Global antimicrobial-resistance drivers: an ecological country-level study at the human-animal interface.

BACKGROUND: Antimicrobial resistance (AMR) is a pressing, holistic, and multisectoral challenge facing contemporary global health. In this study we assessed the associations between socioeconomic, anthropogenic, and environmental indicators and country-level rates of AMR in humans and food-producing animals. METHODS: In this modelling study, we obtained data on Carbapenem-resistant Acinetobacter baumanii and Pseudomonas aeruginosa, third generation cephalosporins-resistant Escherichia coli and Klebsiella pneumoniae, oxacillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus faecium AMR in humans and food-producing animals from publicly available sources, including WHO, World Bank, and Center for Disease Dynamics Economics and Policy. AMR in food-producing animals presented a combined prevalence of AMR exposure in cattle, pigs, and chickens. We used multivariable ß regression models to determine the adjusted association between human and food-producing animal AMR rates and an array of ecological country-level indicators. Human AMR rates were classified according to the WHO priority pathogens list and antibiotic-bacterium pairs. FINDINGS: Significant associations were identified between animal antimicrobial consumption and AMR in food-producing animals (OR 1·05 [95% CI 1·01-1·10]; p=0·013), and between human antimicrobial consumption and AMR specifically in WHO critical priority (1·06 [1·00-1·12]; p=0·035) and high priority (1·22 [1·09-1·37]; p<0·0001) pathogens. Bidirectional associations were also found: animal antibiotic consumption was positively linked with resistance in critical priority human pathogens (1·07 [1·01-1·13]; p=0·020) and human antibiotic consumption was positively linked with animal AMR (1·05 [1·01-1·09]; p=0·010). Carbapenem-resistant Acinetobacter baumanii, third generation cephalosporins-resistant Escherichia coli, and oxacillin-resistant Staphylococcus aureus all had significant associations with animal antibiotic consumption. Analyses also suggested significant roles of socioeconomics, including governance on AMR rates in humans and animals. INTERPRETATION: Reduced rates of antibiotic consumption alone will not be sufficient to combat the rising worldwide prevalence of AMR. Control methods should focus on poverty reduction and aim to prevent AMR transmission across different One Health domains while accounting for domain-specific risk factors. The levelling up of livestock surveillance systems to better match those reporting on human AMR, and, strengthening all surveillance efforts, particularly in low-income and middle-income countries, are pressing priorities. FUNDING: None.

ß-Lactam-Resistant Streptococcus pneumoniae Dynamics Following Treatment: A Dose-Response Meta-analysis.

BACKGROUND: Patient exposure to antibiotics promotes the emergence of drug-resistant pathogens. The aim of this study was to identify whether the temporal dynamics of resistance emergence at the individual-patient level were predictable for specific pathogen-drug classes. METHODS: Following a systematic review, a novel robust error meta-regression method for dose-response meta-analysis was used to estimate the odds ratio (OR) for carrying resistant bacteria during and following treatment compared to baseline. Probability density functions fitted to the resulting dose-response curves were then used to optimize the period during and/or after treatment when resistant pathogens were most likely to be identified. RESULTS: Studies of Streptococcus pneumoniae treatment with ß-lactam antibiotics demonstrated a peak in resistance prevalence among patients 4 days after completing treatment with a 3.32-fold increase in odds (95% confidence interval [CI], 1.71-6.46). Resistance waned more gradually than it emerged, returning to preexposure levels 1 month after treatment (OR, 0.98 [95% CI, .55-1.75]). Patient isolation during the peak dose-response period would be expected to reduce the risk that a transmitted pathogen is resistant equivalently to a 50% longer isolation window timed from the first day of treatment. CONCLUSIONS: Predictable temporal dynamics of resistance levels have implications both for surveillance and control.