Early warning of NPS using intra-urban wastewater-based epidemiology
Abstract
Introduction: New psychoactive substances (NPS) evolve rapidly and challenge conventional surveillance systems. Wastewater-based epidemiology (WBE) enables the detection of emerging drug use patterns, but treatment plant-level approaches face limitations for NPS due to low concentrations and degradation
Objectives: To design an intra-urban early warning system based on WBE to enhance early detection of NPS and support timely public health decision-making
Methods: We developed a model integrating sociodemographic data, drug use indicators, and the sewer network of Barcelona using geographic information systems. The network was represented as a graph, and an optimization algorithm was applied to identify sampling sites that maximize detection capacity while balancing population coverage, proximity to “hotspots,” and minimization of interference (e.g., hospitals). Two strategies were evaluated: population coverage (4 sites) and hotspot-focused surveillance (5 sites). Coverage and implementation costs were estimated
Results: Optimal sampling locations were identified in districts with a higher likelihood of NPS use. The population-based strategy achieved coverage of up to 14.5% of the target population, while the hotspot-focused strategy covered up to 24.7% of identified hotspots. Estimated annual costs ranged from €127,000 to €154,000, with sample collection accounting for the largest share
Conclusions: This study presents an innovative, data-driven and scalable approach for early detection of NPS at the urban level. Combining intra-urban WBE with optimization algorithms enables non-intrusive, neighborhood level surveillance that is fully anonymized and independent of healthcare access or testing behaviours. This approach generates timely, objective, and actionable intelligence, strengthening early warning systems and improving preparedness for emerging public health threats
Key messages: • Intra-urban WBE with optimisation enables earlier, more precise detection of NPS, strengthening urban early warning systems and supporting timely public health action.
• A scalable, anonymised and data-driven approach improves detection of emerging drug use beyond treatment plants, enhancing preparedness and targeted responses.
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BibTeX
@article{mazariogarcia2026early,
title = {{Early warning of NPS using intra-urban wastewater-based epidemiology}},
author = {M Mazarío-García and D Martínez and J Pueyo-Ros and S Burdons and MJ Chesa and E Calle and MG Barbaglia and M Bartroli and LL Corominas},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.1862},
url = {https://doi.org/10.1093/eurpub/ckag169.1862},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Early warning of NPS using intra-urban wastewater-based epidemiology
AU - M Mazarío-García
AU - D Martínez
AU - J Pueyo-Ros
AU - S Burdons
AU - MJ Chesa
AU - E Calle
AU - MG Barbaglia
AU - M Bartroli
AU - LL Corominas
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.1862
UR - https://doi.org/10.1093/eurpub/ckag169.1862
AB - Introduction: New psychoactive substances (NPS) evolve rapidly and challenge conventional surveillance systems. Wastewater-based epidemiology (WBE) enables the detection of emerging drug use patterns, but treatment plant-level approaches face limitations for NPS due to low concentrations and degradation Objectives: To design an intra-urban early warning system based on WBE to enhance early detection of NPS and support timely public health decision-making Methods: We developed a model integrating sociodemographic data, drug use indicators, and the sewer network of Barcelona using geographic information systems. The network was represented as a graph, and an optimization algorithm was applied to identify sampling sites that maximize detection capacity while balancing population coverage, proximity to “hotspots,” and minimization of interference (e.g., hospitals). Two strategies were evaluated: population coverage (4 sites) and hotspot-focused surveillance (5 sites). Coverage and implementation costs were estimated Results: Optimal sampling locations were identified in districts with a higher likelihood of NPS use. The population-based strategy achieved coverage of up to 14.5% of the target population, while the hotspot-focused strategy covered up to 24.7% of identified hotspots. Estimated annual costs ranged from €127,000 to €154,000, with sample collection accounting for the largest share Conclusions: This study presents an innovative, data-driven and scalable approach for early detection of NPS at the urban level. Combining intra-urban WBE with optimization algorithms enables non-intrusive, neighborhood level surveillance that is fully anonymized and independent of healthcare access or testing behaviours. This approach generates timely, objective, and actionable intelligence, strengthening early warning systems and improving preparedness for emerging public health threats Key messages: • Intra-urban WBE with optimisation enables earlier, more precise detection of NPS, strengthening urban early warning systems and supporting timely public health action. • A scalable, anonymised and data-driven approach improves detection of emerging drug use beyond treatment plants, enhancing preparedness and targeted responses.
SN - 1101-1262
SN - 1464-360X
ER -