的准确评估对于消除疾病至关重要.
- 之前的模型缺乏有效干预评估的精度.
研究的目的:
- 开发一种先进的预测模型,用于评估内脏莱什曼病控制.
- 提高公共卫生干预措施有效性评估的准确性.
- 将该模型应用于中国的扬泉,这是一个患有特有内脏莱什曼病的地区.
主要方法:
- 开发了一种混合的季节性自回归集成移动平均和长期短期记忆 (SARIMA-LSTM) 模型.
- 该模型将SARIMA与基于残余的LSTM神经网络集成在一起.
- 利用了泉疾病控制和预防中心的数据.
主要成果:
- 萨里马-LSTM模型显示出优异的预测性能 (MSE = 2.824,MAE = 1.279,RMSE = 1.681).
- 统计分析证实了预测和实际病例数量之间的显著差异 (p < 0.001).
- 实际的内脏莱什曼病例比模型预测的要低.
结论:
- 合并的SARIMA-LSTM模型显著优于单个SARIMA和LSTM模型的性能.
- 该模型的准确性支持实施的内脏莱什曼病预防和控制措施的有效性.
- 这种方法为公共卫生监测和干预评估提供了一个强大的工具.
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