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The collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs. European Food Safety Authority (EFSA)

Amoebic gill disease (AGD) and complex gill disease (CGD) are the most significant marine gill diseases in salmon aquaculture in Scotland. Little is published about diagnostic performance of tests to detect these diseases, making it difficult to interpret test results. We estimated diagnostic sensitivity (DSe) and specificity (DSp) of common tests for AGD (gross AGD score, qPCR for Neoparamoeba perurans, histopathology) and CGD (gross proliferative gill disease (PGD) score, gross total gill score, histopathology). Because specifications in our sampling protocol implemented to encourage consistency across the farms might affect diagnostic performance of histopathology (historically the reference standard for gill diseases), we used Bayesian latent class models without reference standard. Cases and non-cases were based on less, medium, and severe stringent case definitions, representing different cut-off levels for the different tests. Gross gill scores for both diseases were excellent in designating non-diseased fish, DSps were generally around 1. To detect CGD, DSe of gross total gill score and gross PGD score were between respectively 0.81 (0.73 - 0.91 lower to upper 95% credible interval) and 0.53 (0.46 - 0.64) for medium stringent case definitions, and to detect AGD the DSe for the gross AGD score was between 0.53 (0.48-0.57) and 0.14 (0.07 - 0.22) for respectively the less and severe stringent case definition. Thus, gross gill scores were medium to good in designating truly diseased fish, implying some false negatives are expected. For CGD the DSe for gross total gill scores were the highest, for AGD it was the qPCR test at a DSe of 0.92 (0.86 - 0.99). For both diseases, DSe was lowest for histopathology, e.g. 0.23 (0.16 - 0.30) for AGD and 0.1 (0.07 - 0.14) for CGD under medium stringent case definitions, perhaps due to collecting the second gill arch on the right rather than the worst affected arch, whilst PCR sampling and gross gill scoring included multiple (PCR) or all (gross scoring) gill arches. The diagnostic goals of these tests differ; gross gill scoring provides a low-cost presumptive diagnosis, PCR a non-lethal confirmation of the presence of a specific pathogen and histopathology provides information on the underlying aetiology of gill damage as well as the extent, severity, and chronology of gill disease. An effective gill health surveillance strategy is likely to incorporate multiple diagnostic tools used in a complementary manner.

Cattle are reservoirs for Shiga toxin Escherichia coli (STEC), bacteria shed in animal feces. Humans are infected through consumption of contaminated food or water and by direct contact, causing serious disease and kidney failure in the most vulnerable., Cattle are a reservoir for Shiga toxin-producing Escherichia coli (STEC), zoonotic pathogens that cause serious clinical disease. Scotland has a higher incidence of STEC infection in the human population than the European average. The aim of this study was to investigate the prevalence and epidemiology of non-O157 serogroups O26, O103, O111, and O145 and Shiga toxin gene carriage in Scottish cattle. Fecal samples (n = 2783) were collected from 110 herds in 2014 and 2015 and screened by real-time PCR. Herd-level prevalence (95% confidence interval [CI]) for O103, O26, and O145 was estimated as 0.71 (0.62, 0.79), 0.43 (0.34, 0.52), and 0.23 (0.16, 0.32), respectively. Only two herds were positive for O111. Shiga toxin prevalence was high in both herds and pats, particularly for stx2 (herd level: 0.99; 95% CI: 0.94, 1.0). O26 bacterial strains were isolated from 36 herds on culture. Fifteen herds yielded O26 stx-positive isolates that additionally harbored the intimin gene; six of these herds shed highly pathogenic stx2-positive strains. Multiple serogroups were detected in herds and pats, with only 25 herds negative for all serogroups. Despite overlap in detection, regional and seasonal effects were observed. Higher herd prevalence for O26, O103, and stx1 occurred in the South West, and this region was significant for stx2 at the pat level (P = 0.015). Significant seasonal variation was observed for O145 prevalence, with the highest prevalence in autumn (P = 0.032). Negative herds were associated with Central Scotland and winter. Herds positive for all serogroups were associated with autumn and larger herd size and were not housed at sampling. IMPORTANCE Cattle are reservoirs for Shiga toxin-producing Escherichia coli (STEC), bacteria shed in animal feces. Humans are infected through consumption of contaminated food or water and by direct contact, resulting in serious disease and kidney failure in the most vulnerable. The contribution of non-O157 serogroups to STEC illness was underestimated for many years due to the lack of specific tests. Recently, non-O157 human cases have increased, with O26 STEC of particular note. It is therefore vital to investigate the level and composition of non-O157 in the cattle reservoir and to compare them historically and by the clinical situation. In this study, we found cattle prevalence high for toxin, as well as for O103 and O26 serogroups. Pathogenic O26 STEC were isolated from 14% of study herds, with toxin subtypes similar to those seen in Scottish clinical cases. This study highlights the current risk to public health from non-O157 STEC in Scottish cattle.

