The Alberta Johne's Disease Initiative (AJDI) is a voluntary, management-based prevention and control program for Johne's disease (JD), a wasting disease in ruminants that causes substantial economic losses to the cattle industry. Despite extensive communication about the program's benefits and low cost to participating producers, approximately 35% of Alberta dairy farmers have not enrolled in the AJDI. Therefore, the objective was to identify differences between AJDI nonparticipants and participants that may influence enrollment. Standardized questionnaires were conducted in person on 163 farms not participating and 61 farms participating in the AJDI. Data collected included demographic characteristics, internal factors (e.g., attitudes and beliefs of the farmer toward JD and the AJDI), external factors (e.g., farmers' JD knowledge and on-farm goals and constraints), as well as farmers' use and influence of various information sources. Nonparticipants and participants differed in at least some aspects of all studied categories. Based on logistic regression, participating farms had larger herds, higher self-assessed knowledge of JD, better understanding of AJDI details before participation, and used their veterinarian more often to get information about new management practices and technologies when compared with nonparticipants. In contrast, nonparticipants indicated that time was a major on-farm constraint and that participation in the AJDI would take too much time. They also indicated that they preferred to wait and see how the program worked on other farms before they participated.

Mycobacterium avium subspecies paratuberculosis (MAP) causes chronic progressive enteritis in ruminants. The pathogen is present in most countries with modern dairy production, causing substantial economic losses for the industry. The objectives of this study were to estimate dairy herd prevalence of MAP in the Western Canadian provinces of Alberta and Saskatchewan, and to determine whether herd size and housing system (tie-stall versus freestall or loose housing) affected the risk of a herd testing positive for MAP. Six environmental samples were collected on 360 Alberta farms (60% of registered producers) and on 166 Saskatchewan dairy farms (99%). In total, 47% of the sampled farms in Alberta and 53% of the sampled farms in Saskatchewan had at least one environmental sample that was MAP culture positive and were, therefore, defined as infected. Sensitivity of environmental sampling was estimated using 3 subsequent annual tests performed on 82 farms. Because laboratory protocols were continuously improved throughout the project, the sensitivity increased over time. Therefore, a mean of the sensitivity estimates weighted on sampling year was constructed; this resulted in sensitivities of 68 and 69% for Alberta and Saskatchewan, respectively. Implementing those estimates in an approximate Bayesian computation model resulted in a true herd prevalence of 68% (95% probability interval: 60-80%) for Alberta and 76% (95% probability interval: 70-85%) for Saskatchewan. Herds with >200 cows had 3.54 times higher odds of being environmental sample positive and had more positive samples than herds with <50 cows (neither province nor housing system affected those results). In conclusion, the majority of Alberta and Saskatchewan dairy farms were infected with MAP and larger herds were more often MAP positive than smaller herds.

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We propose a solution to the problem of finding an empirical therapy policy in a health care facility that minimizes the cumulative infected patient-days over a given time horizon. We assume that the parameters of the model are known and that when the policy is implemented, all patients receive the same treatment at a given time. We model the emergence and spread of antimicrobial resistance at the population level with the stochastic version of a compartmental model. The model features two drugs and the possibility of double resistance. Our solution method is a variant of the Monte-Carlo tree search algorithm. In our example, this method allows to reduce the cumulative infected patient-days over two years by 22% compared to the best standard therapy.