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).

Genetic analysis of infectious bronchitis virus (IBV) in vaccinated poultry populations over a period of 10 years.

Infectious bronchitis virus (IBV) is an avian pathogen from the Coronavirus family causing major health issues in poultry flocks worldwide. Because of its negative impact on health, performance, and bird welfare, commercial poultry are routinely vaccinated by administering live attenuated virus. However, field strains are capable of rapid adaptation and may evade vaccine-induced immunity. We set out to describe dynamics within and between lineages and assess potential escape from vaccine-induced immunity. We investigated a large nucleotide sequence database of over 1700 partial sequences of the S1 spike protein gene collected from clinical samples of Dutch chickens submitted to the laboratory of Royal GD between 2011 and 2020. Relative frequencies of the two major lineages GI-13 (793B) and GI-19 (QX) did not change in the investigated period, but we found a succession of distinct GI-19 sublineages. Analysis of dN/dS ratio over all sequences demonstrated episodic diversifying selection acting on multiple sites, some of which overlap predicted N-glycosylation motifs. We assessed several measures that would indicate divergence from vaccine strains, both in the overall database and in the two major lineages. However, the frequency of vaccine-homologous lineages did not decrease, no increase in genetic variation with time was detected, and the sequences did not grow more divergent from vaccine sequences in the examined time window. Concluding, our results show sublineage turnover within the GI-19 lineage and we demonstrate episodic diversifying selection acting on the partial sequence, but we cannot confirm nor rule out escape from vaccine-induced immunity.RESEARCH HIGHLIGHTSSuccession of GI-19 IBV variants in broiler populations.IBV lineages overrepresented in either broiler, or layer production chickens.Ongoing episodic selection at the IBV S1 spike protein gene sequence.Several positively selected codons coincident with N-glycosylation motifs.

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.

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 explanatory 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.

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

Dairy cows are negatively affected by the introduction of bovine viral diarrhea virus (BVDV), and consequently, produce less milk. Existing literature on potential milk production losses is based on relatively outdated data and hardly evaluates milk production loss in relation to a new BVDV infection in a surveillance system. This study determined the annual and quarterly loss in milk production of BVDV introduction in 3,126 dairy herds participating in the Dutch BVDV-free program between 2007 and 2017. Among these herds, 640 were "breakdown-herds" that obtained and subsequently lost their BVDV-free status during the study period, and 2,486 herds obtained and retained their BVDV-free status during the study period. Milk yields before and after BVDV introduction were compared through annual and quarterly linear mixed models. The fixed variables for both models included herd type (breakdown-herd or free-herd), bovine viral diarrhea status (on an annual and quarterly basis), year, season, and a random herd effect. The dependent variable was the average daily milk yield on the test day. To define the possible BVDV-introduction dates, 4 scenarios were developed. In the default scenario, the date of breakdown (i.e., loss of the BVDV-free status) was assumed as the BVDV-introduction date. For the other 3 scenarios, the BVDV-introduction dates were set at 4, 6, and 9 mo before the date of breakdown, based on the estimated birth date of a persistently infected calf. In the default scenario, the loss in milk yield due to BVDV introduction occurred mainly in the first year after breakdown, with a reduction in yield of 0.08 kg/cow per day compared with the last year before breakdown. For the other 3 scenarios, the greatest yield reduction occurred in the second year after BVDV introduction, with a loss of 0.09, 0.09, and 0.1 kg/cow per day, respectively. For the first 4 quarters after BVDV introduction in the default scenario, milk yield loss was 0.14, 0.09, 0.02, and 0.08 kg/cow per day, respectively. These quarterly results indicated that milk yield loss was greatest in the first quarter after BVDV introduction. Overall, BVDV introduction had a negative, but on average a relatively small, effect on milk yield for herds participating in the BVDV-free program. This study will enable dairy farmers and policymakers to have a clearer understanding of the quantitative milk production effect of BVDV on dairy farms in a control program.

Risk-based surveillance for meat-borne parasites.

