使用Poisson和负二项式模型预测蚊子传播疾病的爆发:一项比较研究
Abdullah Al-Manji1, Adil Al Wahaibi2, Mohammed Al-Azri1
1Department of Family Medicine and Public Health, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Oman.
Journal of infection and public health
|August 3, 2025
概括
通过使用包括延迟气候和蚊子数据的等级模型,提高了在阿曼准确的登革热预测. 带有滞后预测因素的负二项模型最好预测未来的登革热疫情.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 数学建模的数学建模
背景情况:
- 登革热是一种重要的蚊子传播疾病 (MBD),是全球日益增长的挑战.
- 城市化,气候变化和旅行增加了MBD的传播.
- 准确的预测模型对于早期登革热检测和疫情控制至关重要.
研究的目的:
- 开发和比较层次化的贝叶斯模型,用于预测阿曼的登革热病例.
- 评估具有或没有滞后环境和昆虫学预测因素的模型.
- 为了确定登革热爆发预测的关键预测因素.
主要方法:
- 来自阿曼地区的每周登革热数据 (2020-2024) 的回顾性分析.
- 开发了四种层次化的贝叶斯模型 (Poisson和负二项式,有或没有滞后).
- 使用融合诊断,MSE,AUC,混矩阵和LOOIC进行评估.
主要成果:
- 带有滞后变量的负二项模型表现出优异的性能 (AUC=0.881,最低LOOIC和MSE).
- 蚊的积极性是最强的预测因素;风速有积极影响,温度有延迟的负面影响.
- 2025年初的预测与观察到的登革热病例数量准确匹配.
结论:
- 将滞后预测因素集成到负二项分层模型中,可以显著改善阿曼登革热爆发的预测.
- 研究结果支持在MBD早期预警系统中使用滞后变量和层次模型.
- 这种方法提高了公共卫生干预措施和对蚊子传播疾病的疫情准备.
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