Bridging the fields of wastewater-based epidemiology with classical epidemiology

摘要

Wastewater-based epidemiology (WBE) is a novel approach able to provide estimates of illicit drugs use in a population through the chemical analysis of specific urinary metabolites in urban wastewater. It was demonstrated over the last years that WBE results can complement the conventional approaches used in drug epidemiology to help facing a complex phenomenon such as drug abuse. More recently WBE has been considered as a promising tool to monitor the use of new psycoactive substances (NPS). The potential of using these two approached together seems enormous. Wastewater analysis is able to produce objective, near-real-time estimates of drug use in a defined population, and provides an excellent means of quantifying changes in drug-use over time. It can give timely information and is extremely adaptable since experiments can be designed to study drug use in a specific area or to compare the use between different areas during defined periods of the year. On the other side, traditional epidemiological indicators can provide much more detailed information about patterns of use (e.g. the frequency and mode of use) of a substance and characteristics of the user populations, including the potential harms (e.g. health risks) on individuals. Few attempts have been made to date to compare drug use estimates obtained through WBE and traditional epidemiological data, but they confirmed the high complementary characteristics of these different approaches. In view of these promising results, WBE will be tested to provide and complement other information in the field of drug epidemiology such as estimation of market size, evaluation of the presence of dumping in a defined area and outcome measurements. WBE is a new, multidisciplinary field of investigation which requires a high degree of collaboration with drug epidemiologists and stakeholders from public health sector, addiction and prevention institutions in order to improve the comparability of approaches and optimize their complementary characteristics.