Antibiotic Resistance Spread and Resistance Control Options. Estonian Experience
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".