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Challenges of surveying wastewater drug loads of small populations and generalizable aspects on optimizing monitoring design

机译:调查人口少的废水中药物负荷量的挑战和可推广方面对优化监测设计的挑战

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摘要

Aims: Quantifying illicit drug loads through wastewater analysis (WWA) is an alternative approach to estimating population drug use. This study investigated the variability of daily drug loads in wastewater and their relationships to environmental factors over an extended period to: (i) explore the suitability of WWA in small populations and (ii) optimize the monitoring design for future studies. Design, Setting, Participants: Daily wastewater samples (n=1369 consecutive days) from a German village with approximately 7160 inhabitants. Measurements: Samples were analysed for cocaine and benzoylecgonine with liquid chromatography-tandem mass spectrometry. Time-series analysis was used to explore the effects of weather and other factors on daily cocaine loads. Subsampling was used to assess monitoring design. Findings: Cocaine loads [mean=652mgCOC/day, standard deviation (SD)=498mgCOC/day] increased over the study period, with higher values during winter and spring. Despite high day-to-day variation, loads were significantly higher during weekends [+161 mgCOC/day, 95% confidence interval (CI)=115-207mgCOC/day, P10-4] and days with frost (+114mgCOC/day, 95% CI=6-223mgCOC/day, P=0.039) or snow (+150mgCOC/day, 95% CI=46-253mgCOC/day, P=0.005). Annual means estimated from 1-week periods were subject to approximately 60% relative error. Increasing sample size and changing sampling from consecutive days to stratified random decreased this uncertainty. Conclusions: Day-to-day variation and seasonality of drug loads from the few long-term wastewater studies available to date suggest that up to 56 stratified random samples are required to obtain reliable (expected uncertainty around 10%) annual estimates of drug loads. Successfully assessing changes in consumption patterns or relationships to external factors requires larger sample sizes than estimating annual means, which holds true for high-prevalence drugs in small communities and low-prevalence drugs in big cities.
机译:目的:通过废水分析(WWA)量化非法药物的使用量是估算人群药物使用情况的另一种方法。这项研究调查了废水中每日药物载量的变化及其与环境因素的长期关系,以:(i)探索WWA在小人群中的适用性,以及(ii)优化监测设计以用于未来的研究。设计,环境和参与者:来自一个拥有约7160名居民的德国村庄的每日废水样本(连续n = 1369天)。测量:用液相色谱-串联质谱法分析样品中的可卡因和苯甲酰芽子碱。使用时间序列分析来探讨天气和其他因素对可卡因每日负荷的影响。二次抽样用于评估监控设计。结果:可卡因负荷[平均= 652mgCOC /天,标准偏差(SD)= 498mgCOC /天]在研究期间有所增加,在冬季和春季均较高。尽管每日变化很大,但周末的负荷明显更高[+161 mgCOC /天,95%置信区间(CI)= 115-207mgCOC /天,P <10-4]和霜冻天(+ 114mgCOC /一天,95%CI = 6-223mgCOC /天,P = 0.039)或下雪(+ 150mgCOC /天,95%CI = 46-253mgCOC /天,P = 0.005)。从1周期间估算的年均误差约为60%。样本量的增加和从连续几天到分层随机抽样的改变减少了这种不确定性。结论:迄今为止可获得的少量长期废水研究的药物负荷的日常变化和季节性表明,需要多达56个分层的随机样本才能获得可靠的(预期的不确定性约为10%)年度药物负荷估计值。要成功地评估消费方式的变化或与外部因素的关系,需要比估计年度平均值更大的样本量,这在小社区的高流行毒品和大城市的低流行毒品中也是如此。

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