Regional risk of exporting cattle seropositive for bluetongue virus from the United States

OBJECTIVE: To create a stochastic model to quantify the risk that shipments of cattle from regions within the United States would contain animals seropositive for bluetongue virus and to determine shipment-level accuracy of serologic testing by use of a competitive ELISA (c-ELISA). SAMPLE POPULATION: 19,216 shipments containing 528,918 cattle and calves. PROCEDURE: Data were obtained on number of animals and state of origin of cattle in export shipments originating within the United States between January 1994 and March 2002. Probability distributions for size of export shipments were determined for all states within the United States, and distributions for agar gel immunodiffusion and c-ELISA accuracy (sensitivity and specificity) were determined from expert opinion and review of the literature. The model simulated selection of a shipment and then determined the probability that a threshold number or percentage of cattle within that shipment would have a positive c-ELISA result. Shipment-level sensitivity, specificity, positive-predictive value, and negative-predictive value were calculated. RESULTS: Substantial differences were evident in the regional probability of a shipment being declared positive, with shipments from northeastern states having the lowest probability and shipments from southwestern states having the highest probability. The c-ELISA had variable predictive values at the shipment level, depending on the threshold used and the prevalence of antibody-positive cattle within the region. CONCLUSIONS AND CLINICAL RELEVANCE: Results from this study will aid importers in making scientifically based decisions regarding risk of importing antibody-positive cattle.     

Management of drug-resistant cyathostominosis on a breeding farm in central North Carolina

REASONS FOR PERFORMING STUDY: Possible anthelmintic resistance on a breeding farm where a rapid rotation anthelmintic programme had been implemented for 9 years was investigated. Cyathostomins resistant to fenbendazole and pyrantel were documented by faecal worm egg count reduction test (FWECRT). OBJECTIVES: To 1) manage small strongyle transmission in a herd of horses in which resistance to both pyrantel pamoate and fenbendazole was identified and thereby reduce the risk of clinical disease in the individual animal, 2) monitor the change in resistance patterns over time and 3) monitor the efficacy of ivermectin over the study period. METHODS: Targeted ivermectin treatment of horses on the farm was instituted for mature horses with faecal worm egg counts (FWEC) > 200 eggs/g (epg) and for horses < age 2 years with FWEC > 100 epg. RESULTS: Over a 30 month period, targeted ivermectin treatment achieved acceptable control in mares, as judged by FWEC, and improved control of patent cyathostome infection in consecutive foal crops. Egg reappearance time (ERT) after treatment with ivermectin was < 8 weeks in mares and foals more frequently in the second year of the study than in the first year. Numbers of anthelmintic treatments were reduced by 77.6 and 533% in the mare and foal group, respectively. CONCLUSIONS: Targeted ivermectin treatment may be an economically viable method of managing multiple drug resistant cyathostominosis. POTENTIAL RELEVANCE: Use of ivermectin should be monitored closely for development of resistance.     

Hierarchical Bayesian model for prevalence inferences and determination of a country's status for an animal pathogen

Certification that a country, region or state is "free" from a pathogen or has a prevalence less than a threshold value has implications for trade in animals and animal products. We develop a Bayesian model for assessment of (i) the probability that a country is "free" of or has an animal pathogen, (ii) the proportion of infected herds in an infected country, and (iii) the within-herd prevalence in infected herds. The model uses test results from animals sampled in a two-stage cluster sample of herds within a country. Model parameters are estimated using modern Markov-chain Monte Carlo methods. We demonstrate our approach using published data from surveys of Newcastle disease and porcine reproductive and respiratory syndrome in Switzerland, and for three simulated data sets.     

