Abstract：
OBJECTIVE: To evaluate the impact of the pandemic on the consumption of antidepressive agents in Central Portugal.
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.
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.
摘要：
目的：评估大流行对葡萄牙中部抗抑郁药消费的影响。
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。
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。
