整合因果推理和机器学习来量化气候与疟疾的关系:来自哥伦比亚市政当局的温度和降雨门证据
1Facultad de Ciencias Médicas y de la Salud, Universidad de Santander, Instituto Masira , Bucaramanga, Santander, Colombia.
PLOS global public health
|February 5, 2026
概括
最佳降雨量和温度值显著影响哥伦比亚的疟疾发病率. 识别这些气候因素可以加强疟疾控制和早期预警系统.
科学领域:
- 环境科学 环境科学
- 流行病学 流行病学
- 公共卫生 公共卫生
背景情况:
- 降雨和温度等气候变量是疟疾传播的关键驱动因素.
- 量化气候和疟疾发病率之间的准确关系对于有效的控制策略至关重要,特别是在哥伦比亚等不同地理区域.
研究的目的:
- 估计雨量和温度对哥伦比亚各市镇疟疾发病率的因果暴露-反应曲线.
- 为了确定针对性干预的最佳气候值与最高疟疾发病率相关.
主要方法:
- 在2007年至2023年期间,环保观察研究涉及969个哥伦比亚市 (低于1600米) 从2007年至2023年.
- 对疟疾的每月标准化发病率 (SIR) 的计算.
- 应用定向环形图 (DAG) 和目标最大概率估计 (TMLE) 来估计影响和调整混.
主要成果:
- 在降雨量,温度和疟疾SIR之间观察到非线性关系.
- 确定疟疾发病率最高的最佳条件是大约25°C和37毫米的降雨量.
- 检测到残留混偏差 (p<0.05),对未测量的混因素的耐受性低至中等 (E值:1.14-1.48).
结论:
- 降雨量和温度对哥伦比亚疟疾发病率有非线性影响.
- 降雨和温度的特定门与增加疟疾风险有关.
- 研究结果支持将这些气候值纳入疟疾早期预警系统,以加强公共卫生干预.
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