There is a plethora of meat-borne hazards - including parasites - for which there may be a need for surveillance. However, veterinary services worldwide need to decide how to use their scarce resources and prioritise among the perceived hazards. Moreover, to remain competitive, food business operators - irrespective of whether they are farmers or abattoir operators - are preoccupied with maintaining a profit and minimizing costs. Still, customers and trade partners expect that meat products placed on the market are safe to consume and should not bear any risks of causing disease. Risk-based surveillance systems may offer a solution to this challenge by applying risk analysis principles; first to set priorities, and secondly to allocate resources effectively and efficiently. The latter is done through a focus on the cost-effectiveness ratio in sampling and prioritisation. Risk-based surveillance was originally introduced into veterinary public health in 2006. Since then, experience has been gathered, and the methodology has been further developed. Guidelines and tools have been developed, which can be used to set up appropriate surveillance programmes. In this paper, the basic principles are described, and by use of a surveillance design tool called SURVTOOLS (https://survtools.org/), examples are given covering three meat-borne parasites for which risk-based surveillance is 1) either in place in the European Union (EU) (Trichinella spp.), 2) to be officially implemented in December 2019 (Taenia saginata) or 3) only carried out by one abattoir company in the EU as there is no official EU requirement (Toxoplasma gondii). Moreover, advantages, requirements and limitations of risk-based surveillance for meat-borne parasites are discussed.

Intramammary antimicrobial treatment of subclinical mastitis and cow performance later in lactation.

The aim of this study was to evaluate long-term therapeutic effects of antimicrobial treatment of recently acquired subclinical mastitis (RASCM) during lactation. Quarter-level clinical mastitis (CM) follow-up, composite somatic cell counts (SCC), and cow-level milk yield later in lactation were evaluated using follow-up data from 2 previously published linked randomized field trials. The first trial randomly assigned antimicrobial treatment with any intramammary product or negative control to culture-positive quarters of cows having a first elevated composite SCC after 2 consecutive low composite SCC measurements. Untreated cows that had a second elevated composite SCC at the next measurement and were staphylococci-positive (i.e., Staphylococcus aureus or non-aureus staphylococci) were randomly assigned to treatment or control. Quarter-level CM cases were reported by the participating herd personnel, and milk yield and composite SCC data were obtained from the regular test-day recording. Frailty survival models were used to evaluate the long-term therapeutic effects of antimicrobial treatment of RASCM on quarter-level CM follow-up. Mixed linear regression models were applied to quantify the effect on milk yield and composite SCC. Data of 638 quarters from 486 cows in 38 herds were available for statistical analyses, of which 229 quarters of 175 cows received antimicrobial treatment for RASCM. Antimicrobial treatment culminated in reduced composite SCC levels later in lactation but did not result in different milk yield levels or CM follow-up compared with control cows. Antimicrobial treatment of cows with RASCM should therefore only be considered in exceptional situations given the current focus on antimicrobial usage reduction in animal husbandry.

Monitoring antimicrobial resistance trends in commensal Escherichia coli from livestock, the Netherlands, 1998 to 2016.

BackgroundMonitoring of antimicrobial resistance (AMR) in animals is essential for public health surveillance. To enhance interpretation of monitoring data, evaluation and optimisation of AMR trend analysis is needed.AimsTo quantify and evaluate trends in AMR in commensal Escherichia coli, using data from the Dutch national AMR monitoring programme in livestock (1998-2016).MethodsFaecal samples were collected at slaughter from broilers, pigs and veal calves. Minimum inhibitory concentration values were obtained by broth microdilution for E. coli for 15 antimicrobials of eight antimicrobial classes. A Poisson regression model was applied to resistant isolate counts, with explanatory variables representing time before and after 2009 (reference year); for veal calves, sampling changed from 2012 represented by an extra explanatory variable.ResultsResistant counts increased significantly from 1998-2009 in broilers and pigs, except for tetracyclines and sulfamethoxazole in broilers and chloramphenicol and aminoglycosides in pigs. Since 2009, resistant counts decreased for all antimicrobials in broilers and for all but the phenicols in pigs. In veal calves, for most antimicrobials no significant decrease in resistant counts could be determined for 2009-16, except for sulfamethoxazole and nalidixic acid. Within animal species, antimicrobial-specific trends were similar.ConclusionsUsing Dutch monitoring data from 1998-2016, this study quantified AMR trends in broilers and slaughter pigs and showed significant trend changes in the reference year 2009. We showed that monitoring in commensal E. coli is useful to quantify trends and detect trend changes in AMR. This model is applicable to similar data from other European countries.

