Increased antidepressant use during the COVID-19 pandemic: Findings from the Friuli Venezia Giulia region, Italy, 2015-2020

Predicting the potential risks posed by antidepressants as emerging contaminants in fish based on network pharmacological analysis

This study conducted a network pharmacology-based analysis to simultaneously discern a broad spectrum of potential environmental risks and health effects of antidepressants, a common class of pharmaceutical emerging contaminants (PECs) possessing a complex pharmacological profile, and in silico predict the adverse phenotypes potentially occurring in fish associated with exposure to antidepressants and their mixtures under realistic exposure scenarios. Results showed that 24 of the included 39 antidepressants had been detected worldwide in water environment across 50 countries. Using the environmentally realistic exposure scenario for China as an example, the predicted blood concentrations of antidepressant residues that were generated based on the Fish Plasma Model ranged from 37.89 (Alprazolam) to 16,772.05 (Sertraline) ng/L in exposed fish. Hazard-based bioactivity network without regard to concentration data was composed of 148 potential targets and 701 antidepressant-target interactions. After filtering each antidepressant-target interaction node using the predicted drug concentrations in the blood of fish under realistic exposure scenarios in China, an environmental risk-based network was refined and showed that 11 targets, including muscarinic acetylcholine receptor M1, alpha-2B adrenergic receptor, serotonin 2 A receptor, etc. might be modulated by antidepressants at concentrations equal to or below the environmental exposure levels and their mixtures in fish. Environmentally relevant concentrations of antidepressants in water samples from China might perturb the behavior, stress response, phototaxis, and development in exposed fish.

Utilization of antidepressants, anxiolytics, and hypnotics during the COVID-19 pandemic

Since the onset of the COVID-19 pandemic, there have been concerns over the mental health impact of COVID-19. This is a review of the utilization of antidepressants, anxiolytics, and hypnotics since the COVID-19 pandemic was declared on March the 11th 2020. A number of reports so far have been based on large prescription databases for administrative use at the national or regional level, but mainly in high-income countries. We found studies reporting increased prescription rates of antidepressants, anxiolytics, and hypnotics during March 2020, which has been interpreted as hoarding of such medications. In the following months, most studies of antidepressant prescription rates did not display a clear pattern of change compared with prepandemic trends. In later phases of the pandemic small increases in utilization of antidepressants, with higher than predicted prescription rates, have been the most consistent finding, especially in youth. In most high-income countries, there were increasing trends in utilization of antidepressants also before 2020, which needs to be considered when estimating utilization during the pandemic, whereas for anxiolytics and hypnotics, the prepandemic patterns of prescriptions were more varying. Overall, after March 2020 we could not find any distinct changes in the utilization of anxiolytics and hypnotics during the COVID-19 pandemic. Most studies did not contain information about the prevalence of indicated psychiatric disorders in the studied populations. More studies are needed about the long-term effects of COVID-19, particularly regarding utilization of antidepressants. Research relating antidepressant utilization with the prevalence of major depression and anxiety disorders would promote a better understanding of how well antidepressant prescription rates reflect the needs of the population.

Pharmaceutical and Recreational Drug Usage Patterns during and Post COVID-19 Determined by Wastewater-Based Epidemiology

Wastewater-based epidemiology (WBE) was applied to evaluate the consumption trends of pharmaceuticals (i.e., antibiotics, non-steroidal anti-inflammatory drugs, antiepileptics, antihypertensives, and others), as well as recreational drugs (caffeine, alcohol, and nicotine), in Latvia from December 2020 to July 2023. The time period covers both the COVID-19 pandemic and the post-pandemic periods; therefore, the impact of the implemented restrictions and the consequences of the illness in terms of the usage of pharmaceuticals thereon were investigated. Additionally, the seasonality and impact of the seasonal flu and other acute upper respiratory infections were studied. The results revealed that the pandemic impacted the consumption of alcohol, nicotine, and caffeine, as well as several pharmaceuticals, such as antihypertensives, antidepressants, psychiatric drugs, and the painkiller ibuprofen. The findings suggest that the imposed restrictions during the pandemic may have had a negative effect on the population's health and mental well-being. Distinct seasonal trends were discovered in the consumption patterns of caffeine and alcohol, where lower use was observed during the summer. The seasonal consumption trends of pharmaceuticals were discovered in the case of antibiotics, the antiasthmatic drug salbutamol, and the decongestant xylometazoline, where higher consumption occurred during colder seasons.

