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The objective was to establish and standardise a broth microdilution susceptibility testing method for porcine Bordetella (B.) bronchiseptica. B. bronchiseptica isolates from different geographical regions and farms were genotyped by macrorestriction analysis and subsequent pulsed-field gel electrophoresis. One reference and one type strain plus two field isolates of B. bronchiseptica were chosen to analyse growth curves in four different media: cation-adjusted Mueller-Hinton broth (CAMHB) with and without 2% lysed horse blood, Brain-Heart-Infusion (BHI), and Caso broth. The growth rate of each test strain in each medium was determined by culture enumeration and the suitability of CAMHB was confirmed by comparative statistical analysis. Thereafter, reference and type strain and eight epidemiologically unrelated field isolates of B. bronchiseptica were used to test the suitability of a broth microdilution susceptibility testing method following CLSI-approved performance standards given in document VET01-A4. Susceptibility tests, using 20 antimicrobial agents, were performed in five replicates, and data were collected after 20 and 24 hours incubation and statistically analysed. Due to the low growth rate of B. bronchiseptica, an incubation time of 24 hours resulted in significantly more homogeneous minimum inhibitory concentrations after five replications compared to a 20-hour incubation. An interlaboratory comparison trial including susceptibility testing of 24 antimicrobial agents revealed a high mean level of reproducibility (97.9%) of the modified method. Hence, in a harmonization for broth microdilution susceptibility testing of B. bronchiseptica, an incubation time of 24 hours in CAMHB medium with an incubation temperature of 35°C and an inoculum concentration of approximately 5 x 105 cfu/ml was proposed.
Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i) to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model) and (ii) to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate model.