Bovine Neonatal Pancytopenia is a heritable trait of the dam rather than the calf and correlates with the magnitude of vaccine induced maternal alloantibodies not the MHC haplotype.

Bovine Neonatal Pancytopenia (BNP), a bleeding syndrome of neonatal calves, is caused by alloantibodies absorbed from the colostrum of particular cows. A commercial BVD vaccine is the likely source of alloantigens eliciting BNP associated alloantibodies. We hypothesized that the rare occurrence of BNP in calves born to vaccinated dams could be associated with genetic differences within dams and calves. We found that the development of BNP within calves was a heritable trait for dams, not for calves and had a high heritability of 19%. To elucidate which genes play a role in the development of BNP we sequenced candidate genes and characterized BNP alloantibodies. Alloantigens present in the vaccine have to be presented to the dam's immune system via MHC class II, however sequencing of DRB3 showed no differences in MHC class II haplotype between BNP and non-BNP dams. MHC class I, a highly polymorphic alloantigen, is an important target of BNP alloantibodies. Using a novel sequence based MHC class I typing method, we found no association of BNP with MHC class I haplotype distribution in dams or calves. Alloantibodies were detected in both vaccinated BNP and non-BNP dams and we found no differences in alloantibody characteristics between these groups, but alloantibody levels were significantly higher in BNP dams. We concluded that the development of BNP in calves is a heritable trait of the dam rather than the calf and genetic differences between BNP and non-BNP dams are likely due to genes controlling the quantitative alloantibody response following vaccination.

Can routinely recorded reproductive events be used as indicators of disease emergence in dairy cattle? An evaluation of 5 indicators during the emergence of bluetongue virus in France in 2007 and 2008.

In response to increasing risks of emerging infectious diseases, syndromic surveillance can be a suitable approach to detect outbreaks of such diseases across a large territory in an early phase. To implement a syndromic surveillance system, the primary challenge is to find appropriate health-related data. The objective of this study was to evaluate whether routinely collected dates of reproductive events in dairy cattle could be used to build indicators of health anomalies for syndromic surveillance. The evaluation was performed on data collected in France between 2003 and 2009. First, a set of 5 indicators was proposed to assess several types of reproductive disorders. For each indicator, the demographic coverage over the total number of cattle at risk was analyzed in time and space. Second, the ability to detect an emerging disease in an early phase was retrospectively evaluated during epidemics of bluetongue serotypes 1 and 8 (BTV-1, BTV-8) in France in 2007 and 2008. Reproductive indicators were analyzed weekly during these epidemics for each indicator in each infected French district (16 in 2007 and 50 in 2008 out of 94 districts). The indicators were able to detect the BTV epidemics despite their low demographic coverage on a weekly basis relatively to total number of cattle (median=1.21%; range=0-11.7%). Four indicators related to abortions, late embryonic death, and short gestations were abnormally elevated during both BTV epidemics. Median times to abnormal elevations in these indicators were 20 to 71 d after the first notification of clinical signs of BTV by veterinarians. These results demonstrate that reproduction data can be used as indicators of disease emergences, whereas in the specific case of these BTV epidemics, detection via these indicators was later than clinical detection by veterinarians. The emergence of bluetongue in 2007 in France was associated with gestations that were a few days shorter than expected. A short gestation indicator underwent high elevations relative to prior random fluctuations and was the earliest (out of the 4 indicators) to show abnormal elevations, making it possible to detect this emergence.

Review state-of-the-art of output-based methodological approaches for substantiating freedom from infection.

