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. 2016 Jul 8;11(7):e0158515.
doi: 10.1371/journal.pone.0158515. eCollection 2016.

Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches

Affiliations

Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches

Alison E Mather et al. PLoS One. .

Abstract

Antimicrobial resistance (AMR) surveillance systems are generally not specifically designed to detect emerging resistances and usually focus primarily on resistance to individual drugs. Evaluating the diversity of resistance, using ecological metrics, allows the assessment of sampling protocols with regard to the detection of rare phenotypes, comprising combinations of resistances. Surveillance data of phenotypic AMR of Canadian poultry Salmonella Heidelberg and swine Salmonella Typhimurium var. 5- were used to contrast active (representative isolates derived from healthy animals) and passive (diagnostic isolates) surveillance and assess their suitability for detecting emerging resistance patterns. Although in both datasets the prevalences of resistance to individual antimicrobials were not significantly different between the two surveillance systems, analysis of the diversity of entire resistance phenotypes demonstrated that passive surveillance of diagnostic isolates detected more unique phenotypes. Whilst the most appropriate surveillance method will depend on the relevant objectives, under the conditions of this study, passive surveillance of diagnostic isolates was more effective for the detection of rare and therefore potentially emerging resistance phenotypes.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Observed ecological diversities of the swine S. Typhimurium var. 5- AMR profiles for all values of the q parameter, including Species richness [SR], Shannon entropy [SE], Simpson diversity [SD], Berger-Parker [BP] for passive surveillance (red) and active surveillance (black) isolates with confidence intervals (dotted lines) for the passive surveillance sample generated by subsampling to the size of the active surveillance sample.
Fig 2
Fig 2. Observed ecological diversities of the poultry S. Heidelberg AMR profiles for all values of the q parameter, including Species richness [SR], Shannon entropy [SE], Simpson diversity [SD], Berger-Parker [BP] for passive surveillance (red) and active surveillance (black) isolates with confidence intervals (dotted lines) for the active surveillance sample generated by subsampling to the size of the passive surveillance sample.

References

    1. Hawkey PM (2008) The growing burden of antimicrobial resistance. J Antimicrob Chemother 62 Suppl 1: i1–9. 10.1093/jac/dkn241 - DOI - PubMed
    1. Hall BG, Barlow M (2004) Evolution of the serine beta-lactamases: past, present and future. Drug Resist Updat 7: 111–123. - PubMed
    1. Anderson RM (1999) The pandemic of antibiotic resistance. Nat Med 5: 147–149. - PubMed
    1. Bax R, Bywater R, Cornaglia G, Goossens H, Hunter P, et al. (2001) Surveillance of antimicrobial resistance—what, how and whither? Clin Microbiol Infect 7: 316–325. - PubMed
    1. Aarestrup FM (2004) Monitoring of antimicrobial resistance among food animals: principles and limitations. J Vet Med B Infect Dis Vet Public Health 51: 380–388. - PubMed

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