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Abstract Background The majority of antimicrobials given during the production of pigs are given to nursery pigs. The influence of antimicrobial use on the levels of antimicrobial resistant (AMR) genes is important to quantify to be able to assess the impact of resistance on the food chain and risk to human and animal health. Results This study investigated the response on the levels of nine AMR genes to five different treatment strategies with oxytetracycline, and the dynamics of gene abundance over time by following 1167 pigs from five different farms in Denmark. The results showed no significant difference between treatments and an increase in abundance for the efflux pump encoding tet(A) gene and the genes encoding the ribosomal protection proteins tet(O) and tet(W) tetracycline resistant genes following treatment, while tet(M) showed no response to treatment. However, it was also observed that the levels of tet(O), tet(W), and ermB in some farms would drift more over time compared to a single treatment-course with antibiotic. Conclusion This study underlines the large variation in AMR levels under natural conditions and the need for increased investigation of the complex interactions of antimicrobial treatment and other environmental and managerial practices in swine production on AMR gene abundance.

Abstract Background Antimicrobial resistance is a global health problem that demands all possible means to control it. Mathematical modelling is a valuable tool for understanding the mechanisms of AMR development and spread, and can help us to investigate and propose novel control strategies. However, it is of vital importance that mathematical models have a broad utility, which can be assured if good modelling practice is followed. Objective The objective of this study was to provide a comprehensive systematic review of published models of AMR development and spread. Furthermore, the study aimed to identify gaps in the knowledge required to develop useful models. Methods The review comprised a comprehensive literature search with 38 selected studies. Information was extracted from the selected papers using an adaptation of previously published frameworks, and was evaluated using the TRACE good modelling practice guidelines. Results None of the selected papers fulfilled the TRACE guidelines. We recommend that future mathematical models should: a) model the biological processes mechanistically, b) incorporate uncertainty and variability in the system using stochastic modelling, c) include a sensitivity analysis and model external and internal validation. Conclusion Many mathematical models of AMR development and spread exist. There is still a lack of knowledge about antimicrobial resistance, which restricts the development of useful mathematical models.