title: Challenges of surveying wastewater drug loads of small populations and generalizable aspects on optimizing monitoring design.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  Daily wastewater samples (n = 1369 consecutive days) from a German village with approximately 7160 inhabitants.
  
  
  METHODS
  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.
  
  
  RESULTS
  Cocaine loads [mean = 652 mgCOC /day, standard deviation (SD) = 498 mgCOC /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) = 115-207 mgCOC /day, P < 10(-4) ] and days with frost (+114 mgCOC /day, 95% CI = 6-223 mgCOC /day, P = 0.039) or snow (+150 mgCOC /day, 95% CI = 46-253 mgCOC /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.
authors: Urban Water Management, Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.
authors: Christoph
authors: C
authors: Ort
authors: Jonas Maria
authors: JM
authors: Eppler
authors: Andreas
authors: A
authors: Scheidegger
authors: Jörg
authors: J
authors: Rieckermann
authors: Martina
authors: M
authors: Kinzig
authors: Fritz
authors: F
authors: Sörgel
mesh_terms: D002853:Chromatography, Liquid; D003042:Cocaine / Q000031:analogs & derivatives* / Q000032:analysis*; D019970:Cocaine-Related Disorders / Q000453:epidemiology*; D006801:Humans; D012621:Seasons; D053719:Tandem Mass Spectrometry; D062065:Wastewater / Q000737:chemistry*; D014887:Weather
chemical_list: D003042:Cocaine; D062065:Wastewater; C005618:benzoylecgonine
keywords: Annual mean; baseline variation; cocaine; influence of external factors; stratified random versus consecutive days; wastewater analysis