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Supplementary information/ material for manuscript titled "Dutch dairy farmers’ perspectives on culling reasons and strategies"

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.

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 Existing literature on potential milk production losses is based on relatively outdated data and hardly evaluates milk production loss in relation to a new BVDV infection in a surveillance system.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.

Two vector-borne infections have emerged and spread throughout the north-western part of Europe in the last decade: Bluetongue virus serotype-8 (BTV-8) and the Schmallenberg virus (SBV). The objective of the current study was to compare three statistical methods when applied in a syndromic surveillance context for the early detection of emerging diseases in cattle in the Netherlands. Since BTV-8 and SBV both have a negative effect on milk production in dairy cattle, routinely collected bulk milk recordings were used to compare the three statistical methods in their potential to detect drops in milk production during a period of seven years in which BTV-8 and SBV emerged. A Cusum algorithm, Bayesian disease mapping model, and spatiotemporal cluster analysis using the space-time scan statistic were performed and their performance in terms of sensitivity and specificity was compared. Spatiotemporal cluster analysis performed best for early detection of SBV in cattle in the Netherlands with a relative sensitivity of 71% compared to clinical surveillance and 100% specificity in a year without major disease outbreaks. Sensitivity to detect BTV-8 was low for all methods. However, many alerts of reduced milk production were generated several weeks before the week in which first clinical suspicions were reported. It cannot be excluded that these alerts represent the actual first signs of BTV-8 infections in cattle in the Netherlands thus leading to an underestimation of the sensitivity of the syndromic surveillance methods relative to the clinical surveillance in place.

EU Member States are obliged by legislation to implement residue surveillance programs to detect illegal use or misuse of veterinary medicines in food producing animals and investigate the reasons for residue violations. According to EU legislation, these programs should be (partly) risk-based, meaning targeted towards groups of animals, where the probability of finding residues is the highest. There is however no default surveillance procedure describing the most efficient way to do so. In this study, a quantitative analysis was conducted to quantify the effectiveness of detecting antimicrobial residues in finishing pigs via risk-based sampling of carcasses. A stochastic scenario tree analysis was applied to estimate the sensitivity of random and risk-based sampling strategies to detect a contaminated carcass. In these models, the probability was calculated that a single carcass will yield a positive outcome when subjected to the testing protocol laid down in the design, given that contamination with antimicrobial residues is prevalent in the herd of origin at the level of the design prevalence. Two design prevalences were used: 0.01% (the assumed true prevalence of residue-positive carcasses) and 0.22% (the prevalence that can be detected using the sample size laid down in EU legislation). In the random design, it was assumed that the carcasses examined for presence of antimicrobial residues were selected randomly from all finishing pigs slaughtered in a year. In the risk-based design, two risk factors were taken into account. First, a high prevalence of chronic pleuritis and pneumonia in the herd of origin was assessed. Secondly, the route of administration of antimicrobials (oral/parenteral) via visual inspection of skin lesions indicative of injectables was used as an additional risk factor. Results showed that the probability of detecting a residue-positive carcass doubled when surveillance was targeted at pigs originating from herds with a high prevalence of chronic pleuritis and pneumonia (compared to random sampling), at similar costs of testing. Including administration route as an additional risk factor led to a negligible increase in sensitivity. Nevertheless, sensitivity values at unit level remained extremely low due to the very low prevalence of antimicrobial residues in pigs. In this study, risk-based alternatives to random sampling improved the cost-effectiveness of residue surveillance in slaughter pigs in the Netherlands, which could be used to enhance current programs and to increase awareness in food business operators.

The outcomes of a voluntary bovine viral diarrhoea virus (BVDV) control programme that has been in place in the Netherlands since 1997 were analysed. This ‘BVDV-free’ programme was studied in dairy herds in the period 1 August 2007 to 1 August 2013. The programme was based on a test and cull approach at the herd level, after which the BVDV status was monitored by testing young stock for antibodies against BVDV or by antigen testing of newborn calves. One of the challenges of the programme was that, without any legislation or subsidies, farmers had to be motivated to pay all costs involved, with eradication of BVDV from their farm as the only incentive. During the study period, the percentage of dairy farms with a ‘BVDV-free’ status in the Netherlands increased from 13% to 24%, while the prevalence of active BVDV infections in Dutch dairy herds decreased. This may be related to the increasing number of participants in the ‘BVDV-free’ programme.

