Temporal trends in bulk tank milk antibody ELISA and PCR test results for bovine viral diarrhoea in New Zealand pastoral dairy herds

Bovine viral diarrhoea viruses from New Zealand belong predominantly to the BVDV-1a genotype

AIM

To determine which genotypes of bovine viral diarrhoea virus (BVDV) circulate among cattle in New Zealand.

METHODS

Samples comprised BVDV-1-positive sera sourced from submissions to veterinary diagnostic laboratories in 2019 (n = 25), 2020 (n = 59) and 2022 (n = 74) from both beef and dairy herds, as well as archival BVDV-1 isolates (n = 5). Fragments of the 5' untranslated region (5' UTR) and glycoprotein E2 coding sequence of the BVDV genome were amplified and sequenced. The sequences were aligned to each other and to international BVDV-1 sequences to determine their similarities and phylogenetic relationships. The 5' UTR sequences were also used to create genetic haplotype networks to determine if they were correlated with selected traits (location, type of farm, and year of collection).

RESULTS

The 5' UTR sequences from New Zealand BVDV were closely related to each other, with pairwise identities between 89% and 100%. All clustered together and were designated as BVDV-1a (n = 144) or BVDV-1c (n = 5). There was no evidence of a correlation between the 5' UTR sequence and the geographical origin within the country, year of collection or the type of farm. Partial E2 sequences from New Zealand BVDV (n = 76) showed 74-100% identity to each other and clustered in two main groups. The subtype assignment based on the E2 sequence was the same as based on the 5' UTR analysis. This is the first comprehensive analysis of genomic variability of contemporary New Zealand BVDV based on the analysis of the non-coding (5' UTR) and coding (E2) sequences.

CONCLUSIONS AND CLINICAL RELEVANCE

Knowledge of the diversity of the viruses circulating in the country is a prerequisite for the development of effective control strategies, including a selection of suitable vaccines. The data presented suggest that New Zealand BVDV are relatively homogeneous, which should facilitate eradication efforts including selection or development of the most suitable vaccines.

Milk as a diagnostic fluid to monitor viral diseases in dairy cattle

BACKGROUND

Infectious viral diseases in dairy cattle have substantial implications for milk production, quality and overall animal health. Diagnostic tools providing reliable results are crucial for effective disease control at the farm and industry level. Pooled or bulk tank milk (BTM) can be used as a cost-effective aggregate sample to assess herd disease status in dairy farms.

FINDINGS

Detection of pathogens or specific antibodies in milk can be used for monitoring endemic diseases within-farm, region or country-level disease surveillance and to make informed decisions on farm management. The suitability of assays applied to pooled milk samples relies on validation data of fit-for-purpose tests to design an optimal testing strategy. Diverse approaches and variable scope of studies determining test accuracy need to be critically appraised before sourcing the parameters to design sampling strategies and interpreting surveys. Determining if BTM or pooled milk is the best approach for a disease management programme should carefully consider several aspects that will impact the accuracy and interpretation, for example, the size of the lactating herd, the risk of infection in the lactating and non-lactating groups, the expected within-herd prevalence, the duration of infection, the duration and concentration of antibodies in milk and use of vaccination.

CONCLUSIONS

There are examples of tests on BTM samples providing efficient assessments of the herd disease status and supporting disease control programmes for viral diseases. However, challenges arise in pooled milk testing due to the need for accurate estimates of the imperfect sensitivity and specificity of the assays. Integration of new biotechnologies could enhance multiplexing and data interpretation for comprehensive surveillance. The development of highly sensitive assays is necessary to meet the demands of larger dairy herds and improve disease detection and assessment.

Evaluation and application of a milk antibody ELISA for assessing the prevalence and incidence of bovine tuberculosis in dairy herds in Hubei Province, China

Bovine tuberculosis (bTB) is a chronic zoonotic disease that is endemic in China. Current in-vitro tests for bTB are mainly based on blood assays. Collection of samples results in some stress to the sampled cattle and associated economic losses for the herd owner. This study was designed to investigate the relationship between milk and serum antibody tests for bTB in dairy cows using 85 cows with milk and corresponding blood samples. Totally 4,395 milk samples were used to assesse the apparent (test) prevalence and incidence of bTB using the milk antibody ELISA. The association between levels of bTB milk antibody and milk quality was also evaluated. Milk and serum antibody tests showed a good correlation with a 87.5% (95% CI: 61.7%, 98.4) positive agreement and 98.7% (95% CI: 95.4, 99.8) negative agreement. The animal level lactoprevalence ranged from 0.3% (95% CI: 0, 1.2) to 33.3% (95% CI: 26.6, 40.6) in different farms and the incidence rate ranged from 0 head/cow-month (95% CI: 0, 0.02) to 0.04 head/cow-month (95% CI: 0.02, 0.07). Twenty percent of sampled farms met the criteria for bTB control in China. The prevalence on large-scale farms was lower (p < 0.001) than on small farms. The bTB milk antibody levels had a negative correlation with milk yield and a positive correlation with somatic cell count (SCC), milk protein percentage (MPP) and percentage of total solids (TS). According to this research, milk ELISA could be used as a supplement of blood samples to assist in the surveillance for bTB and for alerting control and eradication of bTB.

Predicting Positive ELISA Results in Dairy Herds with a Preferred Status in a Paratuberculosis Control Program

Dairy herds participating in the Dutch milk quality assurance program for paratuberculosis are assigned a herd status on the basis of herd examinations by ELISA of individual serum or milk samples, followed by an optional confirmatory fecal PCR. Test-negative herds are assigned Status A; the surveillance of these herds consists of biennial herd examinations. Farmers falsely believing that their Status A herds are Map-free may inadvertently refrain from preventive measures. Therefore, we aimed to develop a predictive model to alert Status A farmers at increased risk of future positive ELISA results. Using data of 8566 dairy herds with Status A in January 2016, two logistic regression models were built, with the probabilities of ≥1 or ≥2 positive samples from January 2017–June 2019 as dependent variables, and province, soil type, herd size, proportion of cattle born elsewhere, time since previous positive ELISA results, and the 95th percentile of the S/P ratios in 2015–2016, as explanatory variables. As internal validation, both models were applied to predict positive ELISA results from January 2019–June 2021, in 8026 herds with Status A in January 2019. The model predicting ≥1 positive sample had an area under the receiver-operating-characteristics curve of 0.76 (95% CI: 0.75, 0.77). At a cut-off predicted probability πc = 0.40, 25% of Status A herds would be alerted with positive and negative predictive values of 0.52 and 0.83, respectively. The model predicting ≥2 positive samples had lower positive, but higher negative, predictive values. This study indicates that discrimination of Status A herds with high and low risks of future positive ELISA results is feasible. This might stimulate farmers with the highest risks to take additional measures to control any undetected Map infections.