Background Knowledge of Ixodes ricinus tick distribution is critical for surveillance and risk management of transmissible tick-borne diseases such as Lyme borreliosis. However, as the ecology of I. ricinus is complex, and robust long-term geographically extensive distribution tick data are limited, mapping often relies on datasets collected for other purposes. We compared the modelled distributions derived from three datasets with information on I. ricinus distribution (quantitative I. ricinus count data from scientific surveys; I. ricinus presence-only data from public submissions; and a combined I. ricinus dataset from multiple sources) to assess which could be reliably used to inform Public Health strategy. The outputs also illustrate the strengths and limitations of these three types of data, which are commonly used in mapping tick distributions. Methods Using the Integrated Nested Laplace algorithm we predicted I. ricinus abundance and presence–absence in Scotland and tested the robustness of the predictions, accounting for errors and uncertainty. Results All models fitted the data well and the covariate predictors for I. ricinus distribution, i.e. deer presence, temperature, habitat, index of vegetation, were as expected. Differences in the spatial trend of I. ricinus distribution were evident between the three predictive maps. Uncertainties in the spatial models resulted from inherent characteristics of the datasets, particularly the number of data points, and coverage over the covariate range used in making the predictions. Conclusions Quantitative I. ricinus data from scientific surveys are usually considered to be gold standard data and we recommend their use where high data coverage can be achieved. However in this study their value was limited by poor data coverage. Combined datasets with I. ricinus distribution data from multiple sources are valuable in addressing issues of low coverage and this dataset produced the most appropriate map for national scale decision-making in Scotland. When mapping vector distributions for public-health decision making, model uncertainties and limitations of extrapolation need to be considered; these are often not included in published vector distribution maps. Further development of tools to better assess uncertainties in the models and predictions are necessary to allow more informed interpretation of distribution maps.

The modelling of disease spread is crucial to the farming industry and policy makers. In some of these industries, excellent data exist on animal movements, along with the networks that these movements create, and allow researchers to model spread of disease (both epidemic and endemic). The Cattle Tracing System is an online recording system for cattle births, deaths and between-herd movements in the United Kingdom and is an excellent resource for any researchers interested in networks or modelling infectious disease spread through the UK cattle system. Data exist that cover many years, and it can be useful to know how much change is occurring in a network, to help judge the merit of using historical data within a modelling context. This article uses the data to construct weighted directed monthly movement networks for two distinct periods of time, 2004–2006 and 2015–2017, to quantify by how much the underlying structure of the network has changed. Substantial changes in network structure may influence policy-makers directly or may influence models built upon the network data, and these in turn could impact policy-makers and their assessment of risk. We examined 13 network metrics, ranging from general descriptive metrics such as total number of nodes with movements and total movements, through to metrics to describe the network (e.g., Giant weakly and strongly connected components) and metrics calculated per node (betweenness, degree and strength). Mixed effect models show that there is a statistically significant effect of the period (2004–2006 vs 2015–2017) in the values of nine of the 13 network metrics. For example median total degree decreased by 19%. In addition to examining networks for two time periods, two updates of the data were examined to determine by how much the movement data stored for 2004–2006 had been cleansed between updates. Examination of these updates shows that there are small decreases in problem movements (such as animals leaving slaughterhouses) and therefore evidence of historical data being improved between updates. In combination with the significant effect of period on many of the network metrics, the modification of data between updates provides further evidence that the most recent available data should be used for network modelling. This will ensure that the most representative descriptions of the network are available to provide accurate modelling results to best inform policy makers.

