Bovine viral diarrhoea virus (BVDV) impacts health and performance of bovine herds. In the present retrospective study, the impact of BVDV control on production performance of suckler herds was tested, using vaccination of all female cows of the herd on the same day (DV). Performance of cows of two commercial suckler herds was analysed during 12 months before DV (PREVAC, n = 497 cows) and during 9 to 21 months after vaccination (POSTVAC, n = 531 cows). The proportion of calves born compared to the initial number of cows subjected to mating did not differ (PREVAC and POSTVAC, 87% and 84% respectively, P = 0.3584). Neither did the proportion of calves weaned compared to the initial number of cows subjected to mating (P = 0.2928) between PREVAC (71%) and POSTVAC (74%). However, the proportion of calves weaned compared to the number of calves born was higher POSTVAC (87%) when compared to PREVAC (81%), (P = 0.0223). Thus, data demonstrate that a BVDV control programme using vaccination in suckler herds, can improve calf survival.
Short Report
The evaluation of production parameters in BVDV endemically infected bovine suckler herds after implementation of a BVDV eradication strategy including vaccination
https://doi.org/10.21203/rs.3.rs-5117244/v1
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BVD
beef
productivity
vaccine
Bovela®
Bovine viral diarrhoea (BVD), caused by BVD virus (BVDV), is endemic in many countries. The basis for seeking BVDV freedom is economic, as well as on welfare grounds, and to promote proactive rather than reactive disease control with associated increased antibiotic use. Control depends on removal of persistently infected (PI) animals, and maintenance of biosecurity to ensure no new PIs are born. Vaccination of pregnant and future pregnant animals to prevent PI formation has been proven to be a successful biosecurity tool (Albrecht et al. 2021).
BVDV control is more successful in dairy than suckler herds for several reasons (Amelung et al. 2018). Suckler herds graze more extensively, and there is intense contact between pregnant dams and young calves, so facilitating virus spread between PIs and pregnant cows. The motivation for farmers to eradicate BVDV is influenced by cost-benefit analyses. Literature provides multiple studies that indicate the economic benefits of BVDV eradication schemes (Yarnall and Thrusfield 2017, Schmitt-van de Leemput et al. 2020). However, the evidence in suckler herds is more scarce than dairy herds.
Therefore, the aim of this study is to add information to the existing literature on economic benefits of BVDV control programmes in suckler herds by comparing key performance indicators (KPIs) in BVDV endemically-infected beef suckler herds before and after implementation of a BVDV eradication strategy including vaccination with a live double-deleted BVDV vaccine (Bovela®). The productive performance of herds before and after implementation of a BVDV eradication strategy including vaccination (BESIV) will be compared by the use of retrospective data analyses. To evaluate productive performance several KPIs, specially developed for suckler herds, will be used (Hewitt 2021).
The study will contribute to the understanding of the impact of endemic BVDV infection on the performance of extensive suckler herds, and demonstrate the benefit of BESIV under these conditions.
Study design
This is an observational, retrospective study using individual cows as the experimental unit. The performance of herds were compared before and after BESIV. Data were collected from the periods before and after vaccination with “Bovela®”, as part of the BESIV (Fig. 1). In herds, the initial non-vaccinated animals served as the control group for the subsequently vaccinated animals. Thus, a comparison was made between the initial herd, endemically infected with BVDV and the same herd during the subsequent BVD-free breeding period, reduced in size by culled cows and increased in size by calving heifers. Herds were maintained under the same conditions other than implementation of vaccination.
Before vaccination (PREVAC) data were collected on the calves that were weaned during the 12 months before the day of vaccination (DV), along with data of their dams. After vaccination (POSTVAC) data were collected on the dams that calved from nine until 21 months after DV. Those animals and their calves were followed until weaning. This timeframe from vaccination to protection reflects a period to ensure calves were born from protected cows.
Vaccination, a single 2 ml intramuscular injection, of all pregnant and future pregnant animals at one farm was performed on the same day. Ethical approval was not required as vaccination was a veterinary recommendation.
The following data were collected for the periods PREVAC and POSTVAC: Number of cows subjected to mating, number of calves born, date of birth of the calves, number of calves weaned from the calvings that took place, mortality at birth, and mortality between birth and weaning. The data were summarised in frequency tables or tables with descriptive statistics as appropriate.
Farm selection
Included in the study were European commercial suckler herds endemically infected with BVDV at the start of the BESIV. For each of the herds, the proof of BVDV circulation was characterised by one of three descriptions:
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Presence of an identified PI for a minimum of six months
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Evidence of the birth of a PI from a cow mated at the farm
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Proof of seroconversion against BVDV during serological surveillance or other testing.
The components of the BESIV protocol, such as the diagnosis and exclusions of PIs and sanitary measures, were the choice of the farmer in consultation with their veterinarian. However, for this retrospective analysis, yearly vaccination with "Bovela®“ lyophilisate and solvent for suspension for injection for cattle of all pregnant and future pregnant animals at one certain day (DV) was a mandatory inclusion factor. Data were collected during the PREVAC and POSTVAC period (Fig. 1) from farm records and or national databases.
