Advancing surveillance of antimicrobial resistance: Summary of the 2015 CIDSC Report
Bibliographic record
Abstract
Background: Antimicrobials are essential for the treatment and control of infectious diseases and therefore, the development and spread of antimicrobial resistance (AMR) is a global health concern.It is recognized that robust AMR surveillance is necessary; however, current gaps in national surveillance programs need to be addressed to enable better evidence-informed program and policy decisions.Objective: To describe how an AMR Surveillance Task Group prioritized national AMR surveillance data requirements for high priority AMR organisms for human health in Canada and made recommendations on addressing the current data gaps.Methods: The 2015 AMR Surveillance Task Group examined the data requirements for previously identified first priority organisms and assessed whether the current system met, partially met or did not meet these requirements.Information was summarized into synopsis tables and a ranking process was used to prioritize the data requirements and develop specific recommendations to address the gaps.Results: First priority organisms identified for AMR surveillance are: Clostridium difficile, Extended-spectrum β-lactamase-producing organisms, Carbapenem-resistant organisms (Acinetobacter + Enterobacteriaceae species), Enterococcus species, Neisseria gonorrhoeae, Streptococcus pyogenes and S. pneumonaea, Salmonella species, Staphylococcus aureus, Mycobacterium tuberculosis and Campylobacter species.For these organisms, there were 19 high priority data requirements identified: 10 of these requirements were met by the current surveillance systems, seven were partially met and two were unmet.For the two high priority data metrics in the community setting, the Task Group recommended conducting a point-prevalence community-based study (i.e., every five years) to follow infection rates of C. difficile infection, and community level antibiogram data on an annual basis for susceptibility data for Enterobacteriaceae species (E. coli and Klebsiella) causing genito-urinary infections.There were eight medium priority data requirements identified: one requirement was met by the current surveillance system, five were partially met and two were unmet.The medium priority unmet data requirements included susceptibility of infection isolates for C. difficile (diarrheal disease) and infection rates for Enterobacteriaceae species causing genito-urinary tract infections in community settings.It was noted that the feasibility of obtaining this medium priority data in the community setting was low.The Task Group identified bloodstream infections as the top priority site of infection for AMR surveillance in the health care setting given the high morbidity and mortality associated with bloodstream infections.The importance of collecting susceptibility data on N. gonorrhoeae in the community was underscored given the rise in resistance and that the current surveillance system only partially collects this data.The Task Group recommended that a review of the national AMR surveillance data requirement priorities should occur on an ongoing basis and when new issues emerge.Conclusion: While current national surveillance programs either capture or partially capture many of the identified data requirements for first priority organisms, several gaps still remain, especially in community settings.A national review of the recommendations of the Task Group is underway.
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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 | 0.056 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".