Discipline: Biological Sciences
Subcategory:
Mary Gockenbach - University of Texas at Arlington
Co-Author(s): McKenna Cortez, University of Nevada - Reno, Reno, NV Ying Huang, Shanghai University, Shanghai, P.R. CHINA Noah Padgett, University of Wisconsin - Whitewater, Whitewater, WI
Antibiotic resistance is a global health concern that involves animals as well as humans. In zoonotic diseases, not generally fatal to humans, antibiotic resistance provides a reservoir from which pathogenic bacteria can gain resistance. Reducing antibiotic resistance in bovine infections is a key part of any plan to slow resistance in human diseases. A two-stage mathematical model is constructed in order to find the most ideal combination of isolation, treatment, and culling that reduces the number of beef cattle with antibiotic resistance at the time of maturity. New legislation, starting in 2017, will restrict the use of antibiotics in cattle feed to veterinary prescription. To compare the impact of this legislation with current practices, an additional set of parameter values is used to simulate the dynamics of antibiotic resistance among beef cattle populations. Culling rates are shown to have a negligible effect, but quarantine rates of 0.5-1 per week lead to a decreased ABR rate. We find that under the new legislation the proportion of cattle with ABR at slaughter decreases by a statistically significant amount. In addition, the number of cattle colonized with antibiotic susceptible bacteria increases. However, the proportion of sellable cattle at the time of slaughter remains roughly the same.
Funder Acknowledgement(s): This project has been partially supported by grants from the National Science Foundation (DMS1263374), the Office of the President of ASU, and the Office of the Provost at ASU.
Faculty Advisor: Christopher Kribs, KRIBS@uta.edu
Role: Literature review, mathematical model development, parameter estimation, modifying Matlab and R codes used for numerical analysis, uncertainty quantification and sensitivity analysis, interpretation and application of results.