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Spatial Exposure of Agricultural Antimicrobial Resistance in Relation to Free-Ranging Domestic Chicken Movement Patterns among Agricultural Communities in Ecuador

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  • 1 Illinois Natural History Survey, Prairie Research Institute, University of Illinois Urbana-Champaign, Champaign, Illinois;
  • | 2 Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan;
  • | 3 Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan;
  • | 4 Institute of Microbiology, Universidad San Francisco de Quito, Quito, Ecuador;
  • | 5 School for Environment and Sustainability, University of Michigan, Ann Arbor, Michigan;
  • | 6 Department of Statistics, School of Information & Computer Science, University of California, Irvine, California;
  • | 7 Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan

ABSTRACT

The use of antimicrobial growth promoters in chicken farming has been commonly associated with high levels of antimicrobial resistance (AMR) in humans. Most of this work, however, has been focused on intensive large-scale operations. Intensive small-scale farming that regularly uses antibiotics is increasing worldwide and has different exposure pathways compared with large-scale farming, most notably the spatial connection between chickens and households. In these communities, free-ranging backyard chickens (not fed antibiotics) can roam freely, whereas broiler chickens (fed antibiotics) are reared in the same husbandry environment but confined to coops. We conducted an observational field study to better understand the spatial distribution of AMR in communities that conduct small-scale farming in northwestern Ecuador. We analyzed phenotypic resistance of Escherichia coli sampled from humans and backyard chickens to 12 antibiotics in relation to the distance to the nearest small-scale farming operation within their community. We did not find a statistically significant relationship between the distance of a household to small-scale farming and antibiotic-resistant E. coli isolated from chicken or human samples. To help explain this result, we monitored the movement of backyard chickens and found they were on average 17 m (min–max: 0–59 m) from their household at any given time. These backyard chickens on average ranged further than the average distance from any study household to its closest neighbor. This level of connectivity provides a viable mechanism for the spread of antimicrobial-resistant bacteria and genes throughout the community.

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Author Notes

Address correspondence to Joseph N. S. Eisenberg, Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109. E-mail: jnse@umich.edu

Disclosure: The authors assert that all procedures contributing to this work comply with the ethical standards reviewed and approved by the University of Michigan Institutional Review Board (HUM00121496) and the Universidad San Francisco de Quito Bioethics Committee (MSP-SDM-10-2013-1019-O). The animal use protocol was approved by the Institutional Animal Care & Use Committee at the University of Michigan (protocol: PRO00006200)

Financial support: This project was funded through the Dow Sustainability Fellowship and the Integrated Training in Microbial Systems program at the University of Michigan.

Authors’ addresses: Hayden D. Hedman, School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, E-mail: hedmanh@umich.edu. Lixin Zhang, Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, and Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, E-mail: lxzhang@epi.msu.edu. Gabriel Trueba, Dayana L. Vinueza Rivera, Rafael A. Zurita Herrera, Jaun Jose Villacis Barrazueta, and Gabriela I. Gavilanes Rodriguez, Institute of Microbiology, Universidad San Francisco de Quito, Quito, Ecuador, E-mails: gtrueba@usfq.edu.ec, dayana.vinueza@hotmail.com, rafazurita1992@gmail.com, juanjovillacis@me.com, and gaby_igr@hotmail.com. Bilal Butt and Johannes Foufopoulos, School of Natural Resource, University of Michigan, Ann Arbor, MI, E-mails: bilalb@umich.edu and jfoufop@umich.edu. Veronica J. Berrocal, Department of Statistics, School of Information and Computer Science, University of California Irvine, Irvine, CA, E-mail: vberroca@uci.edu. Joseph N. S. Eisenberg, Department of Epidemiology, University of Michigan, Ann Arbor, MI, E-mail: jnse@umich.edu.

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