METHODS: To estimate the causal effect of the pandemic an interrupted time series analysis was conducted. Data of antidepressant drugs monthly dispensed in community pharmacies between Jan-2010 and Dec-2021 were provided by the regional Health Administration. Anti-Parkinson dopaminergic agents and statins, theoretically not influenced by COVID-19 pandemics, were used as comparator series. The number of packages was converted into defined daily doses and presented as defined daily doses/1000 inhabitants/day. A Bayesian structural time-series model with CausalImpact on R/RStudio was used to predict the counterfactual. Analyses with different geographical granularity (9 sub-regions and 78 municipalities) were performed.
RESULTS: When compared to counterfactual, regional consumption non-significantly increased after the pandemic declaration, with a relative effect of + 1.30% [95%CI -1.6%:4.2%]. When increasing the granularity, differences appeared between sub-region with significant increases in Baixo Mondego + 6.5% [1.4%:11.0%], Guarda + 4.4% [1.1%:7.7%] or Cova da Beira + 4.1% [0.17%:8.3%], but non-significant variation in the remaining 6 sub-regions. Differences are more obvious at municipality level, ranging from increases of + 37.00% [32.00%:42.00%] to decreases of -11.00% [-17.00%:-4.20%]. Relative impact positively correlated with percentage of elderly in the municipality (r = 0.301; p = 0.007), and negatively with population density (r=-0.243; p = 0.032). No other predicting variables were found.
CONCLUSIONS: Antidepressant consumption suffered very slight variations at regional level after the COVID-19 pandemic declaration. Analysis with higher granularity allowed identifying municipalities with higher impact (increase or decrease). The absence of clear association patterns suggests other causal hypotheses of the differences.
方法:为了估计大流行的因果效应,进行了中断时间序列分析。2010年1月至2021年12月期间,社区药房每月分发的抗抑郁药物数据由地区卫生管理局提供。抗帕金森病多巴胺能药物和他汀类药物,理论上不受COVID-19大流行的影响,用作比较器系列。将包装的数量转换成规定的每日剂量,并表示为规定的每日剂量/1000居民/天。使用对R/RStudio具有因果关系的贝叶斯结构时间序列模型来预测反事实。进行了不同地理粒度(9个子区域和78个城市)的分析。
结果:与反事实相比,大流行宣布后,区域消费没有显着增加,相对效果为+1.30%[95CI-1.6%:4.2%]。当增加粒度时,亚区域之间出现差异,白沙蒙德戈+6.5%[1.4%:11.0%]显著增加,Guarda+4.4%[1.1%:7.7%]或CovadaBeira+4.1%[0.17%:8.3%],但其余6个子区域的变异不显著。在直辖市一级的差异更加明显,从增加37.00%[32.00%:42.00%]到减少-11.00%[-17.00%:-4.20%]不等。相对影响与城市老年人百分比呈正相关(r=0.301;p=0.007),与人口密度呈负相关(r=-0.243;p=0.032)。没有发现其他预测变量。
结论:在COVID-19大流行宣布后,抗抑郁药的消费在地区水平上差异很小。具有较高粒度的分析允许识别具有较高影响(增加或减少)的城市。缺乏明确的关联模式表明了差异的其他因果假设。