Prevalence, main serovars, and antimicrobial resistance profiles of Non-typhoidal Salmonella in poultry samples from the Americas: A systematic review and meta-analysis
Bibliographic record
Abstract
Poultry and poultry-derived products such as meat and eggs are among the main sources of non-typhoidal Salmonella (NTS) transmission to the human. Therefore, we performed a systematic review and used random-effects meta-analyses to 1) estimate the prevalence of NTS in poultry samples from birds, products and subproducts, and environmental samples, 2) examine the diversity and frequency of their serovars, and 3) estimate the prevalence and profiles of antimicrobial resistance (AMR) in NTS isolates reported in studies from the Americas. We included 157 studies from 15 countries comprising 261,408 poultry samples and estimated an overall pooled prevalence of 17.9% (95% CI: 10.8–26.3) in birds, 21.8% (17.7–26.1) in products and subproducts, and 29.5% (24.2–35.1) in environmental samples. At the national level, the prevalence of NTS was heterogenous across countries with the highest values in Mexico, the USA, and Canada. In total, 131 serovars were identified from 13,388 isolates, Heidelberg, Kentucky, Enteritidis, and Typhimurium were the most prevalent in the overall top 10 ranking (range 6.5–20.8%). At the national level, Enteritidis and Typhimurium were identified in most of the countries, though with national differences in their ranks. The prevalence of AMR increased from 24.1% for 1 antibiotic, to 36.2% for 2-3 antibiotics, and 49.6% for ≥ 4 antibiotics. Kentucky, Heidelberg, Typhimurium, and Enteritidis were the serovars with the highest prevalence of AMR and tetracycline, ampicillin, streptomycin, ceftiofur, and amoxicillin-clavulanic acid were the top five antibiotics to which NTS isolates were resistant. In conclusion, NTS was distributed through the avian production chain with high and heterogenous values of prevalence in poultry samples. Besides, there were distinctive patterns of serovars distribution across countries and an alarming prevalence of AMR among zoonotic serovars.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.031 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".