The effect of bovine viral diarrhea virus introduction on milk production of Dutch dairy herds

Yue, Xiaomei; Steeneveld, W.; Voort, Mariska van der; Schaik, G. van; Vernooij, J.C.M.; Duijn, Linda van; Veldhuis, Anouk; Hogeveen, H.

doi:10.3168/jds.2020-18866

Cited by 9 publications

(9 citation statements)

References 30 publications

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“…Firstly, the average milk production and SCC in Lombardy were relatively high compared to other studies from different countries. For instance, the average milk production ranged from 23.2kg/d to 28.3 kg/d, and the average SCC ranged from 65,000 cells/mL to 105,000 cells/mL in the Netherlands [13,25]. The high milk production in Lombardy was due to several reasons.…”

Section: Discussionmentioning

confidence: 99%

Linear Mixed-effects model to quantify the association between somatic cell count and milk production in Italian dairy herds

Luo

Steeneveld

Nielen

et al. 2022

Preprint

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Milk production loss due to mastitis in dairy herds is economically important. Before estimating the economic impacts of mastitis, it is crucial to quantify the association between mastitis and milk production. The objective of this study was to estimate the association between somatic cell count (SCC, as an indicator of intramammary infection due to mastitis) and milk production for dairy cows in Lombardy (Italy). The test-day (TD) records data of 3,816 dairy herds located in 3 different geographical areas of Lombardy from January 2016 to December 2018 were used. After data editing, the final dataset comprised 10,445,464 TD records from 2,970 farms and 826,831 cows. The analysis was carried out by using a mixed-effects model with seven fixed effects (geographical area, breed, days in milk, parity, season and year) and nested random effects for each cow and herd. The results indicated that the SCC had a negative association with milk production. When the SCC increased every two-fold, the milk production lost 0.830 (95% CI: -0.832, -0.828) kg/cow/day in the whole Lombardy. These results can be used for economic calculations on the costs of mastitis.

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Section: Discussionmentioning

confidence: 99%

Linear Mixed-effects model to quantify the association between somatic cell count and milk production in Italian dairy herds

Luo

Steeneveld

Nielen

et al. 2022

Preprint

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“…On the other hand, if the antibody prevalence of case herds was relatively high before the BVDVfree certification, the changes in economic and production performance are likely to be small. The high antibody prevalence associated with lifelong immunity in the majority of the cows in the herd could protect the herd from serious negative effects (2,(55)(56)(57)(58). A possible way to define the infection status of case herds more precisely is to consider the BVDV test results prior to BVDV-free certification, such as the presence of (newborn) PI animals.…”

Section: Effectsmentioning

confidence: 99%

Estimating the Effect of a Bovine Viral Diarrhea Virus Control Program: An Empirical Study on the Performance of Dutch Dairy Herds

Yue

Voort

et al. 2022

Front. Vet. Sci.

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More and more European countries have implemented a bovine viral diarrhea virus (BVDV) control program. The economic effects of such programs have been evaluated in simulations, but empirical studies are lacking, especially in the final stage of the program. We investigated the economic (gross margin) and production effects (milk yield, somatic cell count, and calving interval) of the herds obtaining BVDV-free certification based on longitudinal annual accounting and herd performance data from Dutch dairy herds between 2014 and 2019, the final stages of the Dutch national BVDV-free program. This study was designed as a case-control study: two types of case herds were defined for two analyses. The case herds in the first analysis are herds where the BVDV status changed from “BVDV not free” to “BVDV free” during the study period. The not-free status refers to a herd that participated in the BVDV-free program but had not yet obtained the BVDV-free certification. In the second analysis, the case herds started participating in the Dutch BVDV-free program during the study period and obtained the BVDV-free certification. Control herds in both analyses were BVDV-free during the entire study period. Potential bias between the covariates of the two herd groups was reduced by matching case and control herds using the propensity score matching method. To compare the differences between case and control herds before and after BVDV-free certification, we used the time-varying Difference-in-Differences estimation (DID) methodology. The results indicate that there was no significant change in milk yield, somatic cell count, calving interval, and gross margin upon BVDV-free certification. There are several possible explanations for the non-significant effects observed in our study, such as the final stage of the BVDV control program, not knowing the true BVDV infection situation in case herds and not knowing if control measures were implemented in case herds prior to participating in the BVDV-free program. In our study, the effects of BVDV-free certification might have been underestimated, given that the Dutch BVDV control program became mandatory during the study period, and some of the case herds might have never experienced any BVDV infection. The results of this study suggest that in the final stage of the BVDV control program, the program may no longer have a clear benefit to the herd performance of participating dairy herds. When designing national programs to eradicate BVDV, it is therefore important to include incentives for such farms to motivate them to join the program.

