Present and Future Surveillance of Antimicrobial Resistance in Animals: Principles and Practices

Abstract

There is broad consensus internationally that surveillance of the levels of antimicrobial resistance (AMR) occurring in various systems underpins strategies to address the issue. The key reasons for surveillance of resistance are to determine (i) the size of the problem, (ii) whether resistance is increasing, (iii) whether previously unknown types of resistance are emerging, (iv) whether a particular type of resistance is spreading, and (v) whether a particular type of resistance is associated with a particular outbreak. The implications of acquiring and utilizing this information need to be considered in the design of a surveillance system. AMR surveillance provides a foundation for assessing the burden of AMR and for providing the necessary evidence for developing efficient and effective control and prevention strategies. The codevelopment of AMR surveillance programs in humans and animals is essential, but there remain several key elements that make data comparisons between AMR monitoring programs, and between regions, difficult. Currently, AMR surveillance relies on uncomplicated antimicrobial susceptibility methods. However, the lack of harmonization across programs and the limitation of genetic information of AMR remain the major drawbacks of these phenotypic methods. The future of AMR surveillance is moving toward genotypic detection, and molecular analysis methods are expected to yield a wealth of information. However, the expectation that these molecular techniques will surpass phenotypic susceptibility testing in routine diagnosis and monitoring of AMR remains a distant reality, and phenotypic testing remains necessary in the detection of emerging resistant bacteria, new resistance mechanisms, and trends of AMR.

Escherichia coli and Salmonella spp. isolated from Australian meat chickens remain susceptible to critically important antimicrobial agents

“…Non-wild type isolates (defined as having MICs above the ECOFF) have been shown to contain acquired resistance mechanisms in their genome, even though they may have MICs below the defined CLSI clinical breakpoints [25]. Therefore, for more simplistic determination of individual and multi-class resistance profiles, we refer to isolates exceeding the antimicrobial ECOFF as “resistant”.…”

Prevalence of Cefotaxime-Resistant Escherichia coli Isolates from Healthy Cattle and Sheep in Northern Spain: Phenotypic and Genome-Based Characterization of Antimicrobial Susceptibility

“…In beef cattle, antimicrobial treatments are mostly implemented in young animals to treat diarrhea and respiratory diseases, while dairy cattle suffer from a wider diversity of pathologies during their longer life span that need to be treated with antimicrobials. In dairy cattle, ␤-lactams are used to treat mastitis (mainly penicillins but also cephalosporins such as ceftiofur and cefquinome) and also during dry-off to control and prevent intramammary infections following the last milking of the lactation period (mostly penicillins) (19). However, intramammary application might be expected to have less effect than oral administration on the spread of AMR in the intestinal microbiota.…”

Antimicrobial Susceptibility Testing of Antimicrobial Peptides to Better Predict Efficacy

“…Different documents describe breakpoints for bacteria, yeasts, filamentous fungi (moulds) and other microorganisms ( Table 1 ). Despite many similarities and agreements, there remains some lack of harmonisation between AST methods from different organisations (Pfaller et al, 2011 , 2014 ; Chowdhary et al, 2015 ; Kahlmeter, 2015 ; Brown et al, 2016 ; Sanguinetti and Posteraro, 2018 ; Simjee et al, 2018 ; Cusack et al, 2019 ). Interpretive categories most commonly assigned are susceptible (S), indicative of a high probability of a successful outcome, and resistant (R), indicative of a low probability of a successful outcome, although in less common cases other categories include; non-susceptible, intermediate, susceptible-dose dependent and area of technical uncertainty (See the documents in Table 1 for details about these interpretive categories).…”