ArticleThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale2011
Antimicrobial resistance surveillance systems: Are potential biases taken into account?
Article in The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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.
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Who cites it
13 citing papers in PubMed.
- Trial
- Network-based characterization of latent co-testing patterns in antimicrobial susceptibility testing.iScience · 2026Article
- Advancing AMR Surveillance: Confluence of One Health and Big Data Integration : Converging One Health and Big Data for AMR.EcoHealth · 2025Review
- Substandard and falsified antibiotics are associated with antimicrobial resistance: a retrospective country-level analysis.BMJ global health · 2025Article
- Bayesian estimation of the prevalence of antimicrobial resistance: a mathematical modelling study.The Journal of antimicrobial chemotherapy · 2024Article
- Strengthening antimicrobial resistance surveillance systems: a scoping review.BMC infectious diseases · 2023Article
- Population-based study ofJournal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2023Article
- Surveillance of antimicrobial resistance in low- and middle-income countries: a scattered picture.Antimicrobial resistance and infection control · 2021Review
- Antimicrobial resistance among uropathogens in the Asia-Pacific region: a systematic review.JAC-antimicrobial resistance · 2021Review
- High Burden of Extended-Spectrum β-Lactamase-ProducingThe American journal of tropical medicine and hygiene · 2019Article
- Harnessing alternative sources of antimicrobial resistance data to support surveillance in low-resource settings.The Journal of antimicrobial chemotherapy · 2019Review
- Burden of community-onset bloodstream infections, Western Interior, British Columbia, Canada.Epidemiology and infection · 2016Article
- Laboratory-based nationwide surveillance of antimicrobial resistance in Ghana.Infection and drug resistance · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe validity of surveillance systems has rarely been a topic of investigation.
objectiveTo assess potential biases that may influence the validity of contemporary antimicrobial-resistant (AMR) pathogen surveillance systems.
methodsIn 2008, reports of laboratory-based AMR surveillance systems were identified by searching Medline. Surveillance systems were appraised for six different types of bias. Scores were assigned as '2' (good), '1' (fair) and '0' (poor) for each bias.
resultsA total of 22 surveillance systems were included. All studies used appropriate denominator data and case definitions (score of 2). Most (n=18) studies adequately protected against case ascertainment bias (score = 2), with three studies and one study scoring 1 and 0, respectively. Only four studies were deemed to be free of significant sampling bias (score = 2), with 17 studies classified as fair, and one as poor. Eight studies had explicitly removed duplicates (score = 2). Seven studies removed duplicates, but lacked adequate definitions (score = 1). Seven studies did not report duplicate removal (score = 0). Eighteen of the studies were considered to have good laboratory methodology, three had some concerns (score = 1), and one was considered to be poor (score = 0).
conclusionContemporary AMR surveillance systems commonly have methodological limitations with respect to sampling and multiple counting and, to a lesser degree, case ascertainment and laboratory practices. The potential for bias should be considered in the interpretation of surveillance data.
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