Qualitative fingerprinting of psychoactive pharmaceuticals, illicit drugs, and related human metabolites in wastewater: A year-long study from Riga, Latvia

废水中精神活性药物、非法药物和相关人体代谢物的定性指纹分析:拉脱维亚里加的一项为期一年的研究

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作者:Ingus Perkons, Laura Elina Tomsone, Veronika Sukajeva, Romans Neilands, Kristina Kokina, Iveta Pugajeva

Abstract

The COVID-19 pandemic has become an unprecedented public health emergency causing immense societal and socio-economic consequences. Multiple studies have outlined that interventions to curb the spread of the virus are likely to have an effect on substance use patterns. In this study, we explored the presence of psychoactive pharmaceuticals, illicit drugs and related human metabolites in 24-h composite wastewater samples that were collected weekly in 2021 from the central WWTP of Riga, Latvia. The analysis was performed via suspect screening approach using three separate high-resolution mass spectrometry (HRMS) workflows, which relied on reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC) and direct infusion HRMS. In total, 39 out of 149 substances were detected throughout the sampling period. These include pharmaceuticals (mainly antiepileptics, antidepressants and antipsychotics), illicit drugs (e.g., MDMA, MDEA, cocaine, etc.) and new psychoactive substances (alpha-PVP). The results were evaluated in relation to COVID-19 incidence rate and the severity of containment and closure policies. For some compounds we observed temporal changes that may be potentially linked to the state of the pandemic. For instance, higher detection rates were observed for several illicit drugs during periods, when restrictions on public events were relaxed. Meanwhile, some psychoactive pharmaceuticals and drugs used to treat upper respiratory tract infections displayed increased prevalence in weeks when the national COVID-19 incidence rates were higher. However, without baseline reference data from previous years, it is difficult to discern how much of the relationships seen are linked to pandemic progression and seasonal variability.

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