Antibiotic Resistance Spread and Resistance Control Options. Estonian Experience
Notice bibliographique
Résumé
Abstract Antibiotic resistance refers to the ability of microbes to grow in the presence of an antibiotic that would have originally killed or inhibited the growth of these microorganisms. Microorganisms resistant to antibiotics exist in humans, animals and in the environment. Resistant microbes can spread from animals to humans and vice versa either through direct contact or through the environment. Resistant bacteria survive in the body during a course of antibiotics and continue to multiply. Treatment of antibiotic-resistant infections takes more time, costs more, and sometimes may prove impossible. The aim of the AMR-RITA project was to develop recommendations based on scientific evidence including the “One Health” principle for the formulation of policy on antibiotic resistance. In order to achieve the goal, the role of human behaviour, human and animal medicine, and the environment was implicated in the development of antibiotic resistance. The evaluation of the resistance spread routes, risks and levels, and the possible measures to control the spread of antibiotic resistance were identified. Topics related to antibiotic resistance were analysed in medicine, veterinary medicine and environment subsections. Existing data were combined with new data to assess the transmission routes and mechanisms of antibiotic resistance. For this purpose, samples were collected from people, animals, food, and the environment. The analysis of the samples focused on the main resistent organisms, resistance genes and antibiotic residues. As a result of the study, we conclude that the use of antibiotics in Estonia is generally low compared to other European countries. However, there are bottlenecks that concern both human and veterinary medicine. In both cases, we admit that for some diagnoses there were no treatment guidelines and antibiotics were used for the wrong indications. The lack of specialists of clinical microbiology is a problem in Estonain hospitals. For example, many hospitals lack an infection control specialist. The major worrying trends are the unwarranted use of broad-spectrum antibiotics in humans and the high use of antibiotics critical for human medicine (cephalosporins, quinolones) in the teratment of animals. If more antibiotics are being used, resistance will also spread. We found that those cattle farms that use more cephalosporins also have higher levels of resistance (ESBL-mediated resistance). It also turned out that genetically close clusters of bacteria are often shared by humans and animals. This is evidence of a transfer of resistance between species. However, such transfer occurs slowly, and we did not detect any transfer events in the recent years. Antibiotic residues, just like other drug residues, can reach the environment. The use of slurry and composted sewage sludge as fertilizer are the main pathways. We detected fluroquinolones and tetracyclines in comparable concentrations in slurry and uncomposted sewage sludge. Composting reduces the content of drug residues, and the efficiency of the process depends on the technology used. In addition to antibiotic residues, we also determined some other drug residues accumulating in the environment. High levels of diclofenac and carbamazepine in surface water are a special concern. These are medicines for human use only, so they reach the environment through sewage treatment plants. Based on the results obtained during the research, we propose a series of evidence-based recommendations to the state for the formulation of antimicrobial resistance policy. We propose that Estonia needs sustainable AMR surveillance institution, which (1) continuously collects and analyses data on the use of antimicrobials and antimicrobial resistance and provides regular feedback to relevant institutions (state, health and research institutions), (2) assesses the reliability of the data and ensures carrying out additional and confirming studies, (3) coordinates the activities of national and international research and monitoring networks and projects. We recommend creation of a competence centre that would deal with the topic of AMR across all fields. This should also include funding for research.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».