This paper proposes Ir-Man (Information Retrieval for Marine Animal Necropsies), a framework for retrieving discrete information from marine mammal post-mortem reports for statistical analysis. When a marine mammal is reported dead after stranding in Scotland, the carcass is examined by the Scottish Marine Animal Strandings Scheme (SMASS) to establish the circumstances of the animal's death. This involves the creation of a "post-mortem" (or necropsy) report, which systematically describes the body. These semi-structured reports record lesions (damage or abnormalities to anatomical regions) as well as other observations. Observations embedded within these texts are used to determine cause of death. While a cause of death is recorded separately, many other descriptions may be of pathological and epidemiological significance when aggregated and analysed collectively. As manual extraction of these descriptions is costly, time consuming and at times erroneous, there is a need for an automated information retrieval mechanism which is a non-trivial task given the wide variety of possible descriptions, pathologies and species. The Ir-Man framework consists of a new ontology, a lexicon of observations and anatomical terms and an entity relation engine for information retrieval and statistics generation from a pool of necropsy reports. We demonstrate the effectiveness of our framework by creating a rule-based binary classifier for identifying bottlenose dolphin attacks (BDA) in harbour porpoise gross pathology reports and achieved an accuracy of 83.4%.

BACKGROUND Accurate estimation of antimicrobial use (AMU) is important in assessing reduction of agricultural AMU. This cross-sectional study aimed to evaluate several approaches for estimating AMU at the herd level and to report on AMU for beef and dairy farms in Scotland. METHODS Pharmaceutical sales data for 75 cattle herds (2011-2015) were screened for antimicrobial products and aggregated by herd and year. Several denominators for usage estimates were calculated and compared for their suitability at the herd level. RESULTS The median total mass of active ingredient sold per kg of bovine livestock was 9.5 mg/kg for beef herds and 14.3 mg/kg for dairy herds. The 'highest priority critically important' antimicrobials (HPCIA) were by total mass of active ingredient, 10.6% of all sales; by total defined daily dose veterinary (DDDVet), 29.8% and by DCDvet, 20.0%. These are the first estimates of AMU for beef cattle in the UK, and for cattle of any kind in Scotland. Estimates of herd-level usage based on population correction unit (PCU) were sensitive to low values for PCU for specific herd-years due to their demographic composition. CONCLUSION Pharmaceutical sales data can provide useful estimates of AMU, but estimating usage per PCU is not appropriate for comparing groups of cattle with different demographic compositions or for setting herd-level targets. Total mass of active ingredient per kilogram of livestock is more stable and hence suitable than PCU-based methods for assessing AMU at the herd level.

When assessing the role of live animal trade networks in the spread of infectious diseases in livestock, attention has focused mainly on direct movements of animals between premises, whereas the role of haulage vehicles used during transport, an indirect route for disease transmission, has largely been ignored. Here, we have assessed the impact of sharing haulage vehicles from livestock transport service providers on the connectivity between farms as well as on the spread of swine infectious diseases in Great Britain (GB). Using all pig movement records between April 2012 and March 2014 in GB, we built a series of directed and weighted static multiplex networks consisting of two layers of identical nodes, where nodes (farms) are linked either by (1) the direct movement of pigs and (2) the shared use of haulage vehicles. The haulage contact definition integrates the date of the move and the duration Δs that lorries are left contaminated by pathogens, hence accounting for the temporal aspect of contact events. For increasing Δs, descriptive network analyses were performed to assess the role of haulage on network connectivity. We then explored how viruses may spread throughout the GB pig sector by computing the reproduction number R. Our results showed that sharing haulage vehicles increases the number of contacts between farms by > 50% and represents an important driver of disease transmission. In particular, sharing haulage vehicles, even if < Δs1 day, will limit the benefit of the standstill regulation, increase the number of premises that could be infected in an outbreak, and more easily raise R above 1. This work confirms that sharing haulage vehicles has significant potential for spreading infectious diseases within the pig sector. The cleansing and disinfection process of haulage vehicles is therefore a critical control point for disease transmission risk mitigation.