A wide variety of control and surveillance programmes that are designed and implemented based on country-specific conditions exists for infectious cattle diseases that are not regulated. This heterogeneity renders difficult the comparison of probabilities of freedom from infection estimated from collected surveillance data. The objectives of this review were to outline the methodological and epidemiological considerations for the estimation of probabilities of freedom from infection from surveillance information and review state-of-the-art methods estimating the probabilities of freedom from infection from heterogeneous surveillance data. Substantiating freedom from infection consists in quantifying the evidence of absence from the absence of evidence. The quantification usually consists in estimating the probability of observing no positive test result, in a given sample, assuming that the infection is present at a chosen (low) prevalence, called the design prevalence. The usual surveillance outputs are the sensitivity of surveillance and the probability of freedom from infection. A variety of factors influencing the choice of a method are presented; disease prevalence context, performance of the tests used, risk factors of infection, structure of the surveillance programme and frequency of testing. The existing methods for estimating the probability of freedom from infection are scenario trees, Bayesian belief networks, simulation methods, Bayesian prevalence estimation methods and the STOC free model. Scenario trees analysis is the current reference method for proving freedom from infection and is widely used in countries that claim freedom. Bayesian belief networks and simulation methods are considered extensions of scenario trees. They can be applied to more complex surveillance schemes and represent complex infection dynamics. Bayesian prevalence estimation methods and the STOC free model allow freedom from infection estimation at the herd-level from longitudinal surveillance data, considering risk factor information and the structure of the population. Comparison of surveillance outputs from heterogeneous surveillance programmes for estimating the probability of freedom from infection is a difficult task. This paper is a 'guide towards substantiating freedom from infection' that describes both all assumptions-limitations and available methods that can be applied in different settings.

Bayesian diagnostic test evaluation and true prevalence estimation of mycoplasma bovis in dairy herds.

The true prevalence of dairy cattle herds with M. bovis infections in the Netherlands is unknown. Previous attempts to estimate prevalences were hampered by the absence of a diagnostic serological test that was validated under field conditions. This study estimated sensitivity and specificity of two commercial serum ELISAs and the true M. bovis herd prevalence using different Bayesian latent class models. A total of 7305 serum samples from 415 randomly chosen dairy herds were collected in fall/winter 2019 and investigated for presence of antibodies against M. bovis using the BIO-K-260 ELISA from Bio-X. Serum samples from 100 of these herds were also tested with a second ELISA, from IDvet. A Bayesian latent class model using the paired test results estimated a sensitivity of 14.1% (95% Bayesian probability interval (BPI): 11.6-16.7%) for the Bio-X ELISA and a specificity of 97.2% (95% BPI: 95.9-98.4%). Sensitivity and specificity for the IDvet ELISA were estimated at 92.5% (95% BPI: 88.3-96.5%) and 99.3% (95% BPI: 98.7-99.8%), respectively. Also, Bio-X ELISA sensitivity was considerably higher with data from calves only and with data from a selection of herds with a clinical outbreak, whereas the IDvet ELISA sensitivity was fairly constant under these conditions. These differences in test sensitivity is expected to be related to an effect of time since infection. A second Bayesian model, applied on test results of all 415 herds, estimated a true herd prevalence of 69.9% (95% BPI: 62.7-77.6%), suggesting M. bovis in endemic amongst dairy cattle herds in the Netherlands. To what extent seropositive herds have experienced a clinical outbreak needs further investigation.

The economic impact of endemic respiratory disease in pigs and related interventions - a systematic review.