Mortality and recovery of runt white sturgeon (Acipenser transmontanus) in a commercial farm in California, USA

We investigated the effect of raising runt white sturgeon (Acipenser transmontanus) separately from dominant fish during the initial stages of grow-out in a commercial farm. Runt fish are poor-growers, have underdeveloped muscle mass, swim slowly and are more-frequently found at the top of the water column. The objective of the study was to describe the mortality and recovery rates (and their determinants) of white-sturgeon runts after separating them from dominant fish. Runt white sturgeon were stocked into twelve 2 m × 2 m rectangular tanks and graded periodically during a follow-up of 46–102 days. Overall mortality rates ranged from 0.3 to 7 dead fish per 1000 sturgeon-days at risk and overall recovery rates from 3.9 to 13.5 recovered fish per 1000 sturgeon-days at risk. Period-specific mortality and recovery rates increased over time. The period-specific mortality rates for all three periods were significantly higher for tanks of runts originating from grow-out tanks with high mortality (p-values: first period = 0.06; second period = 0.09; third period = 0.03), but were similar for tanks of runts of high- and low-mean initial weight. The period-specific recovery rates were significantly higher in runts originating from high-mortality grow-out tanks only for the third period (p = 0.05) but not the first and second periods (p-values = 0.33 and 0.25, respectively). Recovery rates were significantly higher in the higher-mean-weight runts tanks for the first and third period but not for the second (p-values: first period = 0.02; second period = 0.65; third period = 0.06). We concluded that the proportion of runts that recover during a 46–89 day period is substantial (16–58%); therefore, it might be worthwhile growing such fish separately in a fish farm for about three months. Financial analysis showed that this practice was profitable, if the value of white sturgeon fish for the farm exceeded $2.05 per kg.     

Use of age and milk production data to improve the ability of enzyme-linked immunosorbent assay test results to predict Mycobacterium avium ssp. paratuberculosis fecal culture status.

Cows from 2 California dairies were tested for paratuberculosis at the end of lactation by using fecal culture and a commercially available serum enzyme-linked immunosorbent assay (ELISA) test kit. Individual cow characteristics and production variables were evaluated along with ELISA testing results as predictors of fecal culture status. In multivariable logistic regression analysis, age and a herd-standardized version of 305-day mature equivalent (305 ME) milk production were significant predictors of fecal culture status after adjusting for herd, quarter of the study year, and ELISA sample-to-positive (S/P) ratio. The area under a nonparametric receiver operating characteristic curve was significantly greater for a multivariable model that included age and the level of milk production when compared with a model without these covariates. In conclusion, consideration of cow-level covariates was useful as an aid in predicting Mycobacterium avium ssp. paratuberculosis (MAP) fecal culture status. For a given ELISA S/P ratio, older cows and those with lower 305 ME milk production relative to other cows in the herd were significantly more likely to be shedding MAP in their feces at the end of lactation.     

Comparison of the Sensitivity of Landscape-fire-succession Models to Variation in Terrain, Fuel Pattern, Climate and Weather

The purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer & wetter, and warmer & drier) and weather (year-to-year variability) was determined for four existing landscape-fire-succession models (EMBYR, FIRESCAPE, LANDSUM and SEM-LAND) and a new model implemented in the LAMOS modelling shell (LAMOS(DS)). Sensitivity was measured as the variance in area burned explained by each of the four factors, and all of the interactions amongst them, in a standard generalised linear modelling analysis. Modelled area burned was most sensitive to climate and variation in weather, with four models sensitive to each of these factors and three models sensitive to their interaction. Models generally exhibited a trend of increasing area burned from observed, through warmer and wetter, to warmer and drier climates with a 23-fold increase in area burned, on average, from the observed to the warmer, drier climate. Area burned was sensitive to terrain for FIRESCAPE and fuel pattern for EMBYR. These results demonstrate that the models are generally more sensitive to variation in climate and weather as compared with terrain complexity and fuel pattern, although the sensitivity to these latter factors in a small number of models demonstrates the importance of representing key processes. The models that represented fire ignition and spread in a relatively complex fashion were more sensitive to changes in all four factors because they explicitly simulate the processes that link these factors to area burned. The US Government's and the Canadian Government's right to retain a non-exclusive, royalty-free license is acknowledged