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.

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).

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.

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.

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.

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.

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.

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.

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.

Risk Factors for Introduction of Bovine Herpesvirus 1 (BoHV-1) Into Cattle Herds: A Systematic European Literature Review.

Given that bovine herpesvirus 1 (BoHV-1) -the causative agent of Infectious Bovine Rhinotracheitis (IBR)- is still endemic in most European countries, BoHV-1 free herds are subject to a considerable risk of (re)introduction of the virus. The aim of this literature review was to describe published, quantified risk factors that are relevant for the introduction of BoHV-1. The risk factors described in this study can be used as input for modeling eradication scenarios and for communication on biosecurity measures to stakeholders. A literature search was conducted in November 2020 in two major online search databases, PubMed and Web of Science. The search criteria "risk factor" combined with different synonyms for BoHV-1 were explored, which resulted in 564 hits. Only studies performed in Europe, written in Dutch, English, French, German or Spanish with an English summary and that quantified risk factors for introduction of BoHV-1 into cattle herds were included. Studies had to quantify the risk factors with crude odds ratios (OR), an estimate of the chance of a particular event occurring in an exposed group to a non-exposed group. After checking for duplicates and excluding articles that did not meet the inclusion criteria, 12 publications remained for this review. Risk factors were classified into seven groups, i.e., herd characteristics, management, animal characteristics, purchase, direct animal contact, neighborhood and indirect transmission routes. Most relevant factors for introduction of BoHV-1 into cattle herds include herd size, purchase of cattle, cattle density, age of cattle, distance to neighboring cattle herds and professional visitors. Together with other direct and indirect animal contacts, these factors are important when elimination of BoHV-1 is considered. A closed farming system and protective clothing for professional visitors can eliminate the major routes of introduction of BoHV-1 in cattle herds. To the best of our knowledge, this is the first systematic review solely focussing on measures that can be taken to control introduction of BoHV-1 into cattle herds. Besides testing, focus on managing these (biosecurity) factors will decrease the risk of introducing the virus.

Why Test Purchased Cattle in BVDV Control Programs?

Bovine viral diarrhea (BVD) is controlled in many countries by detection and culling of persistently infected (PI) animals. The most important risk factor for BVDV introduction is purchase. An introduced cow can be PI and transmit the virus to other cattle in the herd. If she is not PI but is pregnant, there is still a risk because the subsequently born calf may be PI, when she encountered the virus in early pregnancy. To control this risk, all cows > 1 year from non-BVDV-free herds that are introduced in herds that participate in the Dutch BVDV control program are tested for virus and antibodies. Depending on the results, subsequent measures such as suspension of the BVDV-free status, removing the animals from the herd, or testing the off-spring of the cow for virus, are undertaken. The aim of this study was to evaluate the results of this risk mitigating measure. Data on cattle movements, calving's, herd-level BVDV status, and animal-level test data were available from all dairy herds that participated in the national BVDV control program (>14,000 dairy herds) for the year 2019. The data were combined and parameters of interest were calculated, i.e., (i) the number of purchased BVD virus positive cattle and (ii) the number of BVD virus positive calves born from purchased cows within 9 months after introduction. In 2019, 217,301 cattle were introduced in Dutch dairy herds that participated in the BVDV control program. Of these, 49,820 were tested for presence of BVD virus and 27 (0.05%) cows introduced in 21 different herds tested BVD virus positive. Out of 46,727 cattle that were tested for antibodies, 20.5% tested positive. The seropositive cows produced 4,341 viable calves, of which 3,062 were tested for virus and subsequently, 40 (1.3%) were found BVD virus positive. These 40 BVD virus positive calves were born in 23 herds. The risk mitigating measure led to detection of 67 BVD virus positive animals in 44 unique herds in 2019. This study makes plausible that the probability and impact of re-introduction of BVDV can be minimized by testing introduced cattle and their subsequently born calves.

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.

An Overview of Current Approaches and Challenges to the Control of Endemic Infectious Cattle Diseases in Albania.

