Journal of Dermatological Case Reports

Monitoring of antimicrobial resistance on the basis of the EU Zoonoses Directive

BackgroundAn estimated 12% of women experience ≥ 1 episode of urinary tract infection (UTI) annually. Incidence is bimodal, with peaks occurring in young, sexually active women (18–24 years) and in post-menopausal women. Previous studies suggest the prevalence of antimicrobial resistance (AMR) in UTI is rising; however recent AMR data for community-acquired UTI are lacking. We estimated the prevalence of AMR among US females with outpatient UTI in 2011–2019, stratified by age.MethodsA retrospective, multicenter, cohort study of AMR among non-duplicate urine isolates in US females (≥ 12 years of age) from 296 institutions from 2011–2019 (BD Insights Research Database, Franklin Lakes, NJ). Phenotypes examined for Enterobacterales (ENT) were: extended spectrum β-lactamase positive (ESBL+; determined by commercial panels or intermediate/resistant to ceftriaxone, cefotaxime, ceftazidime or cefepime); nitrofurantoin (NFT) not-susceptible (NS); fluoroquinolone (FQ) NS; trimethoprim-sulfamethoxazole (TMP-SMX) NS; and NS to ≥ 2 or ≥ 3 drug classes (including ESBL+). Gram-positive phenotypes were, methicillin resistant S. aureus and S. saprophyticus and vancomycin-resistant Enterococcus. Isolates were stratified by patient age (≥ 12 to < 18, ≥ 18 to < 55, ≥ 55 to < 65, ≥ 65 to < 75, ≥ 75 years). Chi-square tests were used to evaluate AMR difference between groups.ResultsIn total, urine isolates were collected from 106 to 296 (2011–2019) US sites. Overall, the prevalence of antimicrobial NS increased with age for all E. coli phenotypes (all P< 0.001; Table 1), and for non-E. coli ENT (all P< 0.001), except NFT NS, which decreased from 70.6% to 59.7% (P=0.002; Table 2). The greatest difference between age groups in prevalence of resistance was observed for FQ NS E.coli: 5.8% (≥ 12 to < 18 years) vs 34.5% (≥ 75 years). For the multi-drug resistant E. coli phenotypes, resistance increased with age, ranging from 4.8–22.4% and 0.9–6.5% for ≥ 2 and ≥ 3 drug NS, respectively. Overall, the prevalence of resistance for Gram-positive phenotypes increased with age (all P< 0.001; Table 3).Table 1. Prevalence of antimicrobial resistance among E. coli isolates in US females with outpatient UTI by age group.Table 2. Prevalence of antimicrobial resistance among non-E. coli ENT isolates in US females with outpatient UTI by age group.Table 3. Prevalence of antimicrobial resistance among Gram-positive isolates in US females with outpatient UTI by age group.ConclusionThe prevalence of AMR in E. coli and non-E. coli ENT increased with age among US females presenting for care in the outpatient setting overall. A similar trend increase by age is also seen in Gram-positive isolates.DisclosuresVikas Gupta, PharmD, BCPS, Becton, Dickinson and Company (Employee, Shareholder)GlaxoSmithKline plc. (Other Financial or Material Support, Funding) Aruni Mulgirigama, MBBS, GlaxoSmithKline plc. (Employee, Shareholder) Ashish V. Joshi, PhD, GlaxoSmithKline plc. (Employee, Shareholder) Nicole Scangarella-Oman, MS, GlaxoSmithKline plc. (Employee, Shareholder) Kalvin Yu, MD, Becton, Dickinson and Company (Employee)GlaxoSmithKline plc. (Other Financial or Material Support, Funding) Gang Ye, PhD, Becton, Dickinson and Company (Employee)GlaxoSmithKline plc. (Other Financial or Material Support, Funding) Fanny S. Mitrani-Gold, MPH, GlaxoSmithKline plc. (Employee, Shareholder)

