用气候和污染数据预测哥斯达黎加因呼吸道疾病而出院的医院排放情况
Shu Wei Chou-Chen1,2, Luis A Barboza1,3
1Centro de Investigación en Matematica Pura y Aplicada, Universidad de Costa Rica, Costa Rica.
Mathematical biosciences and engineering : MBE
|August 23, 2024
概括
准确预测呼吸道疾病住院情况对于医疗保健资源分配至关重要. 这项研究开发了利用气候和污染数据的预测模型,以改善公共卫生决策.
科学领域:
- 环境科学环境科学
- 公共卫生 公共卫生
- 数据科学是数据科学.
背景情况:
- 呼吸系统疾病对医疗保健系统造成了重大的全球经济负担.
- 疾病发病率受到气候,社会经济因素和污染的影响.
研究的目的:
- 模拟和预测哥斯达黎加医院每周的呼吸系统住院病例.
- 确定影响住院率的关键气候和污染因素.
主要方法:
- 使用随机森林,XGboost,Prophet 和整体方法进行预测.
- 包含22个气候变化指数和气溶光学深度 (污染指标).
- 在2000-2018年的数据上训练模型,在2019年的数据上测试,使用滑动窗口和网格搜索优化.
主要成果:
- 根据准确性和过度装配预防,确定了每个地区的最佳预测模型.
- 计算预测间隔使用符合推理可靠的预测.
- 确定了气候变量的相对重要性,揭示了区域模式.
结论:
- 开发了可靠的呼吸系统住院预测模型.
- 证明了统计学学习和环境数据在公共卫生中的有用性.
- 为优化资源分配提供了一个框架,以应对呼吸系统疾病的趋势.
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