Pre-slaughter control of Escherichia coli O157 in beef cattle: a simulation study.

A stochastic simulation model was used to assess the benefit of measures implemented in the pre-slaughter period that are aimed at reducing the contamination of beef carcasses with Shiga-like-toxin-producing Escherichia coli O157. The scenario studied was based on an abattoir processing approximately 1000 head of lot-fed cattle per day. Input assumptions were described using probability distributions to reflect uncertainty in their true values. Control measures that were assessed were based on either a reduction in herd prevalence of infection, reduction in opportunity for cross-contamination in the processing plant by re-ordering of the slaughter queue, reduction of concentration of E. coli O157 in fresh faeces, or a reduction in the amount of faeces, mud and bedding ('tag') transferred from the hide to the carcass. Some control measures evaluated were hypothetical in nature and were included to assist with the planning of research priorities. Simulations suggested that the greatest potential impact is associated with vaccination and with an agent that reduces shedding E. coli O157 in faeces. Knowledge of herd-test results obtained by testing a sample of animals from the herd provides only a minor advantage in control programmes, although application of a rapid test to all animals in all lots might be of some benefit. Under most scenarios, there is ample opportunity for cross-contamination to occur within the slaughter plant as a result of early entry of cattle contaminated with E. coli O157. An industry-wide reduction in the amount of tag attached to hides and addition of a source of cattle having a prolonged average fasting time were not predicted to have a large impact on mean amount of carcass contamination with E. coli O157.     

The magnitude of reproductive wastage to lamb marking in 30 Merino flocks in south-west Queensland

Thirty groups of Merino ewes in 6 districts of south-west Queensland were studied between 1976 and 1985 to determine the magnitude of reproductive wastage to lamb making. Relatively high pregnancy rates (77 to 100%, mean 93%) and a wide range of lamb marking percentages (10 to 115%, mean 78%) were recorded. The mean reproductive wastage due to failure to mate and failure to lamb was low (1.6 and 3.4% respectively) in 8 flocks where harnessed rams were used. This indicated that loss of lambs from birth to lamb making was the major cause of reproductive wastage in most years.     

Development of an algorithm for assessing the risk to food safety posed by a new animal disease

An algorithm was developed as a tool to rapidly assess the potential for a new or emerging disease of livestock to adversely affect humans via consumption or handling of meat product, so that the risks and uncertainties can be understood and appropriate risk management and communication implemented. An algorithm describing the sequence of events from occurrence of the disease in livestock, release of the causative agent from an infected animal, contamination of fresh meat and then possible adverse effects in humans following meat handling and consumption was created. A list of questions complements the algorithm to help the assessors address the issues of concern at each step of the decision pathway. The algorithm was refined and validated through consultation with a panel of experts and a review group of animal health and food safety policy advisors via five case studies of potential emerging diseases of cattle. Tasks for model validation included describing the path taken in the algorithm and stating an outcome. Twenty-nine per cent of the 62 experts commented on the model, and one-third of those responding also completed the tasks required for model validation. The feedback from the panel of experts and the review group was used to further develop the tool and remove redundancies and ambiguities. There was agreement in the pathways and assessments for diseases in which the causative agent was well understood (for example, bovine pneumonia due to Mycoplasma bovis). The stated pathways and assessments of other diseases (for example, bovine Johne's disease) were not as consistent. The framework helps to promote objectivity by requiring questions to be answered sequentially and providing the opportunity to record consensus or differences of opinion. Areas for discussion and future investigation are highlighted by the points of diversion on the pathway taken by different assessors.     

Antimicrobial ratings: the importance of importance

Debate about antimicrobial resistance (AMR) in animals and the impact on humans is often inappropriately focussed on the crude amount of antimicrobials used in animals without deference to issues of ‘intensity of use’, ‘quality of use’ and especially the class of agents being administered. In the latter case, tools for helping to manage how the use of specific antimicrobial agents impact on the risk and consequences of antimicrobial resistance in humans have been available for almost two decades. These consist of antimicrobial ratings systems, which formally define the importance of each individual agent in human health by assigning them to a position on a graduated scale of ‘importance’ comprising up to four categories of risk. Until recently, these published ratings have only had a modest impact on antimicrobial stewardship at the frontline of medical and veterinary practice, although they will undoubtedly have a substantial influence into the future. This article considers the evolution of the available ‘antimicrobial ratings systems’ applicable to Australian and international settings and their pivotal future‐role in the educating of animal managers, policy makers and prescribers. Faithful application of these rating systems at all levels of decision making to do with antimicrobial use is now seen as central to the protection of animals, humans and economies from the scourge of AMR.     

Predicting Additive and Non-additive Genetic Effects from Trials Where Traits Are Affected by Interplot Competition

There are two key types of selection in a plant breeding program, namely selection of hybrids for potential commercial use and the selection of parents for use in future breeding. Oakey et al. (in Theoretical and Applied Genetics 113, 809–819, 2006) showed how both of these aims could be achieved using pedigree information in a mixed model analysis in order to partition genetic effects into additive and non-additive effects. Their approach was developed for field trial data subject to spatial variation. In this paper we extend the approach for data from trials subject to interplot competition. We show how the approach may be used to obtain predictions of pure stand additive and non-additive effects. We develop the methodology in the context of a single field trial using an example from an Australian sorghum breeding program.