A stochastic risk-analysis model for the spread of bovine viral diarrhea virus after introduction to naive cow-calf herds

Department of Clinical Sciences, Kansas State University, Manhattan, KS 66502, USA.
Preventive Veterinary Medicine (Impact Factor: 2.17). 03/2010; 95(1-2):86-98. DOI: 10.1016/j.prevetmed.2010.02.009
Source: PubMed


A stochastic SIR model was developed to simulate the spread of bovine viral diarrhea virus (BVDV) through a cow-calf herd and estimate the effect of the virus on the herd, including abortions, calf morbidity, and calf mortality. The model was applied with three herd sizes (400, 100, and 50 head) and four control strategies (no intervention, vaccination of breeding stock, testing all calves pre-breeding and culling of persistently infected calves, and both vaccination of adults and testing and culling of calves). When no control strategy was implemented the BVDV reproductive rate (R(E-PI)) of persistently infected calves (PI's), vertical transmission rate from cows to calves and the mortality rate of PI's were influential in the number of PI's produced in the herd. When a vaccination program alone was implemented the vaccine efficacy was influential in the number of PI's produced in the herd. All control strategies decreased the effects of BVDV on the herd at both 1 and 10 years compared to no control. In most cases the combination of adult vaccination and calf testing and culling resulted in the largest decrease in the both the median and 95% prediction interval for the range of effects from BVDV. The effect of control strategies was most apparent in the 400 head herds. All control strategies increased the probability of early clearance of PI's from the herd for all herd sizes. Fifty and 100 head herds cleared infection by 4 and 9 years respectively even without a control program but 400 head herds did not always clear infection after 10 years unless a testing program was implemented. The model presented is valuable in assessing the effect of control strategies and the effects of disease parameters on BVDV spread in beef herds.

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    • "Virus may also be introduced from other farms at any stage, usually by contact with PI animals across a boundary fence (Stott et al., 2010). In the presence of exposure from other herds sharing fencelines or communal pasture, removing the source of the infection inside the herd (culling PI animals) may not solve the risk of infections (Smith et al., 2010). "
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    ABSTRACT: Bovine viral diarrhoea virus (BVDV) causes one of the most important diseases of cattle in terms of economic costs and welfare. The aims were to estimate herd prevalence and to investigate the factors associated with antibodies in bulk tank milk (BTM) in dairy herds through a matched case–control study. To estimate herd prevalence, BTM samples were randomly selected (n = 314) from a population (N = 1604). The true prevalence of BVDV was 24.3% (CI 95% = 20.1–29.3%). For the case–control study, BVDV antibody-positive herds (high antibody titres) were classified as cases (n = 21) and matched (n = 63) by milk production with herds presenting low antibody titres (ratio of 1 : 3). Three multivariable models were built: 1) full model, holding all 21 variables, and two models divided according to empirical knowledge and similarity among variables; 2) animal factor model; and 3) biosecurity model. The full model (model 1) identified: age as a culling criteria (OR = 0.10; CI 95% = 0.02–0.39; P < 0.01); farms that provided milk to other industries previously (OR = 4.13; CI 95% = 1.17–14.49; P = 0.02); and isolation paddocks for ill animals (OR = 0.14; CI 95% = 0.01–0.26; P = 0.02). The biosecurity model revealed a significant association with the use of natural mating (OR = 9.03; CI 95% = 2.14–38.03; P < 0.01); isolation paddocks for ill animals (OR = 0.06; CI 95% = 0.05–0.83; P = 0.03); years providing milk for the same industry (OR = 0.94; CI 95% = 0.91–0.97; P = 0.02); and direct contact over fences among cattle of neighbouring farms (OR = 5.78; CI 95% = 1.41–23.67; P = 0.04). We recommend the application of grouping predictors as a good choice for model building because it could lead to a better understanding of disease–exposure associations.
    Transboundary and Emerging Diseases 03/2014; DOI:10.1111/tbed.12219 · 2.94 Impact Factor
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    • "Validation of the model disease outputs was performed in Smith et al. (2010) using two published outbreaks involving 4 cow-calf herds in which the source of the virus could be inferred (Taylor et al., 1994; VanCampen et al., 2000). No published economic outcome is available to directly validate the economic outcomes of the model. "
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    ABSTRACT: A stochastic model was designed to calculate the cost-effectiveness of biosecurity strategies for bovine viral diarrhea virus (BVDV) in cow-calf herds. Possible sources of BVDV introduction considered were imported animals, including the calves of pregnant imports, and fenceline contact with infected herds, including stocker cattle raised in adjacent pastures. Spread of BVDV through the herd was modeled with a stochastic SIR model. Financial consequences of BVDV, including lost income, treatment costs, and the cost of biosecurity strategies, were calculated for 10 years, based on the risks of a herd with a user-defined import profile. Results indicate that importing pregnant animals and stockers increased the financial risk of BVDV. Strategic testing in combination with vaccination most decreased the risk of high-cost outbreaks in most herds. The choice of a biosecurity strategy was specific to the risks of a particular herd.
    Preventive Veterinary Medicine 12/2013; 113(4). DOI:10.1016/j.prevetmed.2013.11.013 · 2.17 Impact Factor
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    ABSTRACT: Objectives To describe management group (mob)-level seroprevalences and incidences of seroconversion to bovine viral diarrhoea virus (BVDV), and to determine the efficacy of a vaccine against BVDV, in beef heifers in commercial herds in Australia. Methods Seroprevalences were assessed in 38 mobs of beef heifers. Of them, 15 mobs that were considered to be at higher risk of BVDV transmission during the upcoming mating period underwent further serological monitoring, and were included in a double-blind controlled trial to assess vaccine efficacy. ResultsIn 66% of mobs, less than half the heifers were seropositive some months before mating start date. However, in only 2 mobs was the incidence of seroconversion during the mating period greater than 10%, with a very high incidence of seroconversion observed in only 1 mob. The pregnancy proportion in placebo-treated heifers in this mob was acceptable (89%), but a high proportion of placebo-treated heifers (26%) had persistently infected calves. The efficacy of the Pestigard® vaccine in preventing the birth of infected calves was estimated as 80%. Conclusions Outbreaks of serious BVDV-related disease are relatively uncommon in mobs of beef heifers, but when they occur, the impact can be large. This highlights the need to approach BVDV control from a risk-assessment perspective, where the likelihood and consequences of widespread BVDV infection in a mob are jointly assessed. Pestigard® vaccination of naïve heifers prior to mating reduces the risk of transplacental infection with BVDV if heifers are exposed to BVDV during early pregnancy.
    Australian Veterinary Journal 12/2013; 91(12). DOI:10.1111/avj.12129 · 1.05 Impact Factor
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