MétaCan
Menu
Back to cohort
Record W4409896448 · doi:10.3390/wild2020014

Anthropogenic Impact and Antimicrobial Resistance Occurrence in South American Wild Animals: A Systematic Review and Meta-Analysis

2025· review· en· W4409896448 on OpenAlexaff
Manuel Pérez Maldonado, Constanza Urzúa‐Encina, Naomi Ariyama, Patricio Retamal

Bibliographic record

VenueWild · 2025
Typereview
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMeta-analysisAntimicrobialAntibiotic resistanceResistance (ecology)BiologyGeographyEcologyMedicineMicrobiologyAntibioticsInternal medicine

Abstract

fetched live from OpenAlex

Antimicrobial resistance (AMR) is a significant global challenge that affects environmental, animal, and human health, with reports of antimicrobial-resistant bacteria and antimicrobial resistance genes becoming increasingly common across these domains. This study aimed to systematically review and compare the occurrence of AMR in bacterial isolates from wild animals in South America, focusing on environments with varying levels of anthropogenic impact. Half of the countries in South America documented AMR in wild animals at least once. Most studies focused on specific animal classes, particularly Aves and Mammalia, with a notable emphasis on the orders Chiroptera and Rodentia, as well as the bacterial species Escherichia coli and Salmonella enterica. Subgroup meta-analyses revealed that, for most antimicrobials, the proportion of AMR was significantly higher in environments with a high anthropogenic impact compared to those with a low anthropogenic impact. However, there were no significant differences between the two types of environments for some antimicrobials. Interestingly, certain beta-lactams showed a higher proportion of AMR in environments with low anthropogenic impact. These findings raise important questions regarding the origins and spread of AMR in wild animals, underscoring the necessity for further research to understand the dynamics of AMR in areas with varying levels of human intervention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.789
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0130.002
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.061
GPT teacher head0.408
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueWildSame topicZoonotic diseases and public healthFrench-language works237,207