Impact of the COVID-19 Pandemic on the Use of Antidepressants by Young Adults in the ASL TO4 Regione Piemonte (Italy)

The association between younger age and poorer mental health during the COVID-19 pandemic has been documented. Whether these changes were associated with a change in antidepressant (AD) use is not well understood. This study aimed to estimate the impact of the COVID-19 pandemic on AD use by young adults in the ASL TO4 Regione Piemonte (Italy). The impact of the pandemic on the weekly prevalence of AD users was assessed using interrupted time-series analysis with autoregressive integrated moving average models. A total of 1071 subjects (18-22 years with ≥1 AD dispensation) were included in the study. The observed prevalence was lower than the predicted value for several weeks after the introduction of the lockdown. However, it was consistently higher than the predicted values from week 134. The maximum difference between observed and predicted values (25 subjects per 10,000 young adults) was found at week 170. Changes in AD use were observed in both genders and were more pronounced for selective serotonin reuptake inhibitors. In conclusion, the impact of the COVID-19 pandemic on the mental health of young adults is likely to be significant in the coming years, which may place a future burden on pharmaceutical public health and community health.

Retrospective spatiotemporal study of antidepressants in Slovenian wastewaters

This study utilizes wastewater-based epidemiology (WBE) to evaluate spatiotemporal changes in the consumption of antidepressants before and during the COVID-19 pandemic in Slovenia. Composite 24-h influent wastewater samples (n = 210) were collected from six wastewater treatment plants between summer 2019 and spring 2021. The samples were extracted using 96-well solid-phase extraction and analysed by liquid chromatography-tandem mass spectrometry. The measured concentrations of target antidepressant biomarkers were then converted to population-normalised mass loads (PNMLs), taking into account flow rate and catchment population. Ten biomarkers, including amitriptyline, bupropion, bupropion-OH, citalopram, norcitalopram, normirtazapine, venlafaxine, O-desmethylvenlafaxine, trazodone, and moclobemide, were above the lower limit of quantification and were included in the spatiotemporal temporal assessment. The highest PNMLs were detected for O-desmethylvenlafaxine (mean ± SD: 82.1 ± 21.2 mg/day/1000 inhabitants) and venlafaxine (38.0 ± 10.6 mg/day/1000 inhabitants), followed by citalopram (27.0 ± 10.7 mg/day/1000 inhabitants). In addition, the mean metabolite/parent compound ratios were comparable with other WBE studies indicating consumption rather than direct disposal. Overall, the results indicated significant spatiotemporal variations depending on the location, and the PNMLs of most biomarkers increased during the first wave of the COVID-19 pandemic (spring of 2020). However, no clear spatial patterns were revealed related to the pandemic.

The Role of Medication, Mental Illness, and Social Isolation on the Development of the Fetus in the Context of the COVID-19 Pandemic

As we enter the COVID-19 post-pandemic period, uncertainty surrounds the impact of the varied effects of medications, mental illness, and social isolation on children born during the pandemic. Medications like selective serotonin reuptake inhibitors (SSRIs) and benzodiazepines during pregnancy, coupled with pandemic-induced social isolation, may contribute to anxiety, depression, and behavioral issues in the offspring. Supporting evidence shows SSRIs' influence on brain development, while third-trimester benzodiazepine use may lead to neonatal withdrawal syndrome. Social isolation during the pandemic has also been linked to increased maternal depression and anxiety. This editorial emphasizes the need for increased surveillance in educational settings and early behavioral assessments by pediatricians. Further research is required to understand the long-term effects of maternal SSRIs. This knowledge can aid in timely interventions to protect the well-being of children born during COVID-19.

Learning and happiness during Covid-19 school closure in urban Malaysia

COVID-19 school closure has disrupted education systems globally raising concerns over learning time loss. At the same time, social isolation at home has seen a decline in happiness level among young learners. Understanding the link between cognitive effort and emotional wellbeing is important for post-pandemic learning recovery interventions particularly if there is a feedback loop from happiness to learning. In this context, we use primary survey data collected during the first school closure in urban Malaysia to study the complex association between learning loss and student happiness. Machine learning methods are used to accommodate the multi-dimensional and interaction effects between the covariates that influence this association. Empirically, we find that the most important covariates are student gender, social economic status (SES) proxied by the number of books ownership, time spent on play and religious activity. Based on the results, we develop a conceptual framework of learning continuity by formalizing the importance of investment in emotional wellbeing.