BACKGROUND: Understanding the financial consequences of endemically prevalent pathogens within the porcine respiratory disease complex (PRDC) and the effects of interventions assists decision-making regarding disease prevention and control. The aim of this systematic review was to identify what economic studies have been carried out on infectious endemic respiratory disease in pigs, what methods are being used, and, when feasible, to identify the economic impacts of PRDC pathogens and the costs and benefits of interventions. RESULTS: By following the PRISMA method, a total of 58 studies were deemed eligible for the purpose of this systematic review. Twenty-six studies used data derived from European countries, 18 from the US, 6 from Asia, 4 from Oceania, and 4 from other countries, i.e., Canada, Mexico, and Brazil. Main findings from selected publications were: (1) The studies mainly considered endemic scenarios on commercial fattening farms; (2) The porcine reproductive and respiratory syndrome virus was by far the most studied pathogen, followed by Mycoplasma hyopneumoniae, but the absence or presence of other endemic respiratory pathogens was often not verified or accounted for; (3) Most studies calculated the economic impact using primary production data, whereas twelve studies modelled the impact using secondary data only; (4) Seven different economic methods were applied across studies; (5) A large variation exists in the cost and revenue components considered in calculations, with feed costs and reduced carcass value included the most often; (6) The reported median economic impact of one or several co-existing respiratory pathogen(s) ranged from €1.70 to €8.90 per nursery pig, €2.30 to €15.35 per fattening pig, and €100 to €323 per sow per year; and (7) Vaccination was the most studied intervention, and the outcomes of all but three intervention-focused studies were neutral or positive. CONCLUSION: The outcomes and discussion from this systematic review provide insight into the studies, their methods, the advantages and limitations of the existing research, and the reported impacts from the endemic respiratory disease complex for pig production systems worldwide. Future research should improve the consistency and comparability of economic assessments by ensuring the inclusion of high impact cost and revenue components and expressing results similarly.

Antibiotic prescription patterns and non-clinical factors influencing antibiotic use by Ecuadorian veterinarians working on cattle and poultry farms: A cross-sectional study.

Understanding antibiotic prescription patterns and non-clinical factors influencing antibiotic use is essential for implementing strategies to promote appropriate antibiotic use. There is, however, limited research exploring these issues with Ecuadorian veterinarians. Therefore, a questionnaire was developed and applied cross-sectionally to veterinarians (n = 173) from two professional organizations to explore the antibiotic prescription patterns and non-clinical factors (e.g., attitudes and perceptions) influencing antibiotic use, and to identify strategies to reduce antibiotic use. The response rate was 78.4%. Responses were compared between veterinarians working mainly on cattle and poultry farms using Mann-Whitney U tests. The most important attitudes, beliefs and perceptions towards antimicrobial resistance (AMR) and antibiotic use were identified with the Relative Importance Index (RII). Veterinarians showed high awareness of AMR and its implications for public health, as well as the necessity of reducing antibiotic use. However, some veterinarians appear to underestimate the potential contribution of veterinary antibiotic use on AMR in humans. Veterinarians self-reported high prescription (> 20%) of antibiotics for cattle and poultry that are critically important for human medicine, such as 3rd and 4th generation cephalosporins, polymyxins and quinolones. Further, antibiotic therapy was not tailored to disease type. Cattle and poultry veterinarians perceived similar barriers to increasing antibiotic stewardship including: poor biosecurity measures, animal confinement, low feed quality, farmers' behaviors (such as stopping antibiotic treatment, storing antibiotics on farms, buying antibiotics in veterinary supply stores), and sales agents' roles as non-professional prescribers of antibiotics. Overall, veterinarians were broadly supportive (>90%) of most strategies to promote appropriate antibiotic use. They saw more merit in improving biosecurity of farms and implementing educational programs for farmers and veterinarians. This study provides insight into the complexity of antibiotic use on Ecuadorian farms and the need for holistic strategies in a One Health context, to achieve antibiotic stewardship.

The DECIDE project: from surveillance data to decision-support for farmers and veterinarians.

Farmers, veterinarians and other animal health managers in the livestock sector are currently missing sufficient information on prevalence and burden of contagious endemic animal diseases. They need adequate tools for risk assessment and prioritization of control measures for these diseases. The DECIDE project develops data-driven decision-support tools, which present (i) robust and early signals of disease emergence and options for diagnostic confirmation; and (ii) options for controlling the disease along with their implications in terms of disease spread, economic burden and animal welfare. DECIDE focuses on respiratory and gastro-intestinal syndromes in the three most important terrestrial livestock species (pigs, poultry, cattle) and on reduced growth and mortality in two of the most important aquaculture species (salmon and trout). For each of these, we (i) identify the stakeholder needs; (ii) determine the burden of disease and costs of control measures; (iii) develop data sharing frameworks based on federated data access and meta-information sharing; (iv) build multivariate and multi-level models for creating early warning systems; and (v) rank interventions based on multiple criteria. Together, all of this forms decision-support tools to be integrated in existing farm management systems wherever possible and to be evaluated in several pilot implementations in farms across Europe. The results of DECIDE lead to improved use of surveillance data and evidence-based decisions on disease control. Improved disease control is essential for a sustainable food chain in Europe with increased animal health and welfare and that protects human health.