Antimicrobial resistance (AMR) poses significant challenges to health and treatment options in both human and veterinary medicine. Animal AMR monitoring in the US evaluates carcasses, retail meat, live animals, and diagnostic laboratory submissions; however, there is a lack of consistent on-farm monitoring of use and resistance. In 2020, 153 pig farms in the Midwestern United States enrolled in an antimicrobial purchase and resistance monitoring program. Intestinal samples or fecal swabs were collected biannually for 3 years from pigs and their dunging areas; antibiotic purchase data were tracked. Salmonella enterica and Escherichia coli were isolated and underwent antibiotic susceptibility testing using either a commercial bovine/ porcine (BOPO 7F) panel (for pig samples) or the National Antimicrobial Resistance Monitoring System (NARMS) Gram-negative panel (for dunging area samples). Minimum inhibitory concentrations (MICs) of antibiotics were used to evaluate the susceptibility of pig sample isolates, while NARMS breakpoints were used to assess resistance in isolates from dunging areas. Tetracyclines were the most purchased, and penicillins were the most used antibiotic class across farm types. For pig samples, more isolates exhibited MIC values at the high end of the tested range among E. coli and Salmonella isolates from wean-to-market (WTM) sites compared to breed-to-wean (BTW) sites for almost all antibiotic classes. In addition, E. coli isolates from sick pigs had higher MIC values compared to isolates from substandard but otherwise healthy pigs. Among the dunging area isolates, both bacteria had higher rates of resistance in the WTM sites compared to the BTW sites across multiple antibiotics. Individual ages of pigs were a likely confounder and were not controlled for, as these data were not reliably collected. A greater frequency of monitoring, along with controlling for age, recent treatments, and disease events at the individual level, would improve farm-level insights from on-farm AMR monitoring. Currently, the interpretation of phenotypic AMR data for resistance monitoring in swine medicine is limited by the lack of established veterinary breakpoints for enteric organisms. The available NARMS breakpoints are designed for humans, can be used for public health monitoring, and are likely to be applicable primarily to gastrointestinal infections involving the same bacteria in farm animals.

Escherichia coli is considered an opportunistic pathogen and an indicator for antimicrobial resistance (AMR) monitoring. Despite many reports on its AMR monitoring, studies based on genome-based analysis of AMR genes are still insufficient. Here, 181 E. coli strains were isolated from anal swab samples collected from pigs and chickens of animal farms located in Eastern China and sequenced through the Illumina platform. The results showed that 87.85% (159/181) of the E. coli isolates were multidrug-resistant (MDR). Ampicillin (AMP)- spectinomycin (SPT)- tetracycline (TET)- florfenicol (FFC)- sulfisoxazole (SF)- trimethoprim/sulfamethoxazole (SXT) was the predominant AMR pattern. By whole-genome sequencing, we found that ST10 (10.49%, 19/181) and ST48 (7.18%, 13/181) were major sequence types. IncFIB and IncX1 were the most prevalent plasmid replicons. The AMR genes blaNDM-5 (1.10%, 2/181), mcr-1 (1.10%, 2/181), tet(X4) (1.10%, 2/181), and cfr (6.08%, 11/181) were also found in these isolates. In addition, among the 169 virulence genes detected, we identified astA (37.02%, 67/181), hlyA (1.66%, 3/181), hlyB (1.66%, 3/181) and hlyD (1.66%, 3/181), which were closely related to heat-stable enterotoxin 1 and α-hemolysin. In addition, there were 33 virulence genes associated with the iron uptake system, and 46 were adhesion-related genes. Our study highlighted the need for routine surveillance of AMR with advanced genomic approaches, providing up-to-date data on the prevalence of AMR for the development and execution of antimicrobial stewardship policy.