The antibody seroprevalence of young stock can be a useful indicator of recent or current infection in a herd. We examine the factors that contribute to the assessment of herd exposure to disease, via spot testing for antibody, using bovine viral diarrhoea virus (BVDv) as an example. A statistical distribution of seroprevalences for BVDv in beef herds identified three groups of herds: low, intermediate and high within-herd BVDv antibody seroprevalence. We tested two assumptions –the intermediate seroprevalence group of herds is assumed to be negative for BVDv at the herd level and alternatively if this group is assumed to be positive. We found that: The herd-level sensitivity and specificity are sensitive to the assumption regarding the herds with intermediate seroprevalence. If an appropriate cut-point is chosen, reducing the sample size from ten to five does not produce a large drop in herd-level test performance. Increasing the cut-point may be valuable at the outset of an eradication programme. Increasing the sample size and decreasing the cut-point is advantageous towards the end of an eradication programme, to minimise the risk of positive herds being misclassified. The framework presented here illustrates how seroprevalence screening may be understood and assessed.

The BVDFree Scheme, the national voluntary programme for the elimination of BVD from cattle herds in England, was launched on July 1, 2016. Cattle keepers can join BVDFree online (bvdfree.org.uk) or by completing a BVDFree registration form. Over 1000 farmers registered with BVDFree in the first year of operation. Laboratories designated by BVDFree upload the results of testing for BVD virus and for BVD antibodies to the BVDFree database. 40 220 unique records pertaining to tests for BVD were uploaded to the database in the first year of operation. Of the 32 909 samples from individual animals tested for presence of BVD virus, 180 (0.55%) were positive and 20 (0.06%) were inconclusive. Of 2853 samples from individual animals tested for presence of antibodies to BVD virus, 286 (10%) were positive. In 2018 the BVDFree Scheme will introduce a process for assigning a BVDFree herd status. The backing of veterinary surgeons and veterinary practices and all organisations which have signed the BVD Statement of Intent for BVDFree is key to improving engagement with the BVDFree Scheme and achieving the aim of the Scheme which is to deliver the next generation of cattle free of BVD to the next generation of farmers.

Small-scale keepers are less likely to engage with production organisations and may therefore be less aware of legislation, rules and biosecurity practices which are implemented in the livestock sector. Their role in the transmission of endemic and exotic diseases is not well studied, but is believed to be important. The authors use small-scale pig keepers in Scotland as an example of how important small-scale livestock keepers might be for national biosecurity. In Scotland more than two thirds of pig producers report that they keep less than 10 pigs, meaning that biosecurity practices and pig health status on a substantial number of holdings are largely unknown; it is considered important to fill this knowledge gap. A questionnaire was designed and implemented in order to gather some of this information. The questionnaire comprised a total of 37 questions divided into seven sections (location of the enterprise, interest in pigs, details about the pig enterprise, marketing of pigs, transport of pigs, pig husbandry, and pig health/biosecurity). Over 610 questionnaires were sent through the post and the questionnaire was also available online. The questionnaire was implemented from June to October 2013 and 135 questionnaires were returned by target respondents. The responses for each question are discussed in detail in this paper. Overall, our results suggest that the level of disease identified by small-scale pig keepers is low but the majority of the small-scale pig keepers are mixed farms, with associated increased risk for disease transmission between species. Almost all respondents implemented at least one biosecurity measure, although the measures taken were not comprehensive in the majority of cases. Overall as interaction between small-scale keepers and commercial producers exists in Scotland the former can pose a risk for commercial production. This investigation fills gaps in knowledge which will allow industry stakeholders and policy makers to adapt their current disease programmes and contingency plans to the reality of small-scale pig-keeping enterprises' health and biosecurity status. We predict that some conclusions from this work will be relevant to countries with similar pig production systems and importantly some of these findings will relate to small-scale producers in other livestock sectors.