Seroprevalence of Schmallenberg virus antibodies among dairy cattle, the Netherlands, winter 2011-2012.

Infections with Schmallenberg virus (SBV) are associated with congenital malformations in ruminants. Because reporting of suspected cases only could underestimate the true rate of infection, we conducted a seroprevalence study in the Netherlands to detect past exposure to SBV among dairy cattle. A total of 1,123 serum samples collected from cattle during November 2011-January 2012 were tested for antibodies against SBV by using a virus neutralization test; seroprevalence was 72.5%. Seroprevalence was significantly higher in the central-eastern part of the Netherlands than in the northern and southern regions (p<0.001). In addition, high (70%-100%) within-herd seroprevalence was observed in 2 SBV-infected dairy herds and 2 SBV-infected sheep herds. No significant differences were found in age-specific prevalence of antibodies against SBV, which is an indication that SBV is newly arrived in the country.

No long-term influence of movement restriction regulations on the contact-structure between and within cattle holding types in the Netherlands.

BACKGROUND: More and more countries hold databases on cattle movements. The primary purpose of the registration of cattle movements is to provide data for quick tracing of contagious animals in case of disease outbreaks and food safety scares. Nevertheless, these data can also be used for analytical studies to get insight into the nature of the contact structure between and within cattle holding types. This paper focuses on the effect post-2001 FMD movement regulations have had on the number of cattle movements between different and within the same cattle holding types. Important characteristics and dynamics of cattle movement patterns of Dutch cattle holding types were identified using data on cattle movements after the 2001 FMD outbreak. RESULTS: The results showed that in 2001, just after the FMD outbreak when strict movement restriction regulations were in force, a reduced number of cattle movements was seen compared to before the FMD outbreak. However, the number of cattle movements off-farm for live trade and the number of imported cattle increased in the period 2002-2004 to higher levels than expected, i.e. to levels almost as high as before the FMD outbreak, despite operative movement restriction regulations. As the number of cattle movements to and from traders strongly decreased just after the FMD outbreak in 2001, traders regained their central role again in the network in the years 2002-2004. CONCLUSIONS: Quantifying the Dutch cattle contact structure between and within holding types up to 3.5 years after the FMD outbreak gave evidence that the post-FMD movement restriction regulations were not able to reduce the number of cattle movements in the longer term. With that the risk of a large epidemic increased. Quantifying contact structures based on animal movement data between different and within the same cattle holding types is important for targeting disease control and for assessing compliance with legislation.

Antimicrobial resistance monitoring in commensal and clinical Escherichia coli from broiler chickens: Differences and similarities.

BACKGROUND: In the Netherlands, antimicrobial resistance (AMR) is monitored in commensal indicator Escherichia coli from healthy broilers at slaughter as part of a European monitoring programme. In a separate programme for poultry health, AMR is monitored in veterinary pathogens from diseased broilers. So far, it is unknown how the outcomes of these two AMR monitoring approaches in the same animal population are associated. AIMS: This study aims to investigate the association between the outcomes of monitoring non-wildtype susceptibility (using epidemiological cut-off values, ECOFF, as prescribed by EU legislation) in commensal E. coli isolated from healthy broilers (i.e. active surveillance) with the outcomes of monitoring clinical resistance (using clinical breakpoints, to determine susceptibility for antibiotic treatment in veterinary practice) in E. coli isolated from diseased broilers (i.e. passive surveillance). METHODS: Data acquired by broth microdilution was analysed for commensal indicator E. coli and clinical E. coli from the Netherlands, 2014-2019. A generalized linear multivariable model (Poisson regression) was used to determine time trends and identify differences in mean resistant proportions. RESULTS: Observed resistant proportions of the monitored commensal E. coli and clinical E. coli were similar with overlapping confidence intervals for most time points for ampicillin, gentamicin, cefotaxime, tetracycline, colistin and trimethoprim/sulfonamide. The statistical analysis showed that only for cefotaxime and tetracycline, mean resistant proportions were different. In commensal E. coli, a decrease of resistant proportions over time was observed, except for gentamicin. In clinical E. coli, no time trend was detected in resistant proportions, except for cefotaxime and colistin. CONCLUSIONS: Generally, the resistant proportions monitored in commensal and clinical E. coli were similar. However, some relevant differences were found, which can be explained by the type of monitoring approach, i.e. active or passive surveillance. The random sample of commensal E. coli isolated from healthy animals (active surveillance), was more suitable to monitor AMR time trends. The sample of clinical isolates from diseased animals (passive surveillance), resulted in a higher chance to detect low-prevalent resistance: i.e. cefotaxime and colistin. The clinical E. coli data showed more fluctuation over time, and data from a longer period of time would be needed to determine the association. This study shows the value of both an active and a passive surveillance component for AMR monitoring.

