Most European countries will miss EU targets on antibacterial use by 2030: historical analysis of European and OECD countries, comparison of community and hospital sectors and forecast to 2040
Bibliographic record
Abstract
The rise of bacterial resistance threatens the treatment of infections and is closely linked to the consumption of antibacterial drugs. The EU's 'One Health' approach aims to address this issue by requiring Member States to reduce consumption by 20% by 2030. This study analyses antibacterial consumption trends in the total care of European and non-European OECD countries, compares the community and hospital sector, uses ARIMA modelling and correlation analysis to provide long-term forecasts, assesses patterns of consumption and evaluates whether current trends are in line with the EU target. Projections to 2040 show increases for Spain (+36.6%; 30.7 DID), Greece (+31.4%; 37.5 DID), Czechia (+29.7%; 19.4 DID), Bulgaria (+28.3%; 33. 7 DID), Malta (+26.5%; 28.8 DID), Denmark (+25.7%; 19.8 DID), Croatia (+17.4%; 24.9 DID), Italy (+13.7%; 26.3 DID), Germany (+7.6%; 12.6 DID), Australia (+12.4%, 18.2 DID), Canada (+8.0%, 14.8 DID), Chile (+90.1%, 66.7 DID), Costa Rica (+0.4%, 19.7 DID), Japan (+22.7%, 12.8 DID) and Korea (+24.3%, 31.9 DID). Declines are forecast for Belgium (-0.5%; 20.5 DID), Romania (-0.6%; 27.2 DID), Cyprus (-1.0%; 33.2 DID), Luxembourg (-2.2%; 19.8 DID), Norway (-3.4%; 15.1 DID), Latvia (-5.5%; 14.1 DID), Lithuania (-6.4%; 17.5 DID), the Netherlands (-8.4%; 8. 8 DID), Portugal (-10.6%; 16.1 DID), Estonia (-12.1%; 11.2 DID), Slovakia (-16.1%; 16.8 DID), France (-17.7%; 19.8 DID), Hungary (-20.4%; 11.3 DID), Slovenia (-21.9%; 10.5 DID), Finland (-24.8%; 9.7 DID), Iceland (-24.9%; 13.9 DID), Sweden (-30.4%; 7.0 DID) and Israel (-70.7%, 4.7 DID). A significant positive correlation was found between current versus projected consumption levels and changes, highlighting stable prescribing patterns in many countries. Northern and Central Europe maintain low levels of consumption with decreasing trends, whereas Latin America, Eastern and Southern Europe show higher levels with projected increases. Western Europe and Asia shows a mixed pattern, with varying trends of increase and decrease. Alarmingly, only Sweden is projected to meet the 20% reduction target by 2030. Even in the best-case scenario, only a proportion of European countries are projected to meet the target, including Austria, Belgium, Croatia, Cyprus, Finland, France, Greece, Hungary, Italy, Iceland, Lithuania, Luxembourg, Latvia, Portugal, Slovenia, Slovakia and Spain, while 11 countries show no potential for a successful reduction. The reliability of the projections is considered good to moderate. Divergent trends between the community and hospital sectors further complicate the assessment of progress and underline the need for targeted interventions. Current trends suggest that the EU targets are unlikely to be met, highlighting the urgent need to strengthen stewardship programmes. Further research is needed to address other objectives of the 'One Health' approach, including the use of classes of antibacterial drugs and the development of bacterial resistance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".