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Article

Investigation of Incidents and Trends of Antimicrobial Resistance in Foodborne Pathogens in Eight Countries from Historical Sample Data

1
Department of Chemical Engineering, Villanova University, Villanova, PA 19085, USA
2
Department of Health, Nutrition & Exercise Sciences, Immaculata University, Immaculata, PA 19345, USA
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(2), 472; https://doi.org/10.3390/ijerph17020472
Received: 8 December 2019 / Accepted: 27 December 2019 / Published: 10 January 2020
(This article belongs to the Section Infectious Disease Epidemiology)
Antimicrobial resistance (AMR) causes millions of illnesses every year, threatening the success of lifesaving antibiotic therapy and, thus, public health. To examine the rise and spread of antimicrobial resistance around the world, our study performs a multivariate statistical analysis of antimicrobial resistance gene data from eight different countries: the US, the UK, China, Brazil, Mexico, Canada, Australia, and South Africa. Multi-dimensional data points were projected onto a two-dimensional plane using principal component analysis and organized into a dendrogram utilizing hierarchical clustering to identify significant AMR genes and pathogens. Outlier genes/pathogens were typically involved in high occurrences of antimicrobial resistance, and they were able to indicate the trend of antimicrobial resistance in the future. Statistical analysis of the data identified: (1) tet(A), aph(3″)-Ib, aph(6)-Id, blaEC, blaTEM-1, qacEdelta1, sul1, sul2, and aadA1 as the nine most common AMR genes among the studied countries; (2) Salmonella enterica and E. coli and Shigella as the most common AMR foodborne pathogens; and (3) chicken as the most prevalent meat carrier of antimicrobial resistance. Our study shows that the overall number of reported antimicrobial resistance cases in foodborne pathogens is generally rising. One potential contributing factor for this is the increasing antimicrobial usage in the growing livestock industry. View Full-Text
Keywords: foodborne pathogens; antimicrobial resistance; principal component analysis; hierarchical clustering foodborne pathogens; antimicrobial resistance; principal component analysis; hierarchical clustering
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MDPI and ACS Style

Yang, K.; Wang, A.; Fu, M.; Wang, A.; Chen, K.; Jia, Q.; Huang, Z. Investigation of Incidents and Trends of Antimicrobial Resistance in Foodborne Pathogens in Eight Countries from Historical Sample Data. Int. J. Environ. Res. Public Health 2020, 17, 472. https://doi.org/10.3390/ijerph17020472

AMA Style

Yang K, Wang A, Fu M, Wang A, Chen K, Jia Q, Huang Z. Investigation of Incidents and Trends of Antimicrobial Resistance in Foodborne Pathogens in Eight Countries from Historical Sample Data. International Journal of Environmental Research and Public Health. 2020; 17(2):472. https://doi.org/10.3390/ijerph17020472

Chicago/Turabian Style

Yang, Katherine, Annie Wang, Matthew Fu, Aaron Wang, Kevin Chen, Qian Jia, and Zuyi Huang. 2020. "Investigation of Incidents and Trends of Antimicrobial Resistance in Foodborne Pathogens in Eight Countries from Historical Sample Data" International Journal of Environmental Research and Public Health 17, no. 2: 472. https://doi.org/10.3390/ijerph17020472

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