一个定量决策支持框架,以评估基于废水的呼吸道病毒监测流行病学的可行性和敏感性
Sunita Samantarat1, Kwanrawee Sirikanchana2, Yong Poovorawan3
1Industrial Toxicology and Risk Assessment Graduate Program, Department of Environmental Science, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.
International journal of hygiene and environmental health
|February 24, 2026
概括
基于废水的流行病学 (WBE) 可以监测像SARS-CoV-2和RSV这样的疾病. 检测灵敏度取决于病毒类型和方法,需要可靠监测的框架.
科学领域:
- 环境微生物学环境微生物学
- 传染病流行病学 传染病流行病学
- 公共卫生监督是对公共卫生的监督.
背景情况:
- 基于废水的流行病学 (WBE) 提供了一种具有成本效益的,非侵入性的传染病监测方法.
- 针对病毒监测的实际WBE实施面临挑战,因为受病原体和方法的影响的检测灵敏度是可变的.
- 准确的WBE需要了解最小的感染个体,以便可靠地检测病毒.
研究的目的:
- 预期评估WBE对SARS-CoV-2,RSV,IAV和RhV的可行性和敏感性.
- 通过WBE估计所需的感染个体的最小数量,以可靠地检测这些病毒.
- 开发和应用一个定量决策支持框架,用于WBE的规划和优化.
主要方法:
- 收集全年每周的废水数据,用于病毒监测.
- 应用了定量决策支持框架和蒙特卡洛模拟.
- 纳入便脱落率,恢复效率和RNA衰变到模拟模型中.
主要成果:
- 尽管在临床循环中,但SARS-CoV-2被检测到全年;RSV显示季节性检测;IAV和RhV未被检测到.
- SARS-CoV-2需要最少的感染 (0.85/100k) 进行检测,而IAV需要最多的 (1177.02/100k) 由于便流失较低.
- 具有≥35%恢复效率的滴滴数字PCR可以检测所有四种病毒.
结论:
- WBE的敏感性是由病毒特异性特征和方法性能的组合决定的.
- 数据驱动的框架有助于规划和优化WBE监控计划.
- 了解病毒泄露和恢复效率对于改善WBE灵敏度至关重要.
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