To investigate whether there is a correlation between the rates of antimicrobial drug consumption in hospital departments and the prevalence of antimicrobial resistance among clinically important bacteria recovered in the hospital. Retrospective study. Tertiary care hospital in Greece. Data on antimicrobial consumption (from January 2001 through December 2004) were expressed as defined daily doses per 100 bed-days. The prevalence of antimicrobial resistance among isolates of Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, and Enterococcus faecium recovered during the same time period were calculated by the microbiology department. We then performed the following analyses: (1) a comparison of the consumption rates for different antimicrobial groups in individual hospital departments, (2) a comparison of the prevalence of resistance to different antimicrobials, and (3) a correlation analysis of antimicrobial consumption rates and the prevalence of antimicrobial resistance. The rates of antimicrobial consumption and the prevalence of resistance varied substantially among the hospital's departments. The annual rate of consumption for carbapenems correlated with the rate of consumption for glycopeptides and third-generation cephalosporins (P < .05). Among P. aeruginosa isolates, the prevalence of imipenem resistance correlated with the prevalence of resistance to amikacin, ciprofloxacin, and ceftazidime (P < .05). The rate of carbapenem consumption correlated with the prevalence of imipenem resistance among P. aeruginosa and A. baumannii isolates (P < .05). The rate of aminoglycoside consumption correlated with the prevalence of amikacin resistance among P. aeruginosa, K. pneumoniae, and E. coli isolates (P < .05). However, the rate of consumption for fluoroquinolones and glycopeptides had no correlation with the prevalence of ciprofloxacin resistance among gram-negative bacteria or vancomycin resistance among E. faecium isolates. These data are suggestive of a differential relationship between antimicrobial consumption and the prevalence of antimicrobial resistance among various species and for various antimicrobial agents. These findings may help to optimize antimicrobial prescription policies in the hospital, especially in departments that have both high rates of antimicrobial consumption and a high prevalence of antimicrobial resistance.

Proposals to improve the harmonisation of monitoring and reporting of antimicrobial resistance in Salmonella, Campylobacter coli and jejuni, indicator Escherichia coli and Enterococcus from food producing animals and derived meat by the European Union Member States are presented. In establishing a list of combinations of bacterial species, food‐producing animal populations and food products and in setting up priorities for the monitoring of antimicrobial resistance from a public health perspective, the potential exposure of the consumers has been considered as the first variable to be taken into account. As the prevalence of Salmonella is decreasing, monitoring of antimicrobial resistance should be enforced in indicator bacteria. The concept of a threshold is introduced for some animal populations and their derived meat (whose consumption is limited to certain Member States) to determine whether monitoring of antimicrobial resistance should be mandatory. Currently used phenotypic monitoring of antimicrobial resistance in bacterial isolates is to be retained but recommendations are given for broadening the harmonised panel of antimicrobials used for Salmonella, E. coli and Enterococcus spp. with the inclusion of substances that are either important for human health or that can provide clearer insight into the resistance mechanisms involved. The use of microdilution methods for testing is confirmed as the preferred option and this should be accompanied by the application of epidemiological cut off values for the interpretation of microbiological resistance. A two‐step testing strategy has been devised to further characterise those isolates of E.coli and Salmonella spp. showing resistance to extended spectrum cephalosporins and carbapenems. Several analytical methods are suggested for monitoring of ESBL/AmpC‐producing E.coli. Finally, full support is given to the collection and reporting of data at isolate level, in order to enable more in‐depth analyses to be conducted, in particular on the occurrence of multi‐resistance.

ABSTR ACT 100 to 0.19 μL/mL for either EO.After that, Minimum Bactericidal Concentrations (MBC) were evaluated for the two EOs.Results: Chromatographic analysis of the M. armillaris EO revealed the presence of 1,8-cineol as the main component (72.3%), and, in lesser magnitude, limonene (7.8%) and α-pinene (6.0%).While in the O. vulgare EO the principal was carvacrol (34.91%).These chemical compounds are commonly present in EOs with high antimicrobial activity, particularly 1,8-cineol.Regarding the antimicrobial activity, the MICs were between 0.78-6.25 μL/mL and 6.25-12.5 μL/mL with MBC/MIC ratios of 2 (bactericidal) and 4 (bacteriostatic) for M. armillaris and O. vulgaris EOs, respectively. Conclusions:The antimicrobial activity of M. armillaris and O. vulgare against E. coli avian origin was confirmed in this first study.The essential oil of M. armillaris had more antimicrobial activity than O. vulgare.The beginning of antimicrobial resistance by zoonotic bacteria has important implications for public health.Therefore, the use of M. armillaris and O. vulgare essential oils alone or combined could be effective on avian E. coli strains and may be an alternative for reducing the losses caused by these bacteria in poultry production whenever a limitation in the use of traditional antibiotics.

