Modelling transmission and control of Mycobacterium avium subspecies paratuberculosis within Irish dairy herds with compact spring calving

Calf rearing programs for the control of bovine Johne's disease (BJD) in dairy farms have been widely adopted globally and are based on evidence that the most significant risk factor for developing the disease is exposure of young calves to infectious doses of the causative organism Mycobacterium avium subsp. paratuberculosis (Mptb). Hygienic calf rearing practices aim to break the transmission cycle of Mptb by removing neonatal calves from their dams within 12h of birth and segregating replacement heifers from the herd until they are 12 months of age. But compliance with these interventions is difficult for many producers and delaying the removal of calves from their dams and earlier return of heifers to the herd are common practices. However, would changing these practices increase the risk of animals contracting BJD? Evidence for age susceptibility of calves and young adults to Mptb is reviewed. The experimental studies selected for inclusion in an analysis of the evidence were those designed specifically to address the issue and were confined to examination of 140 cattle in experiments conducted by eight groups of workers between the years 1938 and 2006. Approximately 75% of calves 12 months old developed lesions indicative of BJD infection when exposed to any of the tested routes of Mptb infection. No direct evidence was found to support the commonly held view that calf removal from the dam for a maximum period of 12h is preferable to 24h. However the studies did show that if exposure to infection occurs at birth, then the risk of infection progressing to BJD is high, particularly in a highly contaminated environment or if the dam is infected. Copyright 2009 Elsevier Ltd. All rights reserved.

Paratuberculosis (also called Johne's disease) is a chronic disease caused by Mycobacterium avium ssp. paratuberculosis (MAP) that affects ruminants and other animals. The epidemiology of paratuberculosis is complex and the clinical manifestations and economic impact of the disease in cattle can be variable depending on factors such as herd management, age, infection dose, and disease prevalence, among others. Additionally, considerable challenges are faced in the control of paratuberculosis in cattle, such as the lack of accurate and reliable diagnostic tests. Nevertheless, efforts are directed toward the control of this disease because it can cause substantial economic losses to the cattle industry mainly due to increased premature culling, replacement costs, decreased milk yield, reduced feed conversion efficiency, fertility problems, reduced slaughter values, and increased susceptibility to other diseases or conditions. The variability and uncertainty surrounding the estimations of paratuberculosis prevalence and impact influence the design, implementation, and efficiency of control programs in diverse areas of the world. This review covers important aspects of the economic impact and control of paratuberculosis, including challenges related to disease detection, estimations of the prevalence and economic effects of the disease, and the implementation of control programs. The control of paratuberculosis can improve animal health and welfare, increase productivity, reduce potential market problems, and increase overall business profitability. The benefits that can derive from the control of paratuberculosis need to be communicated to all industry stakeholders to promote the implementation of control programs. Moreover, if the suspected link between Johne's disease in ruminants and Crohn's disease in humans was established, significant economic losses could be expected, particularly for the dairy industry, making the control of this disease a priority across dairy industries internationally.

A stochastic budgetary simulation model of a dairy farm was developed to allow investigation of the effects of varying biological, technical, and physical processes on farm profitability. The model integrates animal inventory and valuation, milk supply, feed requirement, land and labor utilization, and economic analysis. A key model output is the estimated distribution of farm profitability, which is a function of total receipts from milk, calves, and cull cows less all variable and fixed costs (including an imputed cost for labor). An application of the model was demonstrated by modeling 2 calving patterns: a mean calving date of February 24 (S1) and a mean calving date of January 27 (S2). Monte Carlo simulation was used to determine the influence of variation in milk price, concentrate cost, and silage quality on farm profitability under each scenario. Model validation was conducted by comparing the results from the model against data collected from 21 commercial dairy farms. The net farm profit with S1 was 53,547 euros, and that with S2 was 51,687 euros; the annual EU milk quota was 468,000 kg, and farm size was 40 ha. Monte Carlo simulation showed that the S1 scenario was stochastically dominant over the S2 scenario. Sensitivity analyses showed that farm profit was most sensitive to changes in milk price. The partial coefficients of determination were 99.2, 0.7, and 0.1% for milk price, concentrate cost, and silage quality, respectively, in S1; the corresponding values in S2 were 97.6, 2.3, and 0.1%. Validations of the model showed that it could be used with confidence to study systems of milk production under Irish conditions.