Muscle pH, rigor mortis and blood variables in Atlantic salmon transported in two types of well-boat.

Two systems for transporting live salmon (Salmo salar) were compared in terms of their effects on blood variables, muscle pH and rigor index: an 'open system' well-boat with recirculated sea water at 13.5 degrees C and a stocking density of 107 kg/m3 during an eight-hour journey, and a 'closed system' well-boat with water chilled from 16.7 to 2.1 degrees C and a stocking density of 243.7 kg/m3 during a seven-hour journey. Groups of 10 fish were sampled at each of four stages: in cages at the farm, in the well-boat after loading, in the well-boat after the journey and before unloading, and in the processing plant after they were pumped from the resting cages. At each sampling, the fish were stunned and bled by gill cutting. Blood samples were taken to measure lactate, osmolality, chloride, sodium, cortisol and glucose, and their muscle pH and rigor index were measured at death and three hours later. In the open system well-boat, the initial muscle pH of the fish decreased at each successive stage, and at the final stage they had a significantly lower initial muscle pH and more rapid onset of rigor than the fish transported on the closed system well-boat. At the final stage all the blood variables except glucose were significantly affected in the fish transported on both types of well-boat.

Evaluation of natural transmission of bovine leukaemia virus within dairy herds of Argentina.

The purpose of this study was to describe patterns of seroconversion to bovine leukaemia virus and to estimate the main parameters needed for future model building. A longitudinal study was carried out between February 1999 and November 2001 in seven commercial dairy farms in Argentina using 1535 lactating cows. Time-interval parameters were analysed using a parametric survival model with shared frailty, time until infection was analysed using a Bayesian interval-censoring survival model and the infection transmission parameter (beta) was estimated by a generalized linear model. The reproduction ratio (R0) was calculated. In total, 1000 cows tested positive and 494 tested negative. The predicted median age at infection was 4.6 years for seroconverted cows. For infected herds, the proportion of positive calves was as high as for infected cows and showed a large proportion of infected breeding heifers. Peaks in the overall average incidence per season-year were observed during autumn and spring. Results reveal that the period around parturition is a high-risk period. Moreover, heavily infected herds seem to have an increased proportion of young stock infected. The overall beta was estimated as 2.9/year (95% CI 1.9-3.7) and combined with a relatively long infectious period it resulted in a high reproductive ratio (R0=8.9). Therefore, a high effectiveness of control measures needs to be achieved to eradicate the disease.

Transmission of bovine leukaemia virus within dairy herds by simulation modelling.

In Argentina, bovine leukaemia virus (BLV) infection is common in dairy herds. The country currently has a National Voluntary Control Programme but relatively few farms have enrolled. However, there is increased interest from authorities and farmers to implement regional compulsory programmes but there is scarce quantitative information of the transmission of BLV in cattle herds. This information is a prerequisite to develop effective BLV control strategies. Mathematical modelling offers ways of integrating population-level knowledge and epidemiological data to predict the outcomes of intervention scenarios. The purpose of the current paper is to gain understanding about the dynamics of the transmission of BLV in dairy herds from Argentina by simulation and to compare various BLV transmission models and select the one that is most appropriate. The hypothetical herd is conceptually described in terms of BLV status as a population of individuals that are protected by maternal antibodies (M), that are susceptible (S), that are in the latent period (E) or that are infectious (I). BLV is spread by horizontal and vertical transmission. We used an age-structured population model and within-herd transmission was simulated by Monte Carlo techniques. The next-generation approach has been used for the systematic computation of the basic reproduction ratio (R0). Parameter values for disease transmission were derived from previously published data; rates of entry, exit or transition between age groups were calculated based on our previous study, observational data, expert opinions and literature. With these parameter values the probability of a minor outbreak was estimated to be 10%, the probability of extinction was estimated as <0.001% and the expected time to extinction as more than 80 years. The probability of a minor outbreak and changes in prevalence were different when the index case was an adult cow compared to introduction by a heifer. Prediction of prevalences from MSI models fit the data satisfactorily. R0 was estimated as 9.5. The sensitivity analysis on R0 showed that all measures directed to reduce the transmission rate are potentially effective given operational control measures. An important prediction of these models is that, even in a relatively small, closed dairy herd, the time-scale for a BLV outbreak may be as long as several years and within-herd control of BLV requires intensive efforts.

Survival analysis on aggregate data to assess time to sero-conversion after experimental infection with Bovine Leukemia virus.

Bovine Leukemia virus (BLV) is a ubiquitous retrovirus that affects mainly cattle. Knowledge of the precise moment of infection is fundamental for identification and evaluation of factors related to BLV transmission. Systematic reviews and meta-analyses provide good evidence on the effects of medical interventions. The objectives were to estimate time to sero-conversion after experimental infection using data from retrieved literature and to detect factors that may influence the length of that interval using survival analysis on pooled data. An analysis using aggregate data from 36 studies totalling 438 observations was performed. From this, four sets were created and analysed by interval-censored accelerated failure time models (AFT) with different distributions (exponential, Weibull, log-logistic, lognormal and generalized gamma), and some variants of the Cox model (Andersen-Gill, smoothing splines) with and without a frailty effect. The AFT gamma model fit best and the estimated median time to sero-conversion in the null model was 57 days (95% confidence interval (CI): 49; 75) using all data and 47 days (95% CI: 39; 55) when only studies using experimental inoculation were considered. Some factors were consistently associated with time to sero-conversion. These included exposure by animal-to-animal contact (resulting in a seven-fold increase in time to sero-conversion compared to direct inoculation), diagnostic method to detect sero-conversion (time to sero-conversion was 1.4 times shorter when AGID was used compared to ELISA), and transmission by insect bites (biological media) delayed sero-conversion 2.3 times compared transmission via needles or other inanimate media. After fitting a frailty Cox model, results showed that sero-conversion in susceptible animals after infection using donors, in which presence of virus before the experiment started was confirmed, increased the hazard of sero-conversion two times in comparison with donors in which virus presence was not confirmed before start of the experiment. Inoculation with blood decreased the hazard 2.5 times in comparison with lymphocyte suspensions. Heterogeneity due to different research groups was also present. Finally, a Cox model with smoothing splines contained three variables: research group, route of inoculation and a non-linear spline for infective dose. In conclusion, it can be stated some factors that influence the time to sero-conversion were identified and quantified and that a moderate influence of research centre existed. These results may contribute to the estimation of the most probable times of infection in field conditions and in a better evaluation of control measures.