Monitoring and Surveillance of Small Ruminant Health in The Netherlands

The impact of the bluetongue serotype 3 outbreak on sheep and goat mortality in the Netherlands in 2023

In September 2023, bluetongue virus serotype 3 (BTV-3) emerged in the Netherlands, infecting over five thousand livestock farms. In sheep, high morbidity and mortality rates were reported that were unlike previously described bluetongue outbreaks. This study aimed to quantify the impact of BTV-3 in the small ruminant population in the Netherlands in 2023. Sheep and goat movement census data and BTV-3 notification data were available from 2020 until the end of 2023. Data were aggregated to farm and week level and mortality indicators were calculated for lambs (<1 year) and adult animals (≥1 year). Population averaged GEE models with a Negative-binomial distribution and a log-link function correcting for repeated measures per farm in time were used to quantify the association between BTV-3 and mortality. In 2023, 2994 sheep farmers and 89 goat farmers notified clinical signs of BTV-3 to the NVWA. During this BTV-3 outbreak period, an additional 55,000 sheep died compared to the same period in 2020-2022. At flock level a high variety in mortality was observed, with a clear increase in mortality in both flocks that were not notified but that were located in infected areas and in flocks of which the farmer notified clinical signs. During the BTV-3 outbreak period, mortality in infected areas increased 4.2 (95 % CI: 4.0-4.3) times in sheep lambs (<1 year) and 4.6 (95 % CI: 4.4-4.8) times in sheep (≥1 year) compared to BTV-3 free areas. Flocks with a confirmed BTV-3 infection that were notified in September showed a 12.8 (95 % CI: 11.4-14.3) times higher mortality in lambs and a 15.1 (95 % CI: 13.7-16.6) times higher mortality in sheep compared to flocks in BTV-3 areas. In flocks of which the farmer notified clinical signs after September, mortality was 4.6 (95 % CI: 4.2-5.0) and 5.6 (95 % CI: 5.1-6.0) times higher in lambs and sheep compared BTV-3 areas respectively. In goats, around 4000 additional deaths were recorded during the BTV-3 outbreak period. In farms that were notified, mortality of goats (≥1 year) was 1.8 (95 % CI: 1.2-2.8) times higher compared to BTV-3 free areas. Since May 2024, multiple BTV-3 vaccines are available in the Netherlands. In June 2024, the first new infections of BTV-3 were confirmed in Dutch sheep flocks. Hopes are that with the possibility to vaccinate, the spread and impact of BTV-3 in the Netherlands will rapidly decline and that losses as observed in 2023 will no longer be seen.

Bluetongue virus serotype 3 in ruminants in the Netherlands: Clinical signs, seroprevalence and pathological findings

BACKGROUND

The bluetongue virus serotype 3 (BTV-3) outbreak in the Netherlands in 2023 caused severe clinical signs in ruminants. The clinical and pathological signs in ruminants and their spread during the outbreak in 2023 are described.

METHODS

Data from the Dutch monitoring and surveillance system were available to describe clinical signs and pathological findings related to BTV-3 in sheep, cattle and goats. During the outbreak, 13 farms (five sheep, five cattle and three dairy goats) were closely monitored.

RESULTS

In 2023, BTV-3 infections were confirmed by real-time polymerase chain reaction in sheep flocks (n = 1807), cattle herds (n = 1864), goat herds (n = 62), alpaca and/or llama herds (n = 15) and one dog. Sheep exhibited the most severe clinical signs and had the highest mortality. In other animal species, a large variation in both occurrence and severity of clinical signs was observed.

LIMITATION

Only 13 farms were closely monitored.

CONCLUSIONS

The clinical signs observed in affected animals during the 2023 BTV-3 outbreak seem to be more severe than those observed during the BTV-8 outbreak between 2006 and 2008. It seems likely that BTV-3 will overwinter, similar to BTV-8. Therefore, the availability of an effective and safe vaccine is crucial to limit the future impact of BTV-3.

Emergence of Bluetongue Virus Serotype 3, the Netherlands, September 2023

Since 1998, notifiable bluetongue virus (BTV) serotypes 1-4, 6, 8, 9, 11, and 16 have been reported in Europe. In August 2006, a bluetongue (BT) outbreak caused by BTV serotype 8 began in northwestern Europe. The Netherlands was declared BT-free in February 2012, and annual monitoring continued. On September 3, 2023, typical BT clinical manifestations in sheep were notified to the Netherlands Food and Product Safety Consumer Authority. On September 6, we confirmed BTV infection through laboratory diagnosis; notifications of clinical signs in cattle were also reported. We determined the virus was serotype 3 by whole-genome sequencing. Retrospective analysis did not reveal BTV circulation earlier than September. The virus source and introduction route into the Netherlands remains unknown. Continuous monitoring and molecular diagnostic testing of livestock will be needed to determine virus spread, and new prevention strategies will be required to prevent BTV circulation within the Netherlands and Europe.

Reference Material Production and Milk Protein Concentration as Elements to Improve Bluetongue Serological Diagnosis in Bulk Tank Milk

The serological surveillance of bluetongue in bulk tank milk is an efficient and cost-effective method for the early detection of bluetongue virus incursions in unvaccinated free areas of the disease. In addition, the availability of standardized and reliable reagents and refined diagnostic procedures with high sensitivity and specificity are essential for surveillance purposes. However, no available reference materials for bluetongue virus serological surveillance in bulk tank milk exist. This study shows the production and characterization of reference material for the implementation of a commercially available bluetongue milk ELISA test in official laboratories, as well as the evaluation of a procedure to increase the sensitivity in samples with low levels of antibodies. This procedure, based on milk protein concentration, allowed us to notably increase the ELISA test's analytical sensitivity, which is useful for milk samples from farms with low within-herd prevalence or pools of bulk tank milk samples. The standardized milk reference material produced here, together with the evaluated procedure to improve analytical sensitivity, could be applied as tools to ensure an accurate diagnosis by official laboratories in bluetongue unvaccinated free areas.

