scholarly journals Modeling the Effect of Bovine Viral Diarrhea Virus in Australian Beef Herds

2021 ◽  
Vol 8 ◽  
Author(s):  
Jake Fountain ◽  
Marta Hernandez-Jover ◽  
Carsten Kirkeby ◽  
Tariq Halasa ◽  
Jennifer Manyweathers ◽  
...  

Bovine viral diarrhea virus (BVDV) is an economically important disease in Australian beef farming. The disease typically results in low-level production losses that can be difficult to detect for several years. Simulation modeling can be used to support the decision to control BVDV; however, current BVDV simulation models do not adequately reflect the extensive farming environment of Australian beef production. Therefore, the objective of this study was to develop a disease simulation model to explore the impact of BVDV on beef cattle production in south-east Australia. A dynamic, individual-based, stochastic, discrete-time simulation model was created to simulate within-herd transmission of BVDV in a seasonal, self-replacing beef herd. We used the model to simulate the effect of herd size and BVDV introduction time on disease transmission and assessed the short- and long-term impact of BVDV on production outputs that influence the economic performance of beef farms. We found that BVDV can become established in a herd after a single PI introduction in 60% of cases, most frequently associated with the breeding period. The initial impact of BVDV will be more severe in smaller herds, although self-elimination is more likely in small herds than in larger herds, in which there is a 23% chance that the virus can persist for >15 years following a single incursion in a herd with 800 breeders. The number and weight of steers sold was reduced in the presence of BVDV and the results demonstrated that repeat incursions exacerbate long-term production losses, even when annual losses appear marginal. This model reflects the short- and long-term production losses attributed to BVDV in beef herds in southeast Australia and provides a foundation from which the influence and economic utility of BVDV prevention in Australian beef herds can be assessed.

2006 ◽  
Vol 44 ◽  
pp. S152 ◽  
Author(s):  
V. Bichko ◽  
M. LaColla ◽  
M.M. Tausek ◽  
L. Lallos ◽  
J. Gillum ◽  
...  

Viruses ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2431
Author(s):  
Yusuke Goto ◽  
Gakuji Yaegashi ◽  
Kazuhiro Fukunari ◽  
Tohru Suzuki

Bovine viral diarrhea virus (BVDV) infection results in a wide variety of clinical manifestations and is a pathogen that is able to cause huge economic losses in the cattle industry worldwide. It is important to identify cattle that are persistently infected (PI) by BVDV within the herd as early as possible because PI animals are the main reservoir of the virus. In contrast, cattle who are acutely infected (AI) with BVDV show various clinical signs, but most cattle show either mild symptoms or are asymptomatic. In general, AI and PI animals can be distinguished by repeat testing within an interval of at least 21 days. However, we found a rare case of a BVDV2-infected AI animal with long-term viral presence, making it indistinguishable from PI through two tests within an interval of 21 days. As a result, we diagnosed one infected animal as AI after 35 days from the initial sample collection via multiple analyses. Our findings recommend performing an additional test using samples that have been collected after 14–21 days from the second sample collection in cases where it is difficult to accurately differentiate an AI diagnosis from a PI diagnosis after only two tests. Additionally, our analysis exhibits that monitoring the number of copies of viruses with similar genomes in the sera by means of quantitative real-time RT-PCR through several sample collections periods might be useful to distinguish AI from PI. Furthermore, our data suggest that the AI animals with a long-term viral presence who show test results similar to those of PI animals might be the result of a coincidental combination of various factors that are present in cattle fields. These findings provide useful information that can be used to improve the diagnosis of BVDV in the field.


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