Temporal monitoring of pharmaceutical consumption using a wastewater-based epidemiologic approach

Abstract

Temporal monitoring of antidepressants, opioids consumption through influent wastewater, before and during the COVID-19 pandemic in Leuven, Belgium. Introduction: Conventional epidemiologic data sources on pharmaceutical consumption include surveys, prescription, sales, and dispensing data. However, prescribed medication may not always be dispensed, and surveys are affected by bias (e.g., response, reporting). Furthermore, data on pharmaceutical dispensing in Belgium only covers public pharmacies, and only records reimbursed medication (e.g., over-the-counter medication, some opioids are unrecorded). In addition, patients may not take the dispensed drugs as prescribed, or incorrectly. There is also a long lag time such as three years for survey data, and over three months for dispensing data. Wastewater-based epidemiology (WBE) centres on the analysis of biomarkers, i.e., human metabolic excretion products of xenobiotics in influent wastewater. WBE complements existing drug utilisation approaches and provides valuable, objective, spatio-temporal information on the consumption of pharmaceuticals in the general population that may not be measured in other datasets. WBE was applied to 24-h composite influent wastewater samples from Leuven, Belgium. Daily samples were analysed from Sept 2019 to Dec 2019 ( n = 63), and on each Monday, Wednesday, and Saturday of the week from Jan 2020 to Dec 2021 ( n = 165). The sampled period also included several governmental restrictions (e.g., stay at home measures) to contain the spread of SARS-CoV-2. Sample preparation and analysis consisted of preconcentration with solid-phase extraction and liquid chromatography coupled to tandem mass spectrometry, respectively. Measured concentrations (ng/L) of 21 pharmaceutical biomarkers, i.e., parent compounds and metabolites, were converted to population normalised mass loads (PNML) by considering the flow rate and catchment population. To better capture population movements, mobile phone data was used in the back-calculations. Concentrations of bupropion, hydromorphone, melitracen, noroxycodone, oxycodone, and tilidine were negligible or below limit of quantification and therefore excluded from further analysis. The pharmaceuticals, amitriptyline, hydroxy-bupropion, N-desmethylcitalopram, citalopram, N-desmethyl-mirtazapine, mirtazapine, trazodone, O-desmethylvenlafaxine, codeine, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine, methadone, morphine, nortilidine, O-desmethyltramadol, and tramadol were detected and included in the temporal assessment. The PNML of most psychoactive pharmaceuticals remained stable throughout the entire sampling period. Highest median PNML levels by pharmaceutical class, respectively opioid and antidepressant, were obtained for tramadol (median 508 mg/day/1000 people) and O-desmethylvenlafaxine (median 392 mg/day/1000 people). Governmental measures appear to have minimal effect on the consumption. Several studies have described the psychological distress (e.g., anxiety, stress) of these measures on mental health (COVID-19 Impact, Sciensano; Mental Health Considerations during COVID-19, WHO). However, there is a long lag time between onset of mental distress, help seeking, and the actual start of pharmaceutical therapy. The sampled period may need to be extended to detect this. It remains important to monitor psychoactive pharmaceuticals with addiction potential (e.g., opioids), as they have led to health crisis in other countries. Throughout the sampled period, a small difference in week/weekend PNML is observed for all analysed pharmaceuticals. Antidepressants and opioids are indicated to be used consistently, and long-term in case of antidepressants. We hypothesize that this change may be explained due to a change in population demographics. Leuven has a large commuting student population, approx. 45% of census population, although it should be noted that the catchment area also encompasses nearby areas. This study shows the potential of WBE to monitor consumption trends of pharmaceuticals with high temporal resolution, may not be captured by other data sources. Furthermore, our findings demonstrate that care should be taken when interpreting WBE results in case of large population disruption, such as a large commuting population or COVID-19 governmental measures.