Aquaculture is an increasingly important source of animal protein for a growing global population. Disease is a major constraint to production, with resultant socio-economic impacts for individuals, communities and economies which rely on aquaculture. Aquatic animal health is also strongly influenced by human factors, ranging from international trade regulations to the behaviours of individuals working in aquaculture. This article summarises the human factors associated with aquaculture production using international examples for illustration.

Generic frameworks for the economic analysis of farm animal disease are now well established. The paper, therefore, uses bovine viral diarrhoea (BVD) as an example to explore how these frameworks need to be adapted to fit the characteristics of a particular disease and the specific objectives of the analysis. In the case of BVD, given the relative strength of tests available to correctly identify virus-positive animals, thus enabling them to be culled, the emphasis has been on cost-benefit analysis of regional and national certification/eradication schemes. Such analyses in turn raise interesting questions about farmer uptake and maintenance of certification schemes and the equity and cost-effective implementation of these schemes. The complex epidemiology of BVD virus infections and the long-term, widespread and often occult nature of BVD effects make economic analysis of the disease and its control particularly challenging. However, this has resulted in a wider whole-farm perspective that captures the influence of multiple decisions, not just those directly associated with disease prevention and control. There is a need to include management of reproduction, risk and enterprise mix in the research on farmer decision-making, as all these factors impinge on, and are affected by, the spread of BVD.

Background Escherichia coli O157 is a bacterial pathogen associated with severe disease in humans for which cattle are an important reservoir of infection. The identification of possible risk factors for infection in cattle could facilitate the development of control strategies and interventions to mitigate the risk to human health. The purpose of this study was to utilize data collected in 2014–2015 during the two contemporaneous cross-sectional surveys of the British E. coli O157 in Cattle Study (BECS) to investigate potential risk factors for E. coli O157 status in cattle destined for the food chain. Results In the England & Wales survey only one variable, herd size, was associated with the outcome farm-level E. coli O157 positive status. The odds increased for each additional animal in the herd. In the Scotland survey, as well as a measure of herd size (the number of cattle aged 12–30 months), having brought breeding females on to the farm in the last year also increased the odds, whereas farms sampled in spring were less likely to be positive compared to those sampled in autumn. On the positive farms, in both surveys, an increase in the proportion of pats positive for E. coli O157 was associated with animals being housed at the time of sampling. However, the effect of housing on pat-level prevalence within positive groups was lower on farms from England & Wales than from Scotland (OR 0.45 (95% C.I. 0.24–0.86)). Conclusion For the first time, factors associated with farm-level E. coli O157 status have been investigated in two contemporaneous surveys with comparable study design. Although factors associated with farm-level E. coli O157 status differed between the two surveys, one consistent factor was an association with a measure of herd size. Factors associated with the proportion of E. coli O157 positive pats within a positive farm were similar in both surveys but differed from those associated with farm-level status. These findings raise the hypothesis that measures to protect public health by reducing the risk from cattle may need to be tailored, rather than by assuming that a GB-wide protocol is the best approach.