Within-herd transmission of Mycoplasma bovis infections after initial detection in dairy cows

Mycoplasma bovis outbreaks in cattle, including pathogen spread between age groups, are not well understood. Our objective was to estimate within-herd transmission across adult dairy cows, youngstock, and calves. Results from 3 tests (PCR, ELISA, and culture) per cow and 2 tests (PCR and ELISA) per youngstock and calf were used in an age-stratified susceptible-infected-removed/recovered (SIR) model to estimate within-herd transmission parameters, pathways, and potential effects of farm management practices. A cohort of adult cows, youngstock, and calves on 20 Dutch dairy farms with a clinical outbreak of M. bovis in adult cows were sampled, with collection of blood, conjunctival fluid, and milk from cows, and blood and conjunctival fluid from calves and youngstock, 5 times over a time span of 12 wk. Any individual with at least one positive laboratory test was considered M. bovis-positive. Transmission dynamics were modeled using an age-stratified SIR model featuring 3 age strata. Associations with farm management practices were explored using Fisher's exact tests and Poisson regression. Estimated transmission parameters were highly variable among herds and cattle age groups. Notably, transmission from cows to cows, youngstock, or to calves was associated with R-values ranging from 1.0 to 80 secondarily infected cows per herd, 1.2 to 38 secondarily infected youngstock per herd, and 0.1 to 91 secondarily infected calves per herd, respectively. In case of transmission from youngstock to youngstock, calves or to cows, R-values were 0.7 to 96 secondarily infected youngstock per herd, 1.1 to 76 secondarily infected calves per herd, and 0.1 to 107 secondarily infected cows per herd. For transmission from calves to calves, youngstock or to cows, R-values were 0.5 to 60 secondarily infected calves per herd, 1.1 to 41 secondarily infected youngstock per herd, and 0.1 to 47 secondarily infected cows per herd. Among on-farm transmission pathways, cow-to-youngstock, cow-to-calf, and cow-to-cow were identified as most significant contributors, with calf-to-calf and calf-to-youngstock also having noteworthy roles. Youngstock-to-youngstock was also implicated, albeit to a lesser extent. Whereas the primary focus was a clinical outbreak of M. bovis among adult dairy cows, it was evident that transmission extended to calves and youngstock, contributing to overall spread. Factors influencing transmission and specific transmission pathways were associated with internal biosecurity (separate caretakers for various age groups, number of people involved), external biosecurity (contractors, external employees), as well as indirect transmission routes (number of feed and water stations).

Data analysis supports monitoring and surveillance of goat health and welfare in the Netherlands

Monitoring and surveillance systems have an increasingly important role in contemporary society ensuring high levels of animal health and welfare, securing export positions, and protecting public health by ensuring animal health and product safety. In the Netherlands, a voluntary monitoring and surveillance system is in place since 2003 to provide a broad overview of livestock trends in addition to disease-specific surveillance systems, including insight into the occurrence and prevalence of new and emerging non-notifiable diseases and disorders. Being a major surveillance component of this monitoring and surveillance system for small ruminant health in the Netherlands, an annual data analysis on routine census data is performed to retrospectively monitor trends and developments regarding goat health and welfare. This paper aims to describe the process of the data analysis on goat farms in the Netherlands in 2020 and subsequent results are discussed. The data analysis provides key monitoring indicators such as animal and farm density, mortality, animal movements, and numbers and origin of imported small ruminants. Trends were analysed over a five-year, period and associations between herd characteristics and herd health are evaluated. Results showed that in 2020 the Dutch goat population consisted of 670,842 goats, distributed over 14,730 unique herds and increased by 2.3 % compared to 2019. Between 2016 and 2020, although probably underestimated, recorded mortality rates showed a decline on both small-scale and professional farms, with a strongest decrease on farms with herd sizes over more than 200 animals. Seventy-five percent of all professional farms registered animal introductions, in addition to 63 % of small-scale farms, including 2439 imported goats. Performing risks analyses requires demographic knowledge of the goat industry. During and after several disease outbreaks, such as bluetongue and Schmallenberg virus disease, the data analysis proved to function as a valuable tool, however, appeared just as important for recording outbreak-free data. Since its start in 2006, the concept of the data-analysis has continuously been improved, and will in the future be further developed, especially if more complete data sets become available. Subsequently, data analysis will increasingly support monitoring and surveillance of goat health and welfare.

Coverage and Representativeness of Passive Surveillance Components for Cattle and Swine in The Netherlands

Common aims of animal health surveillance systems are the timely detection of emerging diseases and health status monitoring. This study aimed to evaluate the coverage and representativeness of passive surveillance components for cattle and swine in the Netherlands from 2015-2019. The passive surveillance components consisted of a telephone helpdesk for veterinary advice and diagnostic and postmortem facilities. Spatial analysis showed heterogeneity (range in RR = 0.26-5.37) of participation across the Netherlands. Generalized linear mixed models showed that distance to the diagnostic facility and farm density were associated with the number of contacts of farmers with the helpdesk and postmortem examination. The contact rate of veterinary practices was associated with their number of clients, ranging in RR from 0.39 to 1.59. We concluded that the evaluation indicated differences in coverage of the passive surveillance components across regions, farms and veterinary practices. Due to the absence of emerging infections in the study period, we were unable to estimate the consequences of the observed differences for the early detection of disease. Nevertheless, regions and veterinary practices with low participation in passive surveillance might be a risk for early detection, and consequently, further understanding of the motivation to participate in passive surveillance components is needed.