Abstract View
Investigating Seasonal Effects on the Spread of Antibiotic Resistant Bacteria in Dairy Farms using Computational Fluid Dynamics
HYOUNGMOOK PAK, Maria King, Texas A&M University
Abstract Number: 431
Working Group: Bioaerosols
Abstract
Dairy farms are well known to harbor various bacteria species that could be pathogenic or resistant to antibiotics. Especially in a free stall dairy farm, these bacteria can disseminate into the open environment, causing nearby animals and people to be exposed to severe health risks. This study aimed to investigate the effects of seasonal factors on the development and spread of antibiotic resistant bacteria (ARB) in a dairy farm. Computational fluid dynamics (CFD) was utilized to assemble an airflow model and experimental air velocity measurements were taken and used for validation.
Two sampling campaigns at different seasons were taken to a dairy farm, which had about 400 cows and 36 axial fans, to measure air velocities and collect aerosolized bacteria at various locations. ANSYS was used to model the turbulent airflow patterns and experimental air velocity measurements were used to validate the CFD model. The airflow models at different seasons closely resembled their respective experimental results. Kirby-Bauer test revealed that bacteria on the southern side of the farm were most resistant to antibiotics, such as ampicillin, cephalothin, and tetracycline. Microbiome analysis was performed on the extracted bacterial DNA to determine which bacteria genus and species were present and carried antibiotic resistant genes. Seasonal factors, such as temperature and relative humidity, were observed to be triggering antibiotic resistant in aerosolized bacteria. On days of sampling, a southerly wind and wind generated by fans were shown to reintroduce certain ARB species back into the dairy farm. Principal coordinate analysis revealed that each seasonal factor had a significant and distinct effect on how ARB were being developed and disseminated in the dairy farm.