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Trends in Medication Use Among Young Adults and the Covid-19 Pandemic Effect
Meital Zur1,2, Avishai M Tsur2,3,4,5, Limor Friedensohn2,3,6
1Pharmacoepidemiology Research Lab, Institute for Drug Research, School of Pharmacy, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
Introduction:
The COVID-19 pandemic caused unprecedented disruptions in healthcare delivery, and changes in medication utilization patterns. While previous studies examined specific therapeutic classes or populations, there is limited longitudinal evidence on medication trends among young adults throughout and beyond the pandemic.
Aim:
To analyze trends in medication dispensation before, during, and after the COVID-19 pandemic among young adults.
Methods:
We conducted a population-based, retrospective cohort study including active-duty Israeli Defense Forces personnel between January 2017 and August 2023. Monthly dispensing rates per 1000 persons were analyzed using an interrupted time series (ITS) design, implemented via generalized linear models with log link and population offsets. Models included linear time trends, month fixed effects to account for seasonality, and negative binomial fallback for overdispersion. Pre-pandemic data (January 2017-March 2020) were used to estimate baseline trends, from which counterfactual predictions were generated for March 2020-August 2022. Goodness-of-fit was evaluated with RMSE and MAPE.
Results:
Pre-pandemic trends varied across therapeutic groups. Adrenergic inhalants (IRR 1.008, 95% CI 1.004-1.011, p = 0.0001), antidiarrheals (IRR 1.005, 95% CI 1.001-1.008, p = 0.004), and ADHD medications (IRR 1.024, 95% CI 1.020-1.027, p < 0.001) exhibited significant upward slopes, whereas antibacterials, antidepressants and hormonal contraceptives showed no significant baseline trend. Seasonality was significant for all groups (p < 0.001). During the pandemic, cumulative differences revealed excesses for adrenergic inhalants (+93.98 per 1000), antidepressants (+87.03), and hormonal contraceptives (+679.21), alongside deficits for antibacterials (-201.99), antidiarrheals (-112.89), and ADHD medications (-294.69).
Conclusions:
Medication usage patterns can be classified into three classes: medications affected by the pandemic due to the inciting pathogen, disease symptoms, or pandemic social disruption; medications unaffected by the pandemic, affected by global disease trends; and medications with a trend change whose relation to the pandemic is unclear. These findings offer a novel framework for anticipating and managing medication needs in future pandemics.
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