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“…Two data sets were collected to quantify the effect of new BVDV introduction on the SCC, CIV, CR, and CMR of dairy herds. The first data set consists of longitudinal herd-level BVDV status data and was previously described in Veldhuis et al (2018) and Yue et al (2021b). The BVDV status data set includes 4,334 dairy herds that participated in the Dutch BVDVfree program between September 4, 2006, and June 15, 2016.…”

Section: Data Collectionmentioning

confidence: 99%

The effect of new bovine viral diarrhea virus introduction on somatic cell count, calving interval, culling, and calf mortality of dairy herds in the Dutch bovine viral diarrhea virus–free program

Yue

Voort

Steeneveld

et al. 2021

Journal of Dairy Science

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Bovine viral diarrhea virus (BVDV) infection has a major effect on the health of cows and consequently on herd performance. Many countries have implemented control or eradication programs to mitigate BVDV infection and its negative effects. These negative effects of BVDV infection on dairy herds are well documented, but there is much less information about the effects of new introduction of BVDV on dairy herds already participating in a BVDV control program. The objective of our study was to investigate the effect of a new BVDV introduction in BVDV-free herds participating in the Dutch BVDV-free program on herd performance. Longitudinal herd-level surveillance data were combined with herd information data to create 4 unique data sets, including a monthly test-day somatic cell count (SCC) data set, annual calving interval (CIV) and culling risk (CR) data sets, and a quarterly calf mortality rate (CMR) data set. Each database contained 2 types of herds: herds that remained BVDV free during the whole study period (defined as free herds), and herds that lost their BVDV-free status during the study period (defined as breakdown herds). The date of losing the BVDV-free status was defined as breakdown date.To compare breakdown herds with free herds, a random breakdown date was artificially generated for free herds by simple random sampling from the distribution of the breakdown month of the breakdown herds. The SCC and CIV before and after a new introduction of BVDV were compared through linear mixed-effects models with a Gaussian distribution, and the CR and CMR were modeled using a negative binomial distribution in generalized linear mixed-effects models. The explana-tory variables for all models included herd type, BVDV status, year, and a random herd effect. Herd size was included as an explanatory variable in the SCC, CIV, and CMR model. Season was included as an explanatory variable in the SCC and CMR model. Results showed that free herds have lower SCC, CR, CMR, and shorter CIV than the breakdown herds. Within the breakdown herds, the new BVDV introduction affected the SCC and CMR. In the year after BVDV introduction, the SCC was higher than that in the year before BVDV introduction, with a factor of 1.011 [2.5th to 97.5th percentile (95% PCTL): 1.002, 1.020]. Compared with the year before BVDV breakdown, the CMR in the year of breakdown and the year after breakdown was higher, with factors of 1.170 (95% PCTL: 1.120; 1.218) and 1.096 (95% PCTL: 1.048; 1.153), respectively. This study reveals that a new introduction of BVDV had a negative but on average relatively small effect on herd performance in herds participating in a BVDV control program.

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The effect of bovine viral diarrhea virus introduction on milk production of Dutch dairy herds

Cited by 9 publications

References 30 publications

Linear Mixed-effects model to quantify the association between somatic cell count and milk production in Italian dairy herds

Linear Mixed-effects model to quantify the association between somatic cell count and milk production in Italian dairy herds

Estimating the Effect of a Bovine Viral Diarrhea Virus Control Program: An Empirical Study on the Performance of Dutch Dairy Herds

The effect of new bovine viral diarrhea virus introduction on somatic cell count, calving interval, culling, and calf mortality of dairy herds in the Dutch bovine viral diarrhea virus–free program

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