Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 463

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Animal antibiotic use has an early but important impact on the emergence of antibiotic resistance in human commensal bacteria

Open access
Smith, David L., Harris, Anthony D., Johnson, Judith A., Silbergeld, Ellen K., Morris, J. Glenn·2002·Proceedings of the National Academy of Sciences

Abstract

Antibiotic use is known to promote the development of antibiotic resistance, but substantial controversy exists about the impact of agricultural antibiotic use (AAU) on the subsequent emergence of antibiotic-resistant bacteria among humans. AAU for animal growth promotion or for treatment or control of animal diseases generates reservoirs of antibiotic-resistant (AR) bacteria that contaminate animal food products. Mathematical models are an important tool for understanding the potential medical consequences of this increased exposure. We have developed a mathematical model to evaluate factors affecting the prevalence of human commensal AR bacteria that cause opportunistic infections (e.g., enterococci). Our analysis suggests that AAU hastens the appearance of AR bacteria in humans. Our model indicates that the greatest impact occurs very early in the emergence of resistance, when AR bacteria are rare, possibly below the detection limits of current surveillance methods.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.082188899

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

Metadata

Authors
Smith, D. L., Harris, A. D., Johnson, J. A., Silbergeld, E. K., & Morris, J. G.
Venue
Proceedings of the National Academy of Sciences
Published
2002-04-23
Volume
99
Issue
9
Pages
6434-6439
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2109054898
Cited by
463
References
2
FWCI
14.71
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.