In Japan, sustainable national antimicrobial resistance (AMR) monitoring has been established in both human and veterinary fields. However, AMR monitoring in the environment, including wildlife, remains limited. This study aimed to assess the possibility of sustainable monitoring using wild deer transported to slaughterhouses and wild foxes surveyed for Echinococcus multilocularis. Escherichia coli, a common AMR indicator bacterium, was isolated from rectal swabs of deer and foxes using Chromagar ECC, with and without antimicrobials (cefotaxime (CTX) or nalidixic acid (NA). Antimicrobial susceptibility was determined, and β-lactamase genes were detected using polymerase chain reaction. Plasmids carrying β-lactamase genes were analyzed by whole-genome sequencing. A total of 104 E. coli strains were isolated from (103/120, 85.8%) deer and 61 strains from (56/99, 56.6%) foxes using medium without antimicrobials. Using a medium containing CTX and NA, two and three strains were isolated, respectively, exclusively from foxes. All deer strains were susceptible to the tested antimicrobials. However, 0-11.5% of fox strains from medium without antimicrobials (n=61) demonstrated resistance. Three strains from foxes had β-lactamase genes in plasmid. Finally, this study demonstrates the feasibility of sustainable AMR monitoring using wild deer transported to a slaughterhouse and wild foxes surveyed for E. multilocularis.

As part of the European Union's harmonized monitoring framework, Belgium conducts antimicrobial resistance (AMR) monitoring in commensal bacteria from livestock. The aim of this study was to conduct a cost analysis of the national AMR monitoring in livestock, and to explore sampling size scenarios in relation to their associated costs and statistical performance (power and confidence) of monitoring. To our knowledge, this is the first published cost evaluation using unit cost aggregation of a national AMR monitoring program in animals. The testing of the different sample size scenarios showed that if the sample size increases, the costs increase linearly. A sample size increase of 10 samples/isolates (e.g., from 170 to 180) can increase the yearly total costs per animal species by 5.2%. Moreover, the testing of the different scenarios showed that if the sample size increases, the power and the confidence level also increase, providing a higher level of trust in the results of the monitoring program. The highest total monitoring costs per animal category were estimated for fattening pigs, broilers and veal calves (over 18% of total costs each, using 2024 data). Among the various monitoring activities, antimicrobial susceptibility testing emerged as the costliest component, representing 50.2% of the total monitoring costs. The approach presented allows it to be used by other countries aiming to estimate the cost of their national AMR monitoring in animals or other similar activities. This economic and scenario testing analysis can be used to suggest informed suggestions to improve AMR monitoring in animals.

Prevalence of ciprofloxacin resistance and associated genetic determinants differed among Campylobacter isolated from human and poultry meat sources in Pennsylvania

Antimicrobial resistance profiles of common mastitis pathogens on Canadian dairy farms

