Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: placing back-calculations in a formal statistical framework.
Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: placing back-calculations in a formal statistical framework.
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DOI：
10.1016/j.scitotenv.2014.02.101
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发表时间：
2014-07-15
影响因子：
9.8
通讯作者：
Ades, A. E.
中科院分区：
文献类型：
--
作者：
Jones, Hayley E.;Hickman, Matthew;Kasprzyk-Hordern, Barbara;Welton, Nicky J.;Baker, David R.;Ades, A. E.
关键词：
由于开发了灵敏和可靠的分析方法，可以非常准确和精确地测量污水中非法药物代谢物的浓度。基于对包括母体药物的排泄特征、给药途径和使用废水系统的个体数量在内的因素的假设，可以根据这些测量的浓度估计药物的消耗水平。当呈现这些“反算”的结果时，经常讨论不确定性的多个来源，但在估计过程中通常不会明确考虑。在本文中，我们将展示如何将这些计算置于一个更正式的统计框架中，通过假设每个参数的分布，基于对支持它的证据的回顾，使用蒙特卡罗模拟方法，然后通过反算直接传播每个参数的不确定性，产生一个分布，而不是每日或平均消耗的单一估计。这可以例如通过中值和可信区间来概括。为了证明这种方法，我们估计可卡因的消费量在一个大的城市英国人口，使用其代谢产物，苯甲酰芽子碱和norbenzoylecgonine的测量浓度。我们还展示了一个更复杂的分析，使用马尔可夫链蒙特卡罗模拟贝叶斯统计框架内实施。我们的模型允许两种代谢物同时告知每日可卡因消耗量的估计值，并明确允许天与天之间的变化。在考虑到这种可变性之后，平均每日消费量的可信区间适当地更宽，这代表了额外的不确定性。我们讨论了扩展该模型的可能性，以及废水样本的分析是否有可能有助于非法药物使用的流行模式。通过分析废水，可以估计非法药物的消费量。然而，必须正式承认不确定性的许多来源。简单而灵活的蒙特卡罗模拟方法可以实现这一点。有许多软件选项：我们提供Excel电子表格和R代码。贝叶斯建模使用马尔可夫链蒙特卡罗允许有趣的扩展。
Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these ‘back-calculations’, the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. Analysis of wastewater allows estimation of illicit drug consumption. However, it is crucial to formally acknowledge the many sources of uncertainty. The simple and flexible Monte Carlo simulation approach allows this. There are many software options: we provide an Excel spreadsheet and R code. Bayesian modelling using Markov chain Monte Carlo allows interesting extensions.
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DOI：
10.1111/j.1467-985x.2004.00349.x
发表时间：
2005-01-01
影响因子：
2
作者：
Greenland, S
通讯作者：
Greenland, S
影响因子：
3.8
作者：
Ades, AE;Lu, G
通讯作者：
Lu, G
影响因子：
2.4
作者：
Ades, A. E.;Welton, Nicky J.;Lu, Guobing
通讯作者：
Lu, Guobing
DOI：
10.1177/0272989x8500500205
发表时间：
1985-01-01
期刊：
Medical decision making : an international journal of the Society for Medical Decision Making
影响因子：
--
作者：
Doubilet, P;Begg, C B;McNeil, B J
通讯作者：
McNeil, B J
影响因子：
11.8
作者：
Khan, Usman;Nicell, Jim A.
通讯作者：
Nicell, Jim A.