Biodesign Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Avenue, Tempe, AZ 85287-8101, USA.
Biodesign Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Avenue, Tempe, AZ 85287-8101, USA.
Sci Total Environ. 2020 Jul 20;727:138406. doi: 10.1016/j.scitotenv.2020.138406. Epub 2020 Apr 16.
Wastewater-based epidemiology (WBE) is an economical technique for monitoring and managing the health and behavior of human populations. Using 2017 nationwide data on geospatial population demographics as a test case, we simulated repeated sampling at all major U.S. wastewater treatment plants (WWTPs; n = 13,940) under constant biomarker loading conditions, to explore the potential sensitivity of WBE for generating skewed data. Simulation of repeated sewage sampling over all four seasons of 2017 yielded a number of expected, inter-dependent phenomena triggered by cooler wintertime temperatures compared to summertime results, including relatively (i) slower in-sewer biomarker decay, (ii) longer distal reach of WBE, (iii) larger effective sewershed monitoring areas, and (iv) an increase in the population represented. Additional important but not necessarily anticipated simulation outcomes included (v) distinct, non-random changes in demographic parameters of monitored subpopulations (e.g., by household income, educational attainment, military service, unemployment, and lack of health insurance), (vi) recurring observation of the latter demographic patterns across various geospatial scales and regions, and (vii) more evenly distributed results in the winter. In contrast, data obtainable by WBE in the summertime were dominated by households residing closest to the WWTP and subpopulations of relatively lesser wealth, educational achievement, healthcare access and employability. The analytical approach presented here should be readily applicable to other regions worldwide and may help to improve the design, robustness and interpretation of future WBE studies.
基于污水的流行病学（WBE）是一种经济有效的监测和管理人群健康和行为的技术。我们使用 2017 年全国人口地理分布数据作为测试案例，在恒定生物标志物负荷条件下，模拟了所有主要美国污水处理厂（WWTP；n=13940）的重复采样，以探索 WBE 产生偏斜数据的潜在敏感性。对 2017 年四个季节的重复污水采样进行模拟，与夏季结果相比，冬季气温较低会引发一些预期的、相互依赖的现象，包括相对（i）生物标志物在下水道中衰减较慢，（ii）WBE 的远端距离较长，（iii）更大的有效下水道流域监测面积，以及（iv）代表的人口增加。其他重要但不一定预期的模拟结果包括（v）监测子群体的人口统计学参数发生明显、非随机变化（例如，按家庭收入、教育程度、兵役、失业和缺乏医疗保险划分），（vi）在各种地理空间尺度和地区反复观察到后者的人口统计模式，以及（vii）冬季结果分布更加均匀。相比之下，WBE 在夏季可获得的数据主要来自距离 WWTP 最近的家庭和相对财富、教育程度、医疗保健获取和就业能力较低的子群体。这里提出的分析方法应该可以很容易地应用于世界其他地区，并有助于改进未来 WBE 研究的设计、稳健性和解释。