In 2019, the United States National Antimicrobial Resistance Monitoring System (NARMS) surveyed raw salmon, shrimp, and tilapia from retail grocery outlets in eight states to assess the prevalence of bacterial contamination and antimicrobial resistance (AMR) in the isolates. Prevalence of the targeted bacterial genera ranged among the commodities: Salmonella (0%–0.4%), Aeromonas (19%–26%), Vibrio (7%–43%), Pseudomonas aeruginosa (0.8%–2.3%), Staphylococcus (23%–30%), and Enterococcus (39%–66%). Shrimp had the highest odds (OR: 2.8, CI: 2.0–3.9) of being contaminated with at least one species of these bacteria, as were seafood sourced from Asia vs. North America (OR: 2.7; CI: 1.8–4.7) and Latin America and the Caribbean vs. North America (OR: 1.6; CI: 1.1–2.3) and seafood sold at the counter vs. sold frozen (OR: 2.1; CI: 1.6–2.9). Isolates exhibited pan-susceptibility (Salmonella and P. aeruginosa) or low prevalence of resistance (<10%) to most antimicrobials tested, with few exceptions. Seafood marketed as farm-raised had lower odds of contamination with antimicrobial resistant bacteria compared to wild-caught seafood (OR: 0.4, CI: 0.2–0.7). Antimicrobial resistance genes (ARGs) were detected for various classes of medically important antimicrobials. Clinically relevant ARGs included carbapenemases (blaIMI-2, blaNDM-1) and extended spectrum β-lactamases (ESBLs; blaCTX-M-55). This population-scale study of AMR in seafood sold in the United States provided the basis for NARMS seafood monitoring, which began in 2020.

Monitoring of antimicrobial resistance in healthy dogs: First report of canine ampicillin-resistant Enterococcus faecium clonal complex 17

An optimized national resistance monitoring program should deliver a precise estimate of the resistance situation for a given combination of bacteria and antimicrobial at a low cost. In order to achieve this, decisions need to be made on the number of samples to be collected at each of different possible sampling points along the food production line. Sampling decisions do not only depend on the prevalence of resistance and sensitivity and specificity of resistance test- ing, but also on the prevalence of the bacteria, and test characteristics of isolation of these bacte- ria. Our aim was to develop a stochastic simulation model that optimized a national resistance monitoring program in pig production, taking multi-stage sampling, imperfect sensitivity and specificity of diagnostic tests, and cost-effectiveness considerations into account. Introduction The use of antimicrobial substances in animal production is one potential reason for the occurrence of resistant bacteria in humans. Thus monitoring the resistance status of various bacteria in the animal population is important for a timely intervention before resistant strains spread throughout the animal population. Currently, Switzerland is developing the scientific basis for the implementation of routine antimicrobial resistance monitoring in food producing animals. Through research projects and pilot monitoring programs in various animals species, data on the prevalence of selected bacteria and antimicrobial resistance are collected. Three major sources of information are available for a comprehensive assessment of the resistance situation (figure 1). The resistance situation in clinical isolates from diseased animals reflects resistance levels in problem animals, and provides information on the effectiveness of common veterinary drugs for the treatment of diseases on swine farms. Therefore, the focus of the resistance monitoring in this group of animals should be on bacteria pathogenic to animals, as well as on zoonotic bacteria such as Salmonella and Campylobacter. The resistance situation in bacteria isolates from healthy animals and food of animal origin, on the other hand, reflects the potential exposure of humans to resistant bacteria from animals. Finally, data on antimicrobial usage are crucial for establishing epi- demiological links between treatment regimens in animals and changes in the resistance situation in animals and humans. Along the food production chain, various sampling points are conceivable for resistance moni- toring in healthy animals including sow, weaner pig or finishing pig farms, at slaughter, and at retail level. The optimal sampling point may differ depending on the targeted bacteria and antimi- crobial resistance involved. When monitoring resistance of bacteria originating from live animals, decisions need to be made on the number of farms monitored, the number of animals tested per farm, the number of samples per animal, and the number of colonies that are submitted to sus- ceptibility testing from each sample.

The World Health Organization has recognized antimicrobial resistance as one of the top three threats to human health. Any use of antibiotics in animals will ultimately affect humans and vice versa. Appropriate monitoring of antimicrobial use and resistance has been repeatedly emphasized along with the need for global policies. Under the auspices of the European Union research project, EFFORT, we mapped antimicrobial use and resistance monitoring programs in ten European countries. We then compared international and European guidelines and policies. In resistance monitoring, we did not find important differences between countries. Current resistance monitoring systems are focused on food animal species (using fecal samples). They ignore companion animals. The scenario is different for monitoring antibiotics use. Recently, countries have tried to harmonize methodologies, but reporting of antimicrobial use remains voluntary. We therefore identified a need for stronger policies.