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.

The effectiveness of bovine tuberculosis surveillance in Dutch badgers.

Countries survey wildlife for bovine tuberculosis (bTB) to ensure case detection or to ascertain a high probability of freedom from bTB in wildlife. The Eurasian badger (Meles meles) is a potential bTB reservoir host. Between 2008 and 2019, 282 badgers were examined post-mortem in the context of general wildlife disease and targeted bTB surveillance programmes in the Netherlands, and no bTB cases were detected. However, it was unclear how effective this surveillance effort was to demonstrate freedom from Mycobacterium bovis infection in the badger population of ±6000 or to detect cases if present. Therefore, surveillance effectiveness was assessed using scenario tree modelling. For lack of standards for wildlife, the models were run against three assumed levels of disease in the population called design prevalence P*: 0.1%, 0.5%, and 3%. A small risk of introduction (0.015/year) was applied, because the Netherlands are officially free from bTB in cattle, with rare import of bTB-infected cattle and no bTB-infected wildlife reported along the Belgian and German borders with the Netherlands. Surveillance more readily picks up bTB presence in badgers when case detection sensitivity tends towards 100% and demonstrates freedom best when the probability of freedom tends towards 100%. For P* 0.1%, 0.5% and 3%, respectively, maximum case detection sensitivity during 2008-2019 was 8%, 35% and 94% and the probability of freedom in 2019 was 46%, 67%, and 95%. At P* = 3%, performing targeted surveillance on 300 badgers in a year would make it extremely unlikely to miss a case (case detection sensitivity > 99.9%); and if no cases are detected, the adjusted probability of freedom would then reach nearly 98.5%. Stakeholders should be made aware that at P* = 3%, one case detected implies around 3% infected badgers. Additional surveillance system components to assess bTB in wildlife and its economics are to be explored further.

Added Value of Meat Inspection Data for Monitoring of Dairy Cattle Health in the Netherlands.

Meat inspection records of one large cattle slaughterhouse were analyzed to evaluate the added value of slaughterhouse data for cattle health surveillance in the Netherlands. Data were available from January 2015 to September 2018, consisting of 467,361 meat inspection records. Analyses included (1) an assessment of the representativeness of the cattle herds in the slaughterhouse data in relation to the cattle herd population in the Netherlands, and (2) multivariable analyses to quantify associations between meat inspection findings and farm of origin characteristics, and the trends in time of the findings in slaughtered cattle. Ninety percent of the meat inspection records originated from dairy cattle therefore this paper only presents the results of dairy herds (N = 422,194 cattle). The dairy herds in the slaughterhouse data seemed representative for the Dutch dairy population although their regional coverage differed from the distribution of dairy herds in the Netherlands. Non-dairy herds were underrepresented in the slaughterhouse data which stresses the importance of the inclusion of data from other slaughterhouses that may be more specialized in slaughtering beef cattle. Inspection records were categorized into 15 indicators related to ante-mortem and post-mortem findings. Following multivariable analyses, seven indicators were deemed of added value to existing cattle health surveillance components, as they provided either new information or information regarding specific health problems.