A model of the spread of the bovine viral-diarrhoea virus within a dairy herd

Wet BVDSim (a stochastic simulation model) was developed to study the dynamics of the spread of the bovine viral-diarrhoea virus (BVDV) within a dairy herd. This model took into account herd-management factors (common in several countries), which influence BVDV spread. BVDSim was designed as a discrete-entity and discrete-event simulation model. It relied on two processes defined at the individual-animal level, with interactions. The first process was a semi-Markov process and modelled the herd structure and dynamics (demography, herd management). The second process was a Markov process and modelled horizontal and vertical virus transmission. Because the horizontal transmission occurs by contacts (nose-to-nose) and indirectly, transmission varied with the separation of animals into subgroups. Vertical transmission resulted in birth of persistently infected (PI) calves. Other possible consequences of a BVDV infection during the pregnancy period were considered (pregnancy loss, immunity of calves). The outcomes of infection were modelled according to the stage of pregnancy at time of infection. BVDV pregnancy loss was followed either by culling or by a new artificial insemination depending on the modelled farmer’s decision. Consistency of the herd dynamics in the absence of any BVDV infection was verified. To explore the model behaviour, the virus spread was simulated over 10 years after the introduction of a near-calving PI heifer into a susceptible 38 cow herd. Different dynamics of the virus spread were simulated, from early clearance to persistence of the virus 10 years after its introduction. Sensitivity of the model to the uncertainty on transmission coefficient was analysed. Qualitative validation consisted in comparing the bulk-milk ELISA results over time in a sample of herds detected with a new infection with the ones derived from simulations.     

Losses over a 2-year period associated with fetal infection with the bovine viral diarrhea virus in a beef cow-calf herd in Saskatchewan.

In 1992, significant calf losses occurred between birth and weaning in a 650-cow Saskatchewan beef herd. These losses occurred subsequent to ill-thrift and disease, and every calf necropsied was found to be persistently infected with bovine viral diarrhea virus (BVDV). The objectives of this study were to describe the losses associated with fetal infection with BVDV in this herd and to determine why they occurred. For investigative purposes, blood samples were collected from the entire cow herd and the surviving calves at pregnancy testing in 1992, and tested by virus isolation for BVDV. Between 51 and 71 persistently infected calves were born in 1992. Bovine viral diarrhea virus was only isolated from calves. The only confirmed fetal infections with BVDV were recorded as the birth of persistently infected calves. However, abortions, reduced pregnancy rates, and delayed calvings were also recorded in the cow herd and may have been the result of fetal infections. The herd was monitored again in 1993. Fetal infections with BVDV were recorded as the birth of stunted, deformed, and persistently infected calves. The greatest losses due to fetal infection with BVDV in the 2 years of this study occurred in cows that were 3-years-old at calving (second calves). Bovine viral diarrhea virus appears to have remained endemic in this herd by transmission from persistently infected calves on young 3- and 4-year-old cows to naive calved 2-year-old cows that were mingled with them annually for rebreeding. Significant numbers of the 2-year-old cows remained naive to BVDV, because they were segregated from persistently infected calves at weaning, preventing cross-infection with BVDV.     

A stochastic model to assess the risk of introduction of bovine viral diarrhea virus to beef cow-calf herds

A spreadsheet model using Monte Carlo simulation was designed to evaluate the introduction of bovine viral diarrhea virus (BVDV) to cow-calf farms and the effect of different testing strategies. Risks were modeled to include imports to the cow-calf herd and stocker calves imported to adjacent pastures. The number of persistently infected (PI) animals imported and the probability of BVDV introduction were monitored for three herd sizes, four import profiles, and six testing strategies. Importing stockers and importing pregnant heifers were the biggest risks for introduction of BVDV. Testing for PI animals in stockers decreased the risk they posed, but testing pregnant heifers was not sufficient to decrease risk unless their calves were also tested. Test sensitivity was more influential than PI prevalence on the likelihood of BVDV introduction, when all imports were tested. This model predicts the risk of BVDV introduction for individual herds based on management decisions, and should prove to be a useful tool to help cow-calf producers in controlling the risk of importing BVDV to a na?ve herd.     

Periparturient infection with bovine viral diarrhea virus type 1 causes hemorrhagic proctocolitis in a cow

After 3 cows of a dairy herd had died from severe hemorrhagic diarrhea, a 4th sick cow was transported to the clinic. Blood analyses revealed the complete absence of white blood cells, the presence of a type 1b strain of bovine viral diarrhea virus (BVDV), and seroconversion to BVDV.     

Pooled-sample testing as a herd-screening tool for detection of bovine viral diarrhea virus persistently infected cattle.

The study was conducted to develop methodology for least-cost strategies for using polymerase chain reaction (PCR)/probe testing of pooled blood samples to identify animals in a herd persistently infected with bovine viral diarrhea virus (BVDV). Cost was estimated for 5 protocols using Monte Carlo simulations for herd prevalences of BVDV persistent infection (BVDV-PI) ranging from 0.5% to 3%, assuming a cost for a PCR/probe test of $20. The protocol associated with the least cost per cow involved an initial testing of pools followed by repooling and testing of positive pools. For a herd prevalence of 1%, the least cost per cow was $2.64 (95% prediction interval = $1.72, $3.68), where pool sizes for the initial and repooled testing were 20 and 5 blood samples per pool, respectively. Optimization of the least cost for pooled-sample testing depended on how well a presumed prevalence of BVDV-PI approximated the true prevalence of BVDV infection in the herd. As prevalence increased beyond 3%, the least cost increased, thereby diminishing the competitive benefit of pooled testing. The protocols presented for sample pooling have general application to screening or surveillance using a sensitive diagnostic test to detect very low prevalence diseases or pathogens in flocks or herds.     