Statistical analysis of data
The main objective of the statistical analysis was the comparison of the performance of the herds after (POSTVAC) and before (PREVAC) the BESIV and the impact on the success or otherwise of breeding and rearing of calves. The statistical analyses were performed using SAS software release 9.4 (SAS, 2016, Cary, North Carolina, USA: SAS Institute Inc.).
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The following variables were subjected to the statistical evaluation:
The following hypotheses were tested for the outcome variables:
H0: PREVAC = POSTVAC
H1: PREVAC ≠ POSTVAC
These tests on differences between the study groups were designed as two-sided tests for a type I error level of α = 0.05 (5%). The data were evaluated for each country/farm separately and for countries pooled stratified by 'country'. Qualitative interactions between countries were tested using the Gail-Simon test. Groups were tested on differences for each country using Fisher's exact test and for the pooled data using the Cochran-Mantel-Haenszel test stratified by 'country'.
Initially, eight suckler herds eligible for inclusion were identified in four different European countries. The selected farms represented 928 cows in the PREVAC period and 952 cows in the POSTVAC period. Unfortunately, the required complete dataset was available for only two of the farms. At six of the eight farms, the number of females put to mating was not complete for the periods being studied, which overlapped multiple seasonal breeding periods.
A descriptive analysis of the data is shown in Table 1. The target sample size of 628 animals was still exceeded, assuming 80% weaned control calves per mated cow, a 5% improvement following intervention, 5% variance, 95% confidence level and 80% power. Depicted are the individual data of the two herds and then the overall data of all animals included in the study. The qualitative interactions between the herds/countries were found to be not significant (P > 0.05) in all cases (Table 2). Therefore, for further analyses of the data, the overall data were used. A total number of 497 and 531 cows, in the PREVAC and POSTVAC group, respectively, were subjected to mating and gave birth to 432 (87%, PREVAC) and 447 (84%, POSTVAC) calves: 10 (PREVAC) and 16 (POSTVAC) calves were stillborn. From the calves that were born alive in the PREVAC period, 352 survived until weaning (83%). For the calves born alive in the POSTVAC period, this number was 391 (91%).
In our study, the NPIs were not statistically different between the PREVAC (71%) and POSTVAC (74%) groups (Table 2; P = 0.3283). Interestingly, in our study, the calving rate, 87% (PREVAC) and 84% (POSTVAC), did not differ between the groups (P = 0.251, Table 2). However the total pre-weaning survival rate was higher in the POSTVAC group (87%) when compared to the PREVAC group (81%) (P = 0.0223, Table 2). The pre-weaning survival rate of alive-born calves was significantly greater for the POSTVAC group (91%) compared to the PREVAC group (83%) (P = 0.0023).
| Country | Group | Number of cows subjected to mating | Total number of calves born | Number of calves born alive | Number of calves weaned | Calving rate %* | Total pre- weaning survival rate %** | Pre-weaning survival rate of alive-born calves*** | Numeric production index**** |
|---|---|---|---|---|---|---|---|---|---|
| France | PREVAC | 161 | 130 | 126 | 119 | 81 | 92 | 94 | 74 |
| POSTVAC | 192 | 158 | 142 | 141 | 82 | 89 | 99 | 73 | |
| Spain | PREVAC | 336 | 302 | 296 | 233 | 90 | 77 | 79 | 69 |
| POSTVAC | 339 | 289 | 289 | 250 | 85 | 87 | 87 | 74 | |
| Overall Data | PREVAC | 497 | 432 | 422 | 352 | 87 | 81 | 83 | 71 |
| POSTVAC | 531 | 447 | 431 | 391 | 84 | 87 | 91 | 74 | |
| *Calving rate: (Number of calves born / number of cows subjected to mating)*100 | |||||||||
| ** Total Pre-weaning survival rate: (Number of calves weaned / number of calves born)*100 | |||||||||
| *** Pre-weaning survival rate of alive-born calves: (Number of calves weaned / (number of calves born - number of calves experiencing stillbirth))*100 | |||||||||
| **** Numeric production index: (number of calves weaned / number of cows subjected to mating)*100 | |||||||||
| Numeric Production Index* | Nweaned | %weaned | 95% CI | Nmatings | p | ||
| PREVAC | 352 | 71 | 66.6 | 74.8 | 497 | 0.3283 | |
| POSTVAC | 391 | 74 | 69.7 | 77.3 | 531 | ||
| Calving index** | Nborn | %born | 95% CI | Nmatings | |||
| PREVAC | 432 | 87 | 83.6 | 89.8 | 497 | 0.2506 | |
| POSTVAC | 447 | 84 | 80.8 | 87.2 | 531 | ||
| Total pre-weaning survival rate*** | Nweaned | %weaned | 95% CI | Nborn | |||
| PREVAC | 352 | 81 | 77.5 | 85.0 | 432 | 0.0223 * | |
| POSTVAC | 391 | 87 | 84.0 | 90.4 | 447 | ||
| Pre-weaning survival rate of alive-born calves**** | Nweaned | %weaned | 95% CI | Nborn alive | |||
| PREVAC | 352 | 83 | 79.5 | 86.8 | 422 | 0.0023 ** | |
| POSTVAC | 391 | 91 | 87.6 | 93.3 | 431 | ||
| N: number of animals; CI: confidence interval | |||||||
| P: p-value of Fisher's exact test ('France', 'Spain') or Cochran-Mantel-Haenszel test ('pooled') of comparison between treatment groups, p-value of the Gail-Simon test on qualitative interactions in brackets | |||||||
| ns: not significant, P > 0.05; *: significant, P < 0.05; **: significant, P < 0.01 | |||||||
| *Numeric production index: (number of calves weaned / number of cows subjected to mating)*100 | |||||||
| **Calving rate: (Number of calves born / number of cows subjected to mating)*100 | |||||||
| *** Total Pre-weaning survival rate: (Number of calves weaned / number of calves born)*100 | |||||||
| **** Pre-weaning survival rate of alive-born calves : Number of alive weaned calves / (number of calves born – number of calves experiencing stillbirth)*100 | |||||||
In six of eight of the farms eligible for inclusion, the number of cows subjected to mating was not registered thus reproduction parameters were unknown. These parameters are important performance indicators that should guide farmers in their farm management.
