Journal of Dairy Science (Jul 2024)
Prevalence and spatial distribution of infectious diseases of dairy cattle in Ontario, Canada
Abstract
ABSTRACT: We investigated the prevalence and spatial distribution of selected pathogens associated with infectious diseases of dairy cattle in Ontario, Canada. The cross-sectional study surveyed bulk tank milk for antibodies against bovine leukemia virus (BLV), Mycobacterium avium ssp. paratuberculosis (MAP), and Salmonella Dublin, and for the presence of mastitis pathogens (Staphylococcus aureus, Streptococcus agalactiae, Mycoplasma bovis). Between October 2021 and June 2022, bulk tank milk samples were obtained from every commercial dairy farm in Ontario (n = 3,286). Samples underwent ELISA testing for the presence of BLV, MAP, and S. Dublin antibodies, and quantitative PCR testing for the detection of specific antigens of pathogens associated with mastitis. Bayesian models were used to estimate prevalence, and spatial analysis was carried out to identify regional clusters of high pathogen prevalence. Prevalence varied for different pathogens, and BLV was widespread across dairy farms in Ontario, with an estimated prevalence of 88.3%. The prevalence of MAP, Staph. aureus and S. Dublin in Ontario dairy herds was 39.8%, 31.5%, and 5.1%, respectively. The vast majority of dairy herds in Ontario were free of intramammary infections caused by Strep. agalactiae and M. bovis. Clusters of increased positive test rates were detected for S. Dublin, MAP, and Staph. aureus, indicating potential geographic risk factors for pathogen transmission. For S. Dublin, an area of increased test positivity rates was detected in southwestern Ontario, close to the Canada-United States border where most of the dairy herds in Ontario are located. Conversely, a localized cluster of positive test outcomes involving 14 subdivisions located in the southeastern region of Ontario was detected for Staph. aureus. Findings from our survey highlight the importance of the testing of aggregated samples and conducting spatial analysis as part of disease surveillance programs, and for implementing risk-based trading approaches among dairy producers.
