人口驱动的基于废水的流行病学:为加强化学监测改进人口估计
Kishore Kumar Jagadeesan1,2, Megan Robertson2,3, John Bagnall2,3
1Department of Chemistry, University of Bath, Claverton Down, Bath BA2 7AY, U.K.
Environmental science & technology
|November 18, 2025
概括
基于废水的流行病学 (WBE) 人口估计使用英国人口普查和NHS数据进行了改进. 密度调整的重叠启动 (BtDO) 模型提供了最准确的结果,揭示了与制药负载的人口关系.
科学领域:
- 环境科学 环境科学
- 公共卫生 公共卫生
- 流行病学 流行病学
背景情况:
- 基于废水的流行病学 (WBE) 对公共卫生和环境监测至关重要.
- 精确的人口估计和废水处理厂 (WWTP) 水域的人口概况是一个重大挑战.
研究的目的:
- 通过整合英国人口普查和NHS数据来完善WWTP水域的人口估计.
- 评估对废水组成的人口影响.
- 为了比较人口估计的四种统计模型的性能.
主要方法:
- 集成高分辨率的2021年英国人口普查数据,NHS患者登记记录和WWTP化学参数.
- 四种统计模型的比较:简单方法 (SA),密度调整引导 (BtD),密度调整引导与重叠 (BtDO) 和贝叶斯层次模型 (ByD).
- 对人口因素 (年龄,贫困) 的分析及其与制药负载的相关性.
主要成果:
- 密度调整的重叠引导 (BtDO) 方法产生了最一致的人口估计,相对不确定性较低 (在大型流域中低至1.5%).
- 老年人口和更高的贫困水平与增加的药物负载相关 (例如,止痛药,r = 0.92,p < 0.01).
- 传统的指标,如化学氧气需求 (COD) 和生物氧气需求 (BOD),高估了人口,特别是在农业地区,由于非人类来源.
结论:
- 开发的框架提高了WBE的精度,用于公共卫生监测和环境风险评估.
- BtDO模型提供了一种可靠的方法,用于在WBE.人口估计.
- 了解人口统计的影响对于准确解释废水数据至关重要.
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