The EU Residue Directive is currently being renegotiated. One key question is how to balance flexibility and harmonization. To address this, we reviewed Danish, Dutch and Swiss monitoring programs for antimicrobial residues in pig meat using the recently developed RISKSUR design tool. The results identified variation regarding number of surveillance components, reactions to suspect and positive findings, prevention activities, diagnostic method, sample matrix, use of targeted/risk-based approaches, and sampling frequency. This variability could largely be explained by differences in overall surveillance objective: Denmark and the Netherlands have a large pork export and higher need for documenting compliance with legislation, whereas Switzerland only trading with EU has a lower need for spending resources on monitoring. It is recommended that the future EU Directive should set standards for monitoring to ensure a basic level of monitoring enabling comparison of results. Minimum handling of carcasses with residues above maximum residue level should be harmonized. Risk-based sampling should be encouraged, and results from risk-based and random sampling should be reported separately. Harmonization is unnecessary for number of surveillance components (but a private component is recommended), prevention, diagnostic method, and way of sampling – assuming that the diagnostic method and sampling matrix combination have sufficient validity.

Potentially inappropriate prescribing is a common problem, especially in elderly care. To tackle this problem, Irish medical experts have developed a list of criteria when medication should be added or omitted based upon the patient's physical condition and medication use, known as the STOPP and START criteria. The STOPP and START criteria have been formulated to identify the prescribing of potentially inappropriate medicines (PIMs) and potential prescribing omissions (PPOs). One of the most common problems of inappropriate prescribing is gastro-intestinal track bleedings. For this purpose, nine of the 87 STOPP and START criteria are designed to prevent this. However, the prevalence of gastro-intestinal track bleedings has not been established when these nine STOPP and START criteria are violated. The database contained 182,000 patients belonging to 49 general practitioners in the region of Amsterdam, The Netherlands. We estimated both the incidence of PIMs and PPOs and whether harm, in this case a gastro-intestinal track bleeding, occurred. We found that although violation of the nine STOPP or START criteria were possibly associated with harm (OR = 1.30), this association was not statistically significant (p = 0.323). Searching for evidence for harm informs decision support design aimed at improving quality of medication prescription as it prioritizes the many suggested criteria based on their relevance

Traditional surveillance for detection of disease outbreaks are triggered by specific symptoms, whereas syndromic surveillance focuses on deviations of non-specific disease indicators such as drop in milk production. Milk production data on herd and test-day level are continuously available for 80-85% of Dutch dairy herds. Real time analyses of milk production data may allow detection of disease outbreaks before any confirmation by laboratory diagnosis and therefore can accelerate the detection of emerging diseases. The objective of this study was to evaluate to what extent syndromic surveillance on milk production data can contribute to early detection of vector borne diseases in the Dutch cattle population. Data were used from January 1st 2003 to March 31st 2012 and evaluated for the detection of bluetongue (re) emergence in 2006 and 2007 (1st analysis) and the Schmallenberg outbreak in 2011 (2nd analysis). Therefore, the methodology described by Madouasse et al. was applied on Dutch data. For the first analysis, a multilevel linear regression model was fitted on 2005 (in which no epidemics occurred) and mean milk production was predicted for 2006-2007. For the second analysis, a multilevel linear regression model was fitted on 2009-2010 and mean milk production was predicted for 2011 and 2012. The differences between observed and predicted milk production for the two models were plotted and analyzed with SaTScan to detect spatio-temporal clusters of decreased milk production. The results showed that no significant drop in milk production was detected during the 2006 and 2007 bluetongue outbreak, whereas a significant drop in milk production was detected at the start of the Schmallenbergvirus outbreak in the eastern part of the Netherlands. This study shows that real time analysis of milk production data can trigger an early signal in a surveillance program.

International Conference on Animal Health Surveillance (ICAHS), Lyon, France, 17-20 May, 2011.; To ease the early detection of (re)emerging animal diseases, the Belgian sanitary Authorities promoted the study on and the implementation of a web based application designed to manage the monitoring and surveillance of atypical syndromes. This "Monitoring and Surveillance System" (MoSS) website is an epidemiological information system which allows the detection of unusual syndromes in domesticated and wild animals, via an online recording system to be used by veterinary field practitioners and (veterinary experts). A hierarchical ascending clustering process automatically compares new records with all records in the database and creates clusters of cases based on homology in clinical description, animal typology and spatial-temporal proximity. The onset of a new cluster is accompanied by the invitation of an expert to lead the identification process via a dedicated forum page, where information about the evolution of cases, treatments and lab results can be shared, to facilitate the diagnostic process. In the MoSS, essential data on atypical syndromes is centralized and analyzed to shorten the detection time of any possible emerging disease in animals. This PhP-MySQL application runs now in English, French and Dutch and manages with cross-border reporting.