Agriculture is an important production sector in Albania that makes a significant contribution to the gross domestic product (GDP) and employment. The livestock sector contributes more than half of the agricultural GDP. The Albanian cattle population represents 50% of the total livestock units and accounts for 85% of the national milk production, the rest being supplied by small ruminants. Cattle productivity, health and welfare are hindered by infectious diseases, some of which are also transmissible to humans (zoonosis). The aim of this manuscript is to provide an overview of the control of selected regulated and non-EU regulated cattle diseases in Albania and to highlight specific challenges for the Albanian cattle industry. The most important infectious cattle diseases in Albania for which national control and eradication strategies are in place are bovine brucellosis, bovine tuberculosis, and anthrax, which are all zoonotic. Additionally, lumpy skin disease recently emerged in the Balkan region and is currently subject to controls. Most of the available funds and European Union support are allocated to the control of EU regulated zoonotic diseases. For control of non-EU regulated cattle diseases, no funds are available resulting in the lack of national control programmes (CPs). Based on research, clinical investigations and laboratory results, several non-EU regulated cattle infectious diseases appear endemic in Albanian dairy farms. While no national CPs exist for any of them, regional initiatives are available on a voluntary basis to control infectious bovine rhinotracheitis and bovine viral diarrhea. In the voluntary CPs, there is no monitored requirement to prove disease freedom of purchased animals and to re-evaluate the herd's free status after the introduction of animals into a herd. Data on animal movements that are routinely collected could potentially be used to control the risk of purchase, but quality needs to be further improved to increase its usefulness in disease CPs. This overview aims to collate existing information on the CPs implemented in Albania and to evaluate these to highlight gaps and threats in disease control, as well as opportunities and strengths through a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, with the goal of providing a framework for the future implementation of animal disease control measures in Albania.

Existence and Quality of Data on Control Programs for EU Non-regulated Cattle Diseases: Consequences for Estimation and Comparison of the Probability of Freedom From Infection.

Some European countries have successfully implemented country-specific control programs (CPs) for infectious cattle diseases that are not regulated or are regulated only to a limited extent at the European Union (EU) level. Examples of such diseases include bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR), and Johne's disease (JD). The CPs vary between countries in the design and quality of collected data as well as methods used to detect infection and estimate prevalence or probability of freedom from infection. Differences in disease status between countries and non-standardized approaches to assess freedom from infection pose a risk for countries with CPs for non-regulated diseases as infected animals may influence the progress of the disease control or eradication program. The implementation of output-based standards allows estimation and comparison of the probability of freedom for non-regulated cattle diseases in European countries. The aim of the current study was to assess the existence and quality of data that could be used for estimating freedom from infection in European countries. The online data collection tool was sent to 32 countries participating in the SOUND control COST Action and was completed by 24 countries. Data on cattle demographics and data from CPs of IBR and BVD exist in more than 50% of the response countries. However, data describing risk factors and CP of JD was reported as existing in <25% of the countries. The overall quality of data in the sections on demographics and CPs of IBR and BVD were evaluated as "good", but risk factors and JD data were mostly evaluated as "fair." Data quality was considered less good mainly due to two quality criteria: accessibility and accuracy. The results of this study show that the quantity and quality of data about cattle populations and CPs are relatively similar in many surveyed countries. The outcome of this work provides an overview of the current situation in the European countries regarding data on EU non-regulated cattle diseases and will further assist in the development and implementation of output-based standards.

Assessment of Evaluation Tools for Integrated Surveillance of Antimicrobial Use and Resistance Based on Selected Case Studies.

Regular evaluation of integrated surveillance for antimicrobial use (AMU) and resistance (AMR) in animals, humans, and the environment is needed to ensure system effectiveness, but the question is how. In this study, six different evaluation tools were assessed after being applied to AMU and AMR surveillance in eight countries: (1) ATLASS: the Assessment Tool for Laboratories and AMR Surveillance Systems developed by the Food and Agriculture Organization (FAO) of the United Nations, (2) ECoSur: Evaluation of Collaboration for Surveillance tool, (3) ISSEP: Integrated Surveillance System Evaluation Project, (4) NEOH: developed by the EU COST Action "Network for Evaluation of One Health," (5) PMP-AMR: The Progressive Management Pathway tool on AMR developed by the FAO, and (6) SURVTOOLS: developed in the FP7-EU project "RISKSUR." Each tool was scored using (i) 11 pre-defined functional aspects (e.g., workability concerning the need for data, time, and people); (ii) a strengths, weaknesses, opportunities, and threats (SWOT)-like approach of user experiences (e.g., things that I liked or that the tool covered well); and (iii) eight predefined content themes related to scope (e.g., development purpose and collaboration). PMP-AMR, ATLASS, ECoSur, and NEOH are evaluation tools that provide a scoring system to obtain semi-quantitative results, whereas ISSEP and SURVTOOLS will result in a plan for how to conduct evaluation(s). ISSEP, ECoSur, NEOH, and SURVTOOLS allow for in-depth analyses and therefore require more complex data, information, and specific training of evaluator(s). PMP-AMR, ATLASS, and ISSEP were developed specifically for AMR-related activities-only ISSEP included production of a direct measure for "integration" and "impact on decision making." NEOH and ISSEP were perceived as the best tools for evaluation of One Health (OH) aspects, and ECoSur as best for evaluation of the quality of collaboration. PMP-AMR and ATLASS seemed to be the most user-friendly tools, particularly designed for risk managers. ATLASS was the only tool focusing specifically on laboratory activities. Our experience is that adequate resources are needed to perform evaluation(s). In most cases, evaluation would require involvement of several assessors and/or stakeholders, taking from weeks to months to complete. This study can help direct future evaluators of integrated AMU and AMR surveillance toward the most adequate tool for their specific evaluation purpose.

