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
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».