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Abstract

Salmonella Dublin is a cattle-adapted pathogen with major impacts on the dairy industry, including calf mortality, abortion, and reduced milk yield. Once introduced it can spread quickly and persist in herds due to asymptomatic carriers that intermittently shed the bacterium. This dissertation aimed to develop an understanding of S. Dublin within British Columbia and in doing so analyze the processes used for disease surveillance and investigation. A retrospective case-control using laboratory records found calves (0.5–6 months) were at highest risk for severe infections. S. Dublin primarily presented as a septicaemic disease with respiratory signs, and the lack of effective antemortem diagnostics likely leads to misdiagnosis and ineffective treatment. A cross-sectional study using bulk tank milk serology revealed S. Dublin is widespread across BC, with ~30% of farms testing positive. Larger herd size was associated with increased risk of S. Dublin positivity, suggesting large farms may be engaged in higher-risk practices. To further investigate risk factors, a Danish risk-scoring tools was adapted and applied to selected positive and negative farms. However, the tool failed to differentiate between farm S. Dublin status, suggesting risk dynamics may be multifactorial. Whole-genome sequencing of S. Dublin isolates from BC cattle showed that BC strains frequently clustered with US isolates, highlighting cattle importation as a possible route of introduction. A qualitative study guided by the Health Belief Model explored BC producers’ perceptions of S. Dublin. Overall, producers expressed uncertainty surrounding S. Dublin, specifically regarding its importance and the roles of stakeholders. Producer narratives and personal experiences often shaped their understanding of S. Dublin, suggesting that storytelling may be a powerful tool to improve engagement and knowledge translation. Ultimately, this dissertation demonstrated the strengths of current surveillance and investigation methods but also revealed important gaps in the dairy ‘health system’, such as a lack of data on animal movement among farms, an absence of cost-benefit analyses for different interventions, and uncertainly regarding the roles and responsibilities of different stakeholders. Principles from the ‘Learning Health Systems’ pioneered in the field of human health care could help to address some of these gaps.