Differences in drug use across three neighbourhoods with varying socioeconomic levels: A wastewater-based surveillance study
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Elsevier
Abstract
This study measured 39 biomarkers of licit (e.g., alcohol, nicotine, benzodiazepines, antidepressants) and illicit drug consumption (e.g., cocaine, amphetamine, cannabis, new psychoactive substances) in wastewater from three neighbourhoods (NGBs) in Barcelona, each representing different socioeconomic and lifestyle profiles. Four weeklong sampling campaigns were conducted between March 2021 and March 2022. The results revealed significant differences in drug use across neighbourhoods that are not apparent in city-level analyses. These differences were particularly notable for illicit drugs—such as higher morphine and cannabis loads in socioeconomically disadvantaged areas—as well as for specific benzodiazepines and antidepressants, which varied in prevalence between neighbourhoods. Alcohol and nicotine patterns were more strongly associated with the local density of bars and restaurants than with socioeconomic status. A clear weekend peak was observed for substances like alcohol. Temporal analysis over the study period showed increased consumption of certain drugs at the end of 2021, likely linked to the reopening of nightlife venues and elevated anxiety related to the COVID-19 pandemic. This study highlights the value of applying wastewater-based epidemiology (WBE) at the intra-city level. By moving beyond aggregated citywide data, intra-urban WBE can reveal spatial and temporal variations in drug use that may otherwise go unnoticed. This approach also enables the identification of communities or socioeconomic groups at higher risk of substance use or mental health challenges, offering critical insights for public health authorities to develop targeted interventions and preventive strategies.
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L. Corominas et al. Differences in drug use across three neighbourhoods with varying socioeconomic levels: A wastewater-based surveillance study. Journal of Environmental Chemical Engineering 14, 2026, 121294. https://doi.org/10.1016/j.jece.2026.121294
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https://doi.org/10.1016/j.jece.2026.121294Sponsors
This research was funded by Delegación del Gobierno para el Plan Nacional Sobre Drogas (2020I009), Instituto de Salud Carlos III-Next Generation EU/ERDF (RD21/0009/0012, RD24/0003/0001 & RD24/0003/0020 – RIAPAd Network). L. Bijlsma acknowledges grant RYC2020–028936-I funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”. We acknowledge: the SCOREwater project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 820751; BCASA, s::can Iberia Sistemas de Medición S.L., Institut Metròpoli and EURECAT for their efforts in setting up and maintaining the SCOREwater stations; the Generalitat de Catalunya through the Consolidated Research Group grants ICRA-Tech 2021-SGR-01283 and 2021 SGR 00753, SA-2021–443, SA-2022–430, and the funding from the CERCA program; the Spanish Agencia Estatal de Investigación, MCIN/AEI/10.13039/501100011033, through grants RED2022–134363-T, PID2022–139446OB-C21, PID2022–139446OB-C22, and PTA2019–017397-I.
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© 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC license








