Evidence map›Paper›PMID 33139558›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

The role of "spillover" in antibiotic resistance.

Scott W Olesen, Marc Lipsitch, Yonatan H Grad

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

  1. Trial
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  7. Gut Resistome of Preschool Children After Prolonged Mass Azithromycin Distribution: A Cluster-randomized Trial.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
    Trial
  8. Article
  9. Article
  10. Genomic surveillance ofMicrobial genomics · 2026
    Article
  11. Article
  12. Institutional spillover effects of antimicrobial use on antimicrobial resistance andAntimicrobial stewardship & healthcare epidemiology : ASHE · 2026
    Article
  13. Article
  14. Review
  15. Article
  16. Article
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  18. Article
  19. Wastewater-Based Surveillance of Antimicrobial Resistance in Niger: An Exploratory Study.The American journal of tropical medicine and hygiene · 2023
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Scott W OlesenDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115.ORCID 0000-0001-5400-4945
Marc LipsitchDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115.
Yonatan H GradDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115; ygrad@hsph.harvard.edu.ORCID 0000-0001-5646-1314

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
Epidemiology of Infectious Diseases and BiodefenseT32AI007535 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI GRAD, YONATAN H, MURRAY, MEGAN B · 1998 to 2025
$4.8M
NIAID NIH HHS T32 AI007535NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

Antibiotic use is a key driver of antibiotic resistance. Understanding the quantitative association between antibiotic use and resulting resistance is important for predicting future rates of antibiotic resistance and for designing antibiotic stewardship policy. However, the use-resistance association is complicated by "spillover," in which one population's level of antibiotic use affects another population's level of resistance via the transmission of bacteria between those populations. Spillover is known to have effects at the level of families and hospitals, but it is unclear if spillover is relevant at larger scales. We used mathematical modeling and analysis of observational data to address this question. First, we used dynamical models of antibiotic resistance to predict the effects of spillover. Whereas populations completely isolated from one another do not experience any spillover, we found that if even 1% of interactions are between populations, then spillover may have large consequences: The effect of a change in antibiotic use in one population on antibiotic resistance in that population could be reduced by as much as 50%. Then, we quantified spillover in observational antibiotic use and resistance data from US states and European countries for three pathogen-antibiotic combinations, finding that increased interactions between populations were associated with smaller differences in antibiotic resistance between those populations. Thus, spillover may have an important impact at the level of states and countries, which has ramifications for predicting the future of antibiotic resistance, designing antibiotic resistance stewardship policy, and interpreting stewardship interventions.

Indexed as

Anti-Bacterial AgentsAntimicrobial StewardshipBacteriaCross-Sectional StudiesDrug Resistance, BacterialDrug Resistance, MicrobialEuropeHospitalsHumansStreptococcus pneumoniaeUnited StatesAnti-Bacterial Agentsantibiotic resistanceantibiotic stewardshipEscherichia coliStreptococcus pneumoniae

Identifiers

PMID33139558
PMCPMC7682407

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.