Antimicrobial Resistance Risk Assessment Models and Database System for Animal-Derived Pathogens

(1) Background: The high use of antibiotics has made the issue of antimicrobial resistance (AMR) increasingly serious, which poses a substantial threat to the health of animals and humans. However, there remains a certain gap in the AMR system and risk assessment models between China and the advance...

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Main Authors: Xinxing Li (Author), Buwen Liang (Author), Ding Xu (Author), Congming Wu (Author), Jianping Li (Author), Yongjun Zheng (Author)
Format: Book
Published: MDPI AG, 2020-11-01T00:00:00Z.
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001 doaj_4a7b1a1f0d3e48e7a1fa6e901023e4d7
042 |a dc 
100 1 0 |a Xinxing Li  |e author 
700 1 0 |a Buwen Liang  |e author 
700 1 0 |a Ding Xu  |e author 
700 1 0 |a Congming Wu  |e author 
700 1 0 |a Jianping Li  |e author 
700 1 0 |a Yongjun Zheng  |e author 
245 0 0 |a Antimicrobial Resistance Risk Assessment Models and Database System for Animal-Derived Pathogens 
260 |b MDPI AG,   |c 2020-11-01T00:00:00Z. 
500 |a 10.3390/antibiotics9110829 
500 |a 2079-6382 
520 |a (1) Background: The high use of antibiotics has made the issue of antimicrobial resistance (AMR) increasingly serious, which poses a substantial threat to the health of animals and humans. However, there remains a certain gap in the AMR system and risk assessment models between China and the advanced world level. Therefore, this paper aims to provide advanced means for the monitoring of antibiotic use and AMR data, and take piglets as an example to evaluate the risk and highlight the seriousness of AMR in China. (2) Methods: Based on the principal component analysis method, a drug resistance index model of anti-<i>E. coli</i> drugs was established to evaluate the antibiotic risk status in China. Additionally, based on the second-order Monte Carlo methods, a disease risk assessment model for piglets was established to predict the probability of <i>E. coli</i> disease within 30 days of taking florfenicol. Finally, a browser/server architecture-based visualization database system for animal-derived pathogens was developed. (3) Results: The risk of <i>E. coli</i> in the main area was assessed and Hohhot was the highest risk area in China. Compared with the true disease risk probability of 4.1%, the result of the disease risk assessment model is 7.174%, and the absolute error was 3.074%. Conclusions: Taking <i>E. coli</i> as an example, this paper provides an innovative method for rapid and accurate risk assessment of drug resistance. Additionally, the established system and assessment models have potential value for the monitoring and evaluating AMR, highlight the seriousness of antimicrobial resistance, advocate the prudent use of antibiotics, and ensure the safety of animal-derived foods and human health. 
546 |a EN 
690 |a drug resistance 
690 |a microbial 
690 |a database system 
690 |a risk assessment 
690 |a DRI 
690 |a second-order Monte Carlo method 
690 |a Therapeutics. Pharmacology 
690 |a RM1-950 
655 7 |a article  |2 local 
786 0 |n Antibiotics, Vol 9, Iss 11, p 829 (2020) 
787 0 |n https://www.mdpi.com/2079-6382/9/11/829 
787 0 |n https://doaj.org/toc/2079-6382 
856 4 1 |u https://doaj.org/article/4a7b1a1f0d3e48e7a1fa6e901023e4d7  |z Connect to this object online.