Emilie Gay

Objectives: To examine the relevance of co-resistance to amoxicillin and tetracycline as an indicator of multidrug resistance (MDR) in animal health. Methods: Escherichia coli isolates collected between 2012 and 2016 by the French surveillance network for antimicrobial resistance in diseased animals (RESAPATH) were analyzed. The proportions of MDR isolates and the proportions of isolates presenting co-resistance to amoxicillin and tetracycline were calculated for seven animal species (cattle, horse, dog, swine, poultry, duck, and turkey). The degree of agreement between these two proportions was estimated by calculating the kappa value. Results: In total, 55,904 isolates were analyzed. MDR proportions were variable among animal species, ranging from 21.9% [20.2; 23.7] in horses to 56.0% [55.4; 56.7] in cattle. A similar situation was observed for proportions of isolates with co-resistance to amoxicillin and tetracycline, with the highest value for cattle 65.0% [64.3; 65.6]. This co-resistance was also most often associated with resistance to other antibiotics, regardless of the animal species considered. Comparative analysis showed substantial agreement between MDR and this co-resistance, with a kappa value of 0.75, all animal species considered. Conclusion: Given the widespread use of penicillins and tetracyclines in animal health, co-resistance to amoxicillin and tetracycline could be an efficient indicator of MDR in E. coli isolates. Based on a specific resistance profile and not an arbitrary number of resistances compared with MDR, this potential indicator is also precise, convenient and suitable for routine use.

Summary: Background: Horses are one of the potential reservoirs of antimicrobial resistance ( AMR ) determinants that could be transferred to human subjects. Objective: To describe the AMR patterns of major bacteria isolated from diseased horses in France. Study design: Retrospective observational study. Methods: Data collected between 2012 and 2016 by RESAPATH , the French national surveillance network for AMR , were analysed. Only antimicrobials relevant in veterinary and human medicine for the isolated bacteria were considered. Mono‐ and multidrug resistance were calculated. The resistance proportions of major equine diseases were assessed and compared. Where data permitted, resistance trends were investigated using nonlinear analysis (generalised additive models). Results: A total of 12,695 antibiograms were analysed. The five most frequently isolated bacteria were Streptococcus spp., Escherichia coli , Pseudomonas spp., Staphylococcus aureus , Pantoea spp. and Klebsiella spp. The highest proportions of resistance to gentamicin were found for S. aureus (22.1%) and Pseudomonas spp. (26.9%). Klebsiella spp. and E. coli had the highest proportions of resistance to trimethoprim‐sulfamethoxazole (15.5 and 26.2%, respectively). Proportions of resistance to tetracycline were among the highest for all the bacteria considered. Resistance to third‐generation cephalosporins was below 10% for all Enterobacteriaceae . The highest proportions of multidrug resistance (22.5%) were found among S. aureus isolates, which is worrying given their zoonotic potential. From 2012 to 2016, resistance proportions decreased in Pseudomonas spp. isolates, but remained the same for S. aureus . For Streptococcus spp. and E. coli , resistance proportions to trimethoprim‐sulfamethoxazole increased. Main limitations: Since antibiograms are not systematic analyses, any selection bias could impact the results. Conclusions: Such studies are essential to estimate the magnitude of the potential threat of AMR to public health, to design efficient control strategies and to measure their effectiveness. These findings may also guide the initial empirical treatment of horse diseases.

Antimicrobial-resistant bacteria in dogs can be transmitted to humans and close contact between dogs and people might foster dissemination of resistance determinants. The aim of our study was to describe the antimicrobial resistance (AMR) pattern of the major causative agents of canine otitis – one of the most common diseases in dogs – isolated in France. Data collected between 2012 and 2016 by the French national surveillance network for AMR, referred to as RESAPATH, were analysed. Resistance trends were investigated using non-linear analysis (generalised additive models). A total of 7021 antibiograms were analysed. The four major causative agents of canine otitis in France were coagulase-positive staphylococci,Pseudomonas aeruginosa,Proteus mirabilisand streptococci. Since 2013, resistance to fluoroquinolones has been on the decrease in bothP. aeruginosaandStaphylococcus pseudintermediusisolates. ForP. aeruginosa, 19.4% of isolates were resistant to both enrofloxacin and gentamicin. The levels of multidrug resistance (acquired resistance to at least one antibiotic in three or more antibiotic classes) ranged between 11.9% forP. mirabilisand 16.0% forS. pseudintermedius.These results are essential to guide prudent use of antibiotics in veterinary medicine. They will also help in designing efficient control strategies and in measuring their effectiveness.

