Foodborne pathogens such as Salmonella that survive cleaning and disinfection during poultry processing are a public health concern because pathogens that survive disinfectants have greater potential to exhibit resistance to antibiotics and disinfectants after their initial disinfectant challenge. While the mechanisms conferring antimicrobial resistance (AMR) after exposure to disinfectants is complex, understanding the effects of disinfectants on Salmonella in both their planktonic and biofilm states is becoming increasingly important, as AMR and disinfectant tolerant bacteria are becoming more prevalent in the food chain. This review examines the modes of action of various types of disinfectants commonly used during poultry processing (quaternary ammonium, organic acids, chlorine, alkaline detergents) and the mechanisms that may confer tolerance to disinfectants and cross-protection to antibiotics. The goal of this review article is to characterize the AMR profiles of Salmonella in both their planktonic and biofilm state that have been challenged with hexadecylpyridinium chloride (HDP), peracetic acid (PAA), sodium hypochlorite (SHY) and trisodium phosphate (TSP) in order to understand the risk of these disinfectants inducing AMR in surviving bacteria that may enter the food chain.

The development of antimicrobial resistance (AMR) represents a significant threat to humans and food animals. The use of antimicrobials in human and veterinary medicine may select for resistant bacteria, resulting in increased levels of AMR in these populations. As the threat presented by AMR increases, it becomes critically important to find methods for effectively interpreting minimum inhibitory concentration (MIC) tests. Currently, a wide array of techniques for analyzing these data can be found in the literature, but few guidelines for choosing among them exist. Here, we examine several quantitative techniques for analyzing the results of MIC tests and discuss and summarize various ways to model MIC data. The goal of this review is to propose important considerations for appropriate model selection given the purpose and context of the study. Approaches reviewed include mixture models, logistic regression, cumulative logistic regression, and accelerated failure time–frailty models. Important considerations in model selection include the objective of the study (e.g., modeling MIC creep vs. clinical resistance), degree of censoring in the data (e.g., heavily left/right censored vs. primarily interval censored), and consistency of testing parameters (e.g., same range of concentrations tested for a given antibiotic).

As backyard poultry (BYP) ownership has increased in the US, the demand for veterinarians who treat BYP has also increased. However, veterinarians who treat BYP remain scarce and are mostly small animal veterinarians and exotic animal practitioners who have limited training in food animal regulatory practices. To gauge whether veterinary students are interested in learning more about BYP and what BYP topics to include in an online training program for veterinary students, a BYP knowledge assessment was conducted. Pre-clinical veterinary students were asked to self-rate their level of knowledge on various topics for both small animal practice and BYP using Likert-type ordinal scales. Wilcoxon signed-rank tests of those Likert data showed significant differences (p < .01 at α = .05) between self-assessed knowledge of poultry and small animal medicine for all surveyed topics. Specifically, veterinary students ranked themselves as less knowledgeable on poultry concepts than on small animal medicine concepts. Nevertheless, students expressed interest in an online training program for treating BYP and drug residue avoidance in BYP, despite having chosen future career tracks that are not exclusively poultry. Specific topics students expressed interest in with respect to BYP training included anatomy, husbandry, prescribing medications, treatment options, food safety, antimicrobial resistance, and extra-label drug use.