估计变化速度以解释疾病趋势的定量废水监测
David A Holcomb1, Ariel Christensen2, Kelly Hoffman3
1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
The Science of the total environment
|August 22, 2024
概括
污水病原体监测可能无法靠谱地跟踪疾病趋势. 将废水数据与其他公共卫生监测数据相结合,可以提高实时疾病预测的准确性.
科学领域:
- 环境流行病学环境流行病学
- 公共卫生监督是对公共卫生的监督.
- 数学建模的数学建模
背景情况:
- 废水监测提供了关于公共卫生疾病趋势的见解.
- 估计病原体负载变化至关重要,但其准确性尚未评估.
研究的目的:
- 评估估计废水病原体负载变化的方法.
- 使用合成和现实世界的数据来评估方法的性能.
主要方法:
- 使用高斯过程生成合成废水时间序列.
- 与已知变化速率对比四种估计方法.
- 应用方法对来自北卡罗来纳州的SARS-CoV-2废水数据.
主要成果:
- 所有测试的方法都不一致地确定了趋势方向.
- 25-50%的估计在模拟中显示出不正确的趋势方向.
- 废水数据本身可能缺乏足够的实时跟踪可靠性.
结论:
- 废水病原体负载估计需要仔细验证.
- 将废水数据与其他监测数据相结合,可以更好地预测疾病趋势.
- 需要进一步的研究来加强实时公共卫生监测.
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