Inquiry of antibodies anti-Neospora caninum in dairy cattle, dogs and rural workers of the south-west region of Mato Grosso State

Considering the importance of neosporosis in the animal health and production, the frequency of antibodies to Neospora caninum was evaluated in dairy cattle of the Southwestern region of Mato Grosso State, Brazil, in addition to serum samples obtained from dogs and humans living in the farms. A total of 1036 serum samples were analyzed, from which 932 were from dairy bovine females, 37 from dogs and 67 from humans, from 24 farms and examined by the indirect fluorescent antibody test (IFAT). Reactive human scrum samples were retested by Western-blotting to confirm the results. Antibodies to N. caninum were found in 499 cattle sera (53.5 %), with at least one positive in each farm, 25 dog sera (67.6 %) and seven human sera (10.5 %). There was no significant difference in the number of positive cattle sera according to age group. The results indicate a wide dissemination of N caninum in the studied region.

Applying statistical approaches in the dissection of genes versus environment for asthma and allergic disease

Now that some of the genes involved in asthma and allergy have been identified, interest is turning to how genetic predisposition interacts with exposure to environmental risk factors. These questions are best answered by studies in which both genotypes and other risk factors are measured, but even simpler studies, in which family history is used as a proxy for genotype, have made suggestive findings. For example, early breast feeding may increase the risk of allergic disease in genetically susceptible children, and decrease the risk of 'sporadic' allergy. This review also addresses the overall importance of genetic causes of allergic disease in the general population.

Solicitors disciplinary hearings in Queensland 1930-2000: a statistical analysis

This article reports on the results of a study undertaken by the author together with her research assistant, Heather Green. The study collected and analysed data from all disciplinary tribunal decisions heard in Queensland since 1930 in an attempt to provide empirical information which has previously been lacking. This article will outline the main features of the disciplinary system in Queensland, describe the research methodology used in the present study and then report on some findings from the study. Reported findings include a profile of solicitors who have appeared before a disciplinary hearing, the types of matters which have attracted formal discipline and the types of orders made by the tribunal. Much of the data is then presented on a time scale so as to reveal any changes over time.

The application of statistical process control charts to the detection and monitoring of hospital-acquired infections

The monitoring of infection control indicators including hospital-acquired infections is an established part of quality maintenance programmes in many health-care facilities. However, surveillance data use can be frustrated by the infrequent nature of many infections. Traditional methods of analysis often provide delayed identification of increasing infection occurrence, placing patients at preventable risk. The application of Shewhart, Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) statistical process control charts to the monitoring of indicator infections allows continuous real-time assessment. The Shewhart chart will detect large changes, while CUSUM and EWMA methods are more suited to recognition of small to moderate sustained change. When used together, Shewhart and EWMA methods are ideal for monitoring bacteraemia and multiresistant organism rates. Shewhart and CUSUM charts are suitable for surgical infection surveillance.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.