Clémence Bourély1,2,3, Thomas Coeffic4, Jocelyne Caillon4,5, Sonia Thibaut4, Géraldine Cazeau2, Eric Jouy6, Nathalie Jarrige2, Claire Chauvin7, Jean-Yves Madec8, Marisa Haenni8, Agnès Leblond3, Emilie Gay2. 1. École Nationale des Services Vétérinaires, VetAgro Sup, 69280 Marcy-l'Étoile, France. 2. Université de Lyon, ANSES, Laboratoire de Lyon, Unité Épidémiologie et appui à la surveillance, 31 avenue Tony Garnier, 69007 Lyon, France. 3. EPIA, Epidémiologie des Maladies Animales et Zoonotiques, INRA, VetAgro Sup, Université de Lyon, 69280 Marcy-l'Étoile, France. 4. MedQual network, Hôpital Saint Jacques, CHU de Nantes, 44000 Nantes, France. 5. CHU Nantes Laboratoire de Bactériologie, 9 Quai Moncousu, 44000 Nantes, France. 6. ANSES, Laboratoire de Ploufragan-Plouzané-Niort, Unité Mycoplasmologie, Bactériologie et Antibiorésistance, Université Bretagne Loire, Technopôle Saint-Brieuc Armor, 22440 Ploufragan, France. 7. ANSES, Laboratoire de Ploufragan-Plouzané-Niort, Unité Epidémiologie, Santé et Bien-être, Université Bretagne Loire, Technopôle Saint-Brieuc Armor, 22440 Ploufragan, France. 8. Université de Lyon, ANSES, Laboratoire de Lyon, Unité Antibiorésistance et Virulence Bactériennes, 31 avenue Tony Garnier, 69007 Lyon, France.
Abstract
OBJECTIVES: To characterize and compare resistance trends in clinical Escherichia coli isolates from humans, food-producing animals (poultry, cattle and swine) and pets (dogs and cats). METHODS: Antibiogram results collected between January 2014 and December 2017 by MedQual [the French surveillance network for antimicrobial resistance (AMR) in bacteria isolated from the community] and RESAPATH (the French surveillance network for AMR in bacteria from diseased animals) were analysed, focusing on resistance to antibiotics of common interest to human and veterinary medicine. Resistance dynamics were investigated using generalized additive models. RESULTS: In total, 743 637 antibiograms from humans, 48 170 from food-producing animals and 7750 from pets were analysed. For each antibiotic investigated, the resistance proportions of isolates collected from humans were of the same order of magnitude as those from food-producing animals or pets. However, resistance trends in humans differed from those observed in pets and food-producing animals over the period studied. For example, resistance to third-generation cephalosporins and fluoroquinolones was almost always below 10% for both humans and animals. However, in contrast to the notable decreases in resistance observed in both food-producing animals and pets, resistance in humans decreased only slightly. CONCLUSIONS: Despite several potential biases in the data, the resistance trends remain meaningful. The strength of the parallel is based on similar data collection in humans and animals and on a similar statistical methodology. Resistance dynamics seemed specific to each species, reflecting different antibiotic-use practices. These results advocate applying the efforts already being made to reduce antibiotic use to all sectors and all species, both in human and veterinary medicine.
OBJECTIVES: To characterize and compare resistance trends in clinical Escherichia coli isolates from humans, food-producing animals (poultry, cattle and swine) and pets (dogs and cats). METHODS: Antibiogram results collected between January 2014 and December 2017 by MedQual [the French surveillance network for antimicrobial resistance (AMR) in bacteria isolated from the community] and RESAPATH (the French surveillance network for AMR in bacteria from diseased animals) were analysed, focusing on resistance to antibiotics of common interest to human and veterinary medicine. Resistance dynamics were investigated using generalized additive models. RESULTS: In total, 743 637 antibiograms from humans, 48 170 from food-producing animals and 7750 from pets were analysed. For each antibiotic investigated, the resistance proportions of isolates collected from humans were of the same order of magnitude as those from food-producing animals or pets. However, resistance trends in humans differed from those observed in pets and food-producing animals over the period studied. For example, resistance to third-generation cephalosporins and fluoroquinolones was almost always below 10% for both humans and animals. However, in contrast to the notable decreases in resistance observed in both food-producing animals and pets, resistance in humans decreased only slightly. CONCLUSIONS: Despite several potential biases in the data, the resistance trends remain meaningful. The strength of the parallel is based on similar data collection in humans and animals and on a similar statistical methodology. Resistance dynamics seemed specific to each species, reflecting different antibiotic-use practices. These results advocate applying the efforts already being made to reduce antibiotic use to all sectors and all species, both in human and veterinary medicine.
Authors: Elisa Massella; Cameron J Reid; Max L Cummins; Kay Anantanawat; Tiziana Zingali; Andrea Serraino; Silvia Piva; Federica Giacometti; Steven P Djordjevic Journal: Antibiotics (Basel) Date: 2020-11-06