Background: Emerging animal and zoonotic diseases and increasing international trade have resulted in an increased demand for veterinary surveillance systems. However, human and financial resources available to support government veterinary services are becoming more and more limited in many countries world-wide. Intuitively, issues that present higher risks merit higher priority for surveillance resources as investments will yield higher benefit-cost ratios. The rapid rate of acceptance of this core concept of risk-based surveillance has outpaced the development of its theoretical and practical bases.

Incidence rates, and proportions of affected horses that retired or died as a result of injury or disorder varied with type of injury and age of horse. Horses returning to training after an initial MSI were at higher risk of subsequent MSIs and showed changes in duration of training preparations, but little change in starts per 100 training days or probability of placing in each start. MSIs in racing horses were less likely to be reported on the day of a race than at other times in the training preparation for all ages except 2-year-olds.

Retail live poultry markets (LPMs) may act as a reservoir of avian influenza viruses (AIV). In this study we test the hypothesis that a rest day in the LPMs where the stalls are completely emptied of poultry, cleansed, and restocked will reduce the isolation rates of avian influenza viruses. The isolation rate of H9N2 subtype viruses from chicken was significantly lower after the rest day than prior to it, indicating its impact in reducing transmission. In contrast, Newcastle disease virus (NDV) isolation rates appear unaffected by this intervention, possibly reflecting differences in herd immunity or virus transmission dynamics.

We used epidemiologic evaluation, molecular epidemiology, and a case-control study to identify possible risk factors for the spread of highly pathogenic avian influenza A virus (subtype H5N1) in chicken farms during the first quarter of 2002 in Hong Kong. Farm profiles, including stock sources, farm management, and biosecurity measures, were collected from 16 case and 46 control chicken farms by using a pretested questionnaire and personal interviews. The risk for influenza A (H5N1) infection was assessed by using adjusted odds ratios based on multivariate logistic regression analysis. Retail marketing of live poultry was implicated as the main source of exposure to infection on chicken farms in Hong Kong during this period. Infection control measures should be reviewed and upgraded as necessary to reduce the spread of influenza A (H5N1) related to live poultry markets, which are commonplace across Asia.

A case-control study of environmental and behavioural factors influencing foot lameness was undertaken on 62 dairy herds comprising an average of 185 milking cows in Taranaki, New Zealand. Thirty two case herds were identified as having had at least 10 per cent of the cows lame during the milking season in which the herd was studied, and thirty control herds were selected on the basis that no more than 3 per cent of cows in these herds had been lame per year for at least two years immediately prior to investigation. Each herd was visited at both a morning and an afternoon milking, and 58 risk factors were measured between the time the farmer began to assemble the cows for milking and the completion of milking. Comparison of single variables between case and control herds identified 24 which showed differences (p<0.10). These variables were then subjected to stepwise multivariate logistic regression, and statistically significant variables in this analysis were used to create a tentative path diagram of possible causal web relationships between the various risk factors and the outcome variable, the lameness prevalence level. Information from a review of the published literature was used to include further variables to the 24 into the initial (or null hypothesis) path model. Logistic path analysis was then used to eliminate non-significant paths from the diagram, leaving 19 arrows joining 13 variables in the final path diagram, compared with 33 joining 20 variables in the initial version. The most influential variables in explaining variation between case and control herds were the average level of maintenance of the track and the degree of patience shown by the farmer in bringing the cows in for milking. Overall, factors associated with the movement of animals to the milking shed explained 40 per cent of the variation (deviance) with regard to the lameness prevalence level. Risk factors associated with characteristics of the milking process explain 24 per cent, and risk factors associated with characteristics of the cows in the herd explain 9.5 per cent. Recommendations are made on management changes which deserve further investigation as ways of reducing lameness problems in dairy herds.