Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods

Abstract

BackgroundWastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures.MethodsWe analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities’ scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA).ResultsThe three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load.ConclusionFDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

Wastewater-Based Epidemiology of Cocaine in the Brazilian Federal District: Spatial Distribution, Weekly Variation and Sample Preservation Strategies

“…1,2 Concentration of the drug residues can be assessed through analytical routines that include sample collection and preservation, followed by specific analytes separation and quantification. Benzoylecgonine (BE) and cocaine (COC) have been the most frequently investigated substances within wastewater-based epidemiology (WBE) initiatives around the world, [3][4][5][6][7] since the former is the most abundant cocaine metabolite. Also for this reason, analytical data concerning benzoylecgonine in wastewater samples has been used as a near real-time tool to estimate cocaine consumption for a given population.…”

Estimation of illicit drug use in the main cities of Colombia by means of urban wastewater analysis

“…wastewater-based epidemiology (WBE), has been presented as a complementary data source to other monitoring tools such as surveys, treatment demand and law enforcement data. The approach has shown great progress, and recent efforts have been put in data triangulation with other sources (Been et al, 2015(Been et al, , 2016 and the statistical analysis of the data produced (Salvatore et al, 2015), especially in large comparison studies. Despite several limitations, it has shown clear advantages, which have been widely recognized EMCDDA, 2015a).…”

Screening for illicit drugs in pooled human urine and urinated soil samples and studies on the stability of urinary excretion products of cocaine, MDMA, and MDEA in wastewater by hyphenated mass spectrometry techniques

“…Analysis of wastewater for illicit drugs is a complementary approach to surveys for obtaining data on drug consumption trends in a community, since wastewater can be considered as a large, strongly diluted, pooled urine (PU) sample. [1][2][3] Wastewater-based epidemiology (WBE) estimates drug consumption at the community level by quantifying excretion products (drug and/or its metabolites) in wastewater and back calculating concentration of these targets to actual drug consumption. An important prerequisite for these back calculations is the knowledge about the best biomarkers to reflect human consumption and their stability in the sewer.…”