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A tool to enhance antimicrobial stewardship using similarity networks to identify antimicrobial resistance patterns across farms

Scientific reports publica este artículo de investigación

20 de febrero de 2023

Antimicrobial resistance (AMR) is one of the major challenges of the century and should be addressed with a One Health approach. This study aimed to develop a tool that can provide a better understanding of AMR patterns and improve management practices in swine production systems to reduce its spread between farms. We generated similarity networks based on the phenotypic AMR pattern for each farm with information on important bacterial pathogens for swine farming based on the Euclidean distance. We included seven pathogens: Actinobacillus suis, Bordetella bronchiseptica, Escherichia coli, Glaesserella parasuis, Pasteurella multocida, Salmonella spp., and Streptococcus suis; and up to seventeen antibiotics from ten classes. A threshold criterion was developed to reduce the density of the networks and generate communities based on their AMR profiles. A total of 479 farms were included in the study although not all bacteria information was available on each farm. We observed significant differences in the morphology, number of nodes and characteristics of pathogen networks, as well as in the number of communities and susceptibility profiles of the pathogens to different antimicrobial drugs. The methodology presented here could be a useful tool to improve health management, biosecurity measures and prioritize interventions to reduce AMR spread in swine farming




Aguilar-Vega C., Scoglio C., Clavijo MJ., Robbins R., Karriker L., Liu X. y Martinez-Lopez B.




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A tool to enhance antimicrobial stewardship using similarity networks to identify antimicrobial resistance patterns across farms

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A tool to enhance antimicrobial stewardship using similarity networks to identify antimicrobial resistance patterns across farms



Participantes:

Center for Animal Disease Modeling and Surveillance. Department of Medicine and Epidemiology. University of California.

Universidad ComplutenseServicio de Inmunología Viral y Medicina Preventiva (SUAT). Centro de Vigilancia Sanitaria Veterinaria (VISAVET). Universidad Complutense (UCM).

Universidad ComplutenseDepartamento de Sanidad Animal. Facultad de Veterinaria. Universidad Complutense (UCM).

Kansas State UniversityDepartment of Electrical and Computer Engineering. Kansas State University (KSU).

Iowa State UniversityVeterinary Diagnostic and Production Animal Medicine (VDPAM). Iowa State University (ISU).

Pig Improvement Company (PIC).

Computer Science Department. University of California.







Scientific reports
FACTOR YEAR Q
3.800 2023

NLMID: 101563288

PMID: 36804990

ISSN: 2045-2322



TÍTULO: A tool to enhance antimicrobial stewardship using similarity networks to identify antimicrobial resistance patterns across farms


REVISTA: Sci Rep


NUMERACIÓN: 13(1):2931


AÑO: 2023


EDITORIAL: Nature Publishing Group


AUTORES: Aguilar-Vega C., Scoglio C., Clavijo MJ., Robbins R., Karriker L., Liu X. and Martinez-Lopez B.


DOI: https://doi.org/10.1038/s41598-023-29980-4


CITA ESTA PUBLICACIÓN:

Aguilar-Vega C., Scoglio C., Clavijo MJ., Robbins R., Karriker L., Liu X. y Martinez-Lopez B. A tool to enhance antimicrobial stewardship using similarity networks to identify antimicrobial resistance patterns across farms. Scientific reports. 13(1):2931. 2023. (A). ISSN: 2045-2322. DOI: 10.1038/s41598-023-29980-4


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