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.

Latent class analysis to assess whole-genome sequencing versus broth microdilution for monitoring antimicrobial resistance in livestock.

Antimicrobial resistance (AMR) monitoring in animals is performed in commensal Escherichia coli, and other microorganisms relevant for human or veterinary health. Due to advances in the field and major reductions in cost, it is expected that whole-genome sequencing (WGS)-based antimicrobial susceptibility testing (AST) will (partly) replace culture-based AST. So far, no studies have been performed without using culture-based AST as the gold standard. Our aim was to use Bayesian latent class analysis to evaluate the accuracy of susceptibility testing of commensal E. coli by WGS-based AST versus culture-based AST as this test does not assume a gold standard. OpenBUGS was used to model two independent tests in three animal populations (N = 150, 50 bacterial isolates per population): veal calves, pigs, and broilers. This resulted in the first estimation of sensitivity and specificity of WGS-based AST versus culture-based AST to detect AMR without a gold standard. Both methods had high sensitivity (>0.92, lowest limit probability interval: 0.76) and specificity was generally high for both methods for all antimicrobial classes except for aminoglycosides and macrolides. We compared WGS results for different length and identity settings (%) of gene alignment and found few differences between the 60/90, 90/90 and 95/95 settings. We recommend to further investigate sensitivity and specificity of WGS-based AST by means of latent class analysis, especially for low-prevalent resistance.

Key Learnings During the Development of a Generic Data Collection Tool to Support Assessment of Freedom of Infection in Cattle Herds.

Various European Member States have implemented control or eradication programmes for endemic infectious diseases in cattle. The design of these programmes varies between countries and therefore comparison of the outputs of different control programmes is complex. Although output-based methods to estimate the confidence of freedom resulting from these programmes are under development, as yet there is no practical modeling framework applicable to a variety of infectious diseases. Therefore, a data collection tool was developed to evaluate data availability and quality and to collect actual input data required for such a modeling framework. The aim of the current paper is to present the key learnings from the process of the development of this data collection tool. The data collection tool was developed by experts from two international projects: STOC free (Surveillance Tool for Outcome-based Comparison of FREEdom from infection, www.stocfree.eu) and SOUND control (Standardizing OUtput-based surveillance to control Non-regulated Diseases of cattle in the EU, www.sound-control.eu). Initially a data collection tool was developed for assessment of freedom of bovine viral diarrhea virus in six Western European countries. This tool was then further generalized to enable inclusion of data for other cattle diseases i.e., infectious bovine rhinotracheitis and Johne's disease. Subsequently, the tool was pilot-tested by a Western and Eastern European country, discussed with animal health experts from 32 different European countries and further developed for use throughout Europe. The developed online data collection tool includes a wide range of variables that could reasonably influence confidence of freedom, including those relating to cattle demographics, risk factors for introduction and characteristics of disease control programmes. Our results highlight the fact that data requirements for different cattle diseases can be generalized and easily included in a data collection tool. However, there are large differences in data availability and comparability across European countries, presenting challenges to the development of a standardized data collection tool and modeling framework. These key learnings are important for development of any generic data collection tool for animal disease control purposes. Further, the results can facilitate development of output-based modeling frameworks that aim to calculate confidence of freedom from disease.