Tam T Tran, Adriana Krolicka, Ananda Tiwari, Tarja Pitkänen, Rolf Lood, Ásta Margrét Ásmundsdóttir, Odd-Gunnar Wikmark
{"title":"Antimicrobial resistance in the Nordics: mapping existing surveillance systems and assessing the impact of COVID-19 using regression models.","authors":"Tam T Tran, Adriana Krolicka, Ananda Tiwari, Tarja Pitkänen, Rolf Lood, Ásta Margrét Ásmundsdóttir, Odd-Gunnar Wikmark","doi":"10.1186/s13756-025-01552-3","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Coronavirus disease 2019 (COVID-19) pandemic constituted the largest global health crisis in recent generations. It may also have disrupted the pattern of antimicrobial use (AMU) and subsequently affected the development of antimicrobial resistance (AMR) - a grave human health concern. This study aimed to give an overview of existing AMR surveillance systems and evaluate the impact of COVID-19 on AMU and AMR in the Nordics using data from these systems.</p><p><strong>Methods: </strong>Nordic AMU data (2017-2022) were extracted from national annual reports (for both humans and animals) and the European Surveillance System (TESSy) (for humans only). For humans, AMU was expressed in defined daily dose (DDD) per 1000 inhabitants per day; for animals, it was expressed in kilogram (kg). Nordic human AMR data (2017-2022) were extracted from TESSy. Multilevel linear regression and negative binomial regression models were used to fit the TESSy data. Data between 2017 and 2019 were categorised as the pre-COVID-19 time, while data between 2020 and 2022 were the per-COVID-19 time.</p><p><strong>Results: </strong>Denmark had a remarkably greater AMU in animals (about 10 times greater) than Norway, Sweden, and Finland. Iceland had the highest human AMU, while Sweden had the lowest. Drug categories, countries, and sectors were significant predictors in the model used to fit human AMU. Bacterial species and drug categories were significant predictors in the models used to fit human resistant Gram-negative and Gram-positive bacteria. The COVID-19 time was not a significant predictor in these models. Among the Nordics, Iceland had the lowest number of resistant isolates; however, high human AMU remains a great concern for Iceland.</p><p><strong>Conclusions: </strong>The study provided insight into current existing AMR surveillance systems in the Nordics. It also showed that the COVID-19 pandemic had very little impact on AMU and AMR in theses countries. This implied that strict regulations on AMU as well as well-coordinated national AMR surveillance systems in the Nordics mitigated the development of AMR crisis also during COVID-19 pandemic. However, the Nordics would still benefit further from a standardized AMR surveillance at regional level, which ultimately facilitate timely information sharing and improve our preparedness for and response to future pandemics and/or large-scale outbreaks.</p>","PeriodicalId":7950,"journal":{"name":"Antimicrobial Resistance and Infection Control","volume":"14 1","pages":"55"},"PeriodicalIF":4.8000,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12121021/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Antimicrobial Resistance and Infection Control","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13756-025-01552-3","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Coronavirus disease 2019 (COVID-19) pandemic constituted the largest global health crisis in recent generations. It may also have disrupted the pattern of antimicrobial use (AMU) and subsequently affected the development of antimicrobial resistance (AMR) - a grave human health concern. This study aimed to give an overview of existing AMR surveillance systems and evaluate the impact of COVID-19 on AMU and AMR in the Nordics using data from these systems.
Methods: Nordic AMU data (2017-2022) were extracted from national annual reports (for both humans and animals) and the European Surveillance System (TESSy) (for humans only). For humans, AMU was expressed in defined daily dose (DDD) per 1000 inhabitants per day; for animals, it was expressed in kilogram (kg). Nordic human AMR data (2017-2022) were extracted from TESSy. Multilevel linear regression and negative binomial regression models were used to fit the TESSy data. Data between 2017 and 2019 were categorised as the pre-COVID-19 time, while data between 2020 and 2022 were the per-COVID-19 time.
Results: Denmark had a remarkably greater AMU in animals (about 10 times greater) than Norway, Sweden, and Finland. Iceland had the highest human AMU, while Sweden had the lowest. Drug categories, countries, and sectors were significant predictors in the model used to fit human AMU. Bacterial species and drug categories were significant predictors in the models used to fit human resistant Gram-negative and Gram-positive bacteria. The COVID-19 time was not a significant predictor in these models. Among the Nordics, Iceland had the lowest number of resistant isolates; however, high human AMU remains a great concern for Iceland.
Conclusions: The study provided insight into current existing AMR surveillance systems in the Nordics. It also showed that the COVID-19 pandemic had very little impact on AMU and AMR in theses countries. This implied that strict regulations on AMU as well as well-coordinated national AMR surveillance systems in the Nordics mitigated the development of AMR crisis also during COVID-19 pandemic. However, the Nordics would still benefit further from a standardized AMR surveillance at regional level, which ultimately facilitate timely information sharing and improve our preparedness for and response to future pandemics and/or large-scale outbreaks.
期刊介绍:
Antimicrobial Resistance and Infection Control is a global forum for all those working on the prevention, diagnostic and treatment of health-care associated infections and antimicrobial resistance development in all health-care settings. The journal covers a broad spectrum of preeminent practices and best available data to the top interventional and translational research, and innovative developments in the field of infection control.