In our study, there was no difference in NPI before and after implementation of the BESIV. This KPI is constituted of two different parameters: the calving rate and total pre-weaning survival rate. It is perhaps surprising that the calving rate did not differ. A non-successful mating can be a result of poor fertility or embryonic mortality or abortion. Vaccination should have protected animals of the POSTVAC group from embryonic mortality or abortion due to BVDV. However, it is possible that endemic BVDV before the DV altered the development of oocytes and further on fertility. Previous studies suggest that BVDV influences oocyte physiology and can alter their function and fertility of cows (Lanyon et al. 2014, Burgstaller et al. 2016). It is possible that the cows in the POSTVAC group still suffered from reduced ovarian function due to recent BVDV exposure.
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The total pre-weaning survival rate did differ between groups. Calf survival was higher in the POSTVAC group. Differences in number of calves weaned will probably be due to prevention of the birth of PIs through use of “Bovela®”, but also to less calves dying due to secondary diseases such as scour and BRD (Laynon et al. 2014).
In our study, the farmers and their veterinarians chose the components of the eradication program, however vaccination with "Bovela®“ was a mandatory inclusion factor. The vaccination component is important. Firstly because of study design as vaccination of the whole herd on DV marks a clear start of BVDV protection. However, it is also an important biosecurity measure, especially in beef farms. Suckler herds graze on widespread areas and sanitary boundaries are difficult to maintain. Therefore, transient or permanent infection, even after PI extinction, cannot be excluded.
For further research, in order to predict potential economic benefits of BVDV eradication for a suckler herd, it would be interesting to use the increased calf survival demonstrated as a parameter into an overall economic model, as proposed by numerous publications (Thomann et al. 2017, Yarnall and Thrusfield 2017). Based on this data, an increase of 6% of weaned calves at 250kg in a 100 calved-cow herd would return €6000, using local live weight prices at €3.6 per kg, minus vaccination cost. To apply these models at individual farm situations, data registration should be professionalised.
To conclude, the study suggests that eradication of BVDV on beef suckler farms, using vaccination with a live double-deleted BVD vaccine, can increase calf survival. In order to predict overall economic benefits of BVDV eradication, the parameter of increased calf survival could be integrated into an overall economic model.
Acknowledgements
We gratefully thank the participating veterinary practitioners, including Eusebio Clemente, María Gutierrez and Alejandro Gonzalez, and farmers for their collaboration.
Ethics approval
Not applicable, farming practices.
Data availability statement
Data available to reviewers upon request.
Declaration of interest
M. Yarnall, M. Cerviño, R. Prieto and A. Bolon are employed by Boehringer Ingelheim and E. Schmitt–van de Leemput was employed as coordinating investigator of the study by Boehringer Ingelheim.
Financial support statement
This study was funded by Boehringer Ingelheim Animal Health.
Author contributions
M. Yarnall: Conceptualisation, Methodology, Formal analysis, Funding acquisition, Project administration, Project Writing - Review & Editing, Supervision
E. Schmitt–van de Leemput: Conceptualisation, Methodology, Data curation, Formal analysis, Writing - Original Draft, Writing - Review & Editing
M. Cerviño: Methodology, Data acquisition, Project Writing - Review & Editing
R. Prieto: Data acquisition, Project Writing - Review & Editing
A. Bolon: Methodology, Data acquisition, Project Writing - Review & Editing
BVDV Bovine viral diarrhoea virus
BESIV BVDV eradication strategy including vaccination
DV Day of vaccination
KPI Key performance indicator
NPI Numeric production index
PREVAC Data collection period (12 months before DV) of the animals before vaccination
POSTVAC Data collection period (nine to 21 months after DV) of the animals after vaccination
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Competing interest reported. M. Yarnall, M. Cerviño, R. Prieto and A. Bolon are employed by Boehringer Ingelheim and E. Schmitt–van de Leemput was employed as coordinating investigator of the study by Boehringer Ingelheim.