Economic consequences of immediate or delayed insemination of a cow in oestrus

Most dairy farmers are not certain whether immediate insemination or delaying the insemination is the best economic decision for a cow in oestrus. A model was developed for determining, based on herd and cow characteristics, the economic consequences of immediate or delayed insemination. The model was based on literature information and expert knowledge. In the model, the oestrus detection and conception rates were made cow-specific. The utility of the model was illustrated using a standard cow and data on 90 cows in oestrus (provided by 10 Dutch dairy farmers). The model suggested that for the majority of cows, the best decision is to immediately inseminate the cow in oestrus, but for most heifers with a flatter lactation curve the best decision was to delay the insemination. The economic effect of delaying the insemination was however small, on average -€18 per cow per year. Immediate insemination of an individual cow did result in relatively low economic benefits, but for a whole herd they can be substantial. This model can be used by farmers to help making the best economic decision for a cow in oestrus.     

The use of a mass-action model to validate the output from a stochastic simulation model of bovine viral diarrhoea virus spread in a closed dairy herd

The spread of bovine virus diarrhoea virus (BVDV) in a closed dairy herd maintained under typical management conditions is studied using two approaches. In the first instance a stochastic computer model is used to simulate the month-to-month changes in the infection status of each animal. These results are contrasted with the results of a mass-action model which uses three differential equations. A comparison of the two approaches indicates that the results are in broad agreement. The stochastic approach has the benefit of providing an estimate of the probability of the infection becoming extinct and the herd becoming BVDV-free for different herd sizes.     

Production and related variables in bovine leukaemia virus-infected cows

A newly developed milk dot blot test was used to detect anti-bovine leukaemia virus (BLV) antibody in milk samples from 2079 lactating adult cows from among 61 herds. The milk dot blot test was highly repeatable; the concordance rate, compared with the agar gel immunodiffusion test performed on serum, was 83.5%. All herds contained BLV-positive cows; the prevalence rate was 36%. BLV-positive cows tended to come from larger herds and were older and more often later in lactation. Fourteen production and related variables (herd size, age, days open, days in milk, milk somatic cell count, milk, fat, and protein produced in the current lactation, projected production of milk, fat, and protein, and breed class average deviations for milk, fat, and protein) were compared between BLV-positive and BLV-negative cows. Although somatic cell count, milk produced, and projected production of milk and protein were related significantly to BLV status using simple tests of association, once the variables herd size, age and days in milk were controlled, these differences were removed. Further analyses using logistic (outcome: individual cow BLV status) and least-squares regression (outcome:herd proportion of BLV-positive cows) failed to show an association between any of the measured production or related variables and BLV-positivity. We concluded that the effect of BLV on production and related variables in dairy cows was below the sensitivity of our analytical techniques or was non-existent.Abbreviations ABCA herd average breed class average for milk, fat, and protein production - AVGAGE average age of the herd - ADIM herd average for days in milk - AGID agar gel immunodiffusion - AVGSCC herd average milk somatic cell count - BCA breed class average, a milk, fat and protein production index calculated by comparing a cow's actual 305-day lactation production to the corresponding BCA standard for the same breed, age, and month of calving - BLV bovine leukaemia virus - CALVINT calving interval - COWAGE cow age - DBCA breed class average deviation for milk, fat, and protein production, the difference between an individual cow's BCA and the herd average - DIM days in milk - HS herd size corresponding to the number of lactating cows in a herd - LACT actual amount of milk, fat, and protein produced in a cow's lactation - ODHIC Ontario Dairy Herd Improvement Corporation - PCTPOS percentage of herd that is BLV-positive - PROJ projected 305-day production for milk, fat, and protein by fitting to a standard lactation curve adjusted for days in milk and age at calving - RHBCA rolling herd average for breed class average for milk, fat, and protein production, the average for all cows that completed a lactation (cows must have completed a 305-day lactation) during the previous 12 months - SCC milk somatic cell count     

Simulation study to assess the efficiency of a test-and-cull scheme to control the spread of the bovine viral-diarrhoea virus in a dairy herd

To control the spread of bovine viral-diarrhoea virus (BVDV), test-and-cull schemes have been used in Scandinavian countries, with success, when combined with strict control of new animal introductions into herds. In situations where BVDV reintroduction is likely to occur, it is necessary to assess precisely the expected efficiency of test-and-cull schemes. The objective of this study was to compare, by simulation, the persistence and consequences of BVDV infection in a fully susceptible dairy herd with either a test-and-cull scheme or no control action. We used a stochastic individual-based model representing the herd structure as groups of animals, herd dynamics, the contact structure within the herd and virus transmission. After an initial introduction of the virus into a fully susceptible herd, the frequency of purchases of animals that introduced the virus was simulated as high, intermediate or null. Virus persistence and epidemic size (total number of animals infected) were simulated over 10 years. The test-and-cull reduced the epidemic size and the number of days the virus was present except in herds with complete prevention of contact between groups of animals. Where no virus was reintroduced, virus persistence did not exceed 6 years with a test-and-cull scheme, whereas the virus was still present 10 years after the virus introduction in some replications with no control action (<2%). Where frequent purchases were made that led to virus introduction (6 within 10 years), with an intermediate virus transmission between groups, the probability of virus persistence 10 years after the first virus introduction fell from 31% to 8% with the test-and-cull scheme (compared to the do-nothing strategy). Within the newly infected herd, the test-and-cull scheme had no effect, on inspection, on the number of PI births, embryonic deaths or abortions over 10 years. Given this, the economic efficiency of the test-and-cull scheme should be further investigated.