Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.
Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT), Data Science Institute, Hasselt University, Hasselt, Belgium.
J Antimicrob Chemother. 2021 Jul 26;76(12 Suppl 2):ii68-ii78. doi: 10.1093/jac/dkab179.
Surveillance of antibiotic consumption in the community is of utmost importance to inform and evaluate control strategies. Data on two decades of antibiotic consumption in the community were collected from 30 EU/European Economic Area (EEA) countries. This article reviews temporal trends and the presence of abrupt changes in subgroups of relevance in antimicrobial stewardship.
For the period 1997-2017, data on yearly antibiotic consumption in the community, aggregated at the level of the active substance, were collected using the WHO ATC classification and expressed in DDD (ATC/DDD index 2019) per 1000 inhabitants per day. We applied a range of non-linear mixed models to assess the presence of changes in the consumption of antibacterials for systemic use (ATC group J01) and eight antibiotic subgroups.
For the majority of the studied groups, a country-specific change-point model provided the best fit. Depending on the antibiotic group/subgroup and on the country, change-points were spread out between 2000 and 2013.
Due to the heterogeneity in antibiotic consumption in the community across EU/EEA countries, a country-specific change-point model provided the better fit. Given the limitations of this model, our recommendation for the included countries is to carefully interpret the country-specific results presented in this article and to use the tutorial included in this series to conduct their own change-point analysis when evaluating the impact of changes in regulations, public awareness campaigns, and other national interventions to improve antibiotic consumption in the community.
社区抗生素使用监测对于提供信息和评估控制策略至关重要。本文收集了来自 30 个欧盟/欧洲经济区(EEA)国家的 20 年来社区抗生素使用数据,回顾了在抗菌药物管理中具有重要意义的亚组的时间趋势和突然变化的情况。
在 1997-2017 年期间,使用世界卫生组织(WHO)ATC 分类法收集了社区中每年抗生素使用的数据,按活性物质汇总,以 DDD(2019 年 ATC/DDD 指数)表示,每 1000 居民每天使用量。我们应用了一系列非线性混合模型来评估全身用抗菌药物(ATC 组 J01)和 8 个抗生素亚组使用量的变化情况。
对于大多数研究组,特定于国家的变化点模型提供了最佳拟合。根据抗生素组/亚组和国家的不同,变化点分布在 2000 年至 2013 年之间。
由于欧盟/EEA 国家社区抗生素使用存在异质性,特定于国家的变化点模型提供了更好的拟合。鉴于该模型的局限性,我们建议纳入本研究的国家仔细解释本文中呈现的特定于国家的结果,并在评估法规变化、公众意识运动和其他旨在改善社区抗生素使用的国家干预措施的影响时,使用本系列中包含的教程来进行自己的变化点分析。