In dairy cattle, mastitis is the most frequent bacterial disease, and the routine use of antibiotics for treatment and prevention can drive antimicrobial resistance (AMR). The aim of our study was to estimate the levels of AMR of the 3 main bacteria isolated from dairy cattle with mastitis in France (Streptococcus uberis, Escherichia coli, and coagulase-positive staphylococci) and to investigate their changes over time. Data collected between 2006 and 2016 by the French surveillance network for AMR in pathogenic bacteria of animal origin (called RESAPATH) were analyzed. The proportions of mono- and multidrug resistance were calculated and the trends were investigated using nonlinear analyses applied to time series. Over the whole period, the lowest proportions of resistance in S. uberis isolates were observed for oxacillin (2.2%) and gentamicin (2.4%) and most resistance levels were below 20%. The trends in resistance showed some significant variation, mainly for S. uberis, but without a common pattern across the various antibiotics examined. For only 2 combinations of bacteria-antibiotic the trend in resistance showed a continuous increase from 2006 to 2016: tetracycline resistance in S. uberis isolates and third-generation cephalosporin resistance in E. coli isolates. In E. coli, the highest proportions of resistance were observed for amoxicillin (28.1%) and tetracycline (23.1%). Resistance to third-generation cephalosporins in E. coli from dairy cattle was almost nil in 2006, but reached 2.4% in December 2016. This increase is particularly concerning because these antibiotics constitute one of the latest therapeutic alternatives to fight severe infectious diseases in humans. Except for penicillin (33.9%), the proportions of resistance in coagulase-positive staphylococci were below 11% during the whole study period. Multidrug resistance (isolates with acquired resistance to at least one antibiotic in 3 or more antibiotic classes) ranged from 2.4% for coagulase-positive staphylococci to 9.9% for S. uberis. These findings can serve as guidelines for practitioners in the choice of the most appropriate antibiotic according to the prevailing epidemiological context. Ultimately, our results contribute to risk assessment of AMR and provide a baseline for setting up and evaluating control measures and designing strategies to limit AMR.

Summary: Antimicrobial resistance (AMR) among bacteria isolated from food‐producing animals is a growing concern with implications for public health. AMR surveillance is essential to identify resistance trends and help in the design of effective and efficient control strategies. The aim of the study was to describe the antimicrobial susceptibility of pathogenic Escherichia coli isolated from three livestock productions in France (cattle, swine and poultry). The trend in resistance to the most commonly prescribed antibiotics in animal health was analysed as follows: amoxicillin (penicillin), spectinomycin or streptomycin (aminoglycoside), tetracycline and trimethoprim‐sulfamethoxazole/Enrofloxacin and ceftiofur were also taken into account as members of critically important antimicrobial families in human and veterinary medicine, that is fluoroquinolones and third‐generation cephalosporins, respectively. Data collected between 2002 and 2015 by the French national surveillance network of AMR referred to as RESAPATH were analysed. Resistance trends were investigated using non‐linear analysis (generalized additive models) applied to time‐series stratified by livestock production and antibiotic. Irrespective of the species and the antibiotic considered, resistance signals over time showed no significant annual cycle. Resistance to third‐generation cephalosporins emerged during the period of the study, with a peak at 22% [20.5; 24.0] in poultry in 2010, decreasing afterwards, while it remained consistently below 10% for the other species. The proportion of resistance to fluoroquinolones was broadly similar between species and remained under 30%, with a slight decreasing trend after 2009. Resistances to tetracycline and amoxicillin remained high, between 90% and 40% over time in cattle and swine. After 2010, there was a decrease in resistance to these antibiotics for all species, especially to tetracycline for poultry with a drop from 84% in 2009 to 43% in 2015. These results contribute to risk assessment and constitute objective evidence on which to evaluate the efficacy of control measures implemented to limit AMR occurrence.

SUMMARY: The objective of this study was to assess the performance of several algorithms for outbreak detection based on weekly proportions of whole carcass condemnations. Data from one French slaughterhouse over the 2005–2009 period were used (177 098 slaughtered cattle, 0.97% of whole carcass condemnations). The method involved three steps: (i) preparation of an outbreak-free historical baseline over 5 years, (ii) simulation of over 100 years of baseline time series with injection of artificial outbreak signals with several shapes, durations and magnitudes, and (iii) assessment of the performance (sensitivity, specificity, outbreak detection precocity) of several algorithms to detect these artificial outbreak signals. The algorithms tested included the Shewart p chart, confidence interval of the negative binomial model, the exponentially weighted moving average (EWMA); and cumulative sum (CUSUM). The highest sensitivity was obtained using a negative binomial algorithm and the highest specificity with CUSUM or EWMA. EWMA sensitivity was too low to select this algorithm for efficient outbreak detection. CUSUM's performance was complementary to the negative binomial algorithm. The use of both algorithms on real data for a prospective investigation of the whole carcass condemnation rate as a syndromic surveillance indicator could be relevant. Shewart could also be a good option considering its high sensitivity and simplicity of implementation.