During the 2001 UK FMD outbreak, local authorities restricted rural access to try to prevent further disease spread by people and animals, which had major socio-economic consequences for rural communities. This study describes the results of qualitative veterinary risk assessments to assess the likelihood of different recreational activities causing new outbreaks of foot and mouth disease, as part of contingency planning for future outbreaks. For most activities, the likelihood of causing new outbreaks of foot and mouth disease is considered to vary from very low to medium depending on the control zone (which is based on distance to the nearest infected premises), assuming compliance with specified mitigation strategies. The likelihood of new outbreaks associated with hunting, shooting, stalking, and equestrian activities is considered to be greater. There are areas of significant uncertainty associated with data paucity, particularly regarding the likelihood of transmission via fomites. This study provides scientific evidence to underpin refinement of rural access management plans and inform decision-making in future disease outbreaks.

Determining the Bovine Viral Diarrhoea (BVD) infection status of cattle herds is a challenge for control and eradication schemes. Given the changing dynamics of BVD virus (BVDV) antibody responses in cattle, classifying herds based on longitudinal changes in the results of BVDV antibody tests could offer a novel, complementary approach to categorising herds that is less likely than the present system to result in a herd’s status changing from year to year, as it is more likely to capture the true exposure dynamics of the farms. This paper describes the dynamics of BVDV antibody test values (measured as percentage positivity (PP)) obtained from 15,500 bovines between 2007 and 2010 from thirty nine cattle herds located in Scotland and Northern England. It explores approaches of classifying herds based on trend, magnitude and shape of their antibody PP trajectories and investigates the epidemiological similarities between farms within the same cluster. Gaussian mixture models were used for the magnitude and shape clustering. Epidemiologically meaningful clusters were obtained. Farm cluster membership depends on clustering approach used. Moderate concordance was found between the shape and magnitude clusters. These methods hold potential for application to enhance control efforts for BVD and other infectious livestock diseases.

There are calls from policy-makers and industry to use existing data sources to contribute to livestock surveillance systems, especially for syndromic surveillance. However, the practical implications of attempting to use such data sources are challenging; development often requires incremental steps in an iterative cycle. In this study the utility of business operational data from a voluntary fallen stock collection service was investigated, to determine if they could be used as a proxy for the mortality experienced by the British sheep population. Retrospectively, Scottish ovine fallen stock collection data (2011–2014) were transformed into meaningful units for analysis, temporal and spatial patterns were described, time-series methods and a temporal aberration detection algorithm applied. Distinct annual and spatial trends plus seasonal patterns were observed in the three age groups investigated. The algorithm produced an alarm at the point of an historic known departure from normal (April 2013) for two age groups, across Scotland as a whole and in specific postcode areas. The analysis was then extended. Initially, to determine if similar methods could be applied to ovine fallen stock collections from England and Wales for the same time period. Additionally, Scottish contemporaneous laboratory diagnostic submission data were analyzed to see if they could provide further insight for interpretation of statistical alarms. Collaboration was required between the primary data holders, those with industry sector knowledge, plus veterinary, epidemiological and statistical expertise, in order to turn data and analytical outcomes into potentially useful information. A number of limitations were identified and recommendations were made as to how some could be addressed in order to facilitate use of these data as surveillance “intelligence.” e.g., improvements to data collection and provision. A recent update of the fallen stock collections data has enabled a longer temporal period to be analyzed, with evidence of changes made in line with the recommendations. Further development will be required before a functional system can be implemented. However, there is potential for use of these data as: a proxy measure for mortality in the sheep population; complementary components in a future surveillance system, and to inform the design of additional surveillance system components.

A vet at Scotland’s Rural College, his practical knowledge and experience enabled him to support rural veterinary practices, as well as to foster his own interest in wildlife.

Traditional indicator-based livestock surveillance has been focused on case definitions, definitive diagnoses and laboratory confirmation. The use of syndromic disease surveillance would increase the population base from which animal health data are captured and facilitate earlier detection of new and re-emerging threats to animal health. Veterinary practitioners could potentially play a vital role in such activities. In a pilot study, specialist private veterinary practitioners (PVP) working in the English pig industry were asked to collect and transfer background data and disease incident reports for pig farms visited during the study period. Baseline data from 110 pig farms were received, along with 68 disease incident reports. Reports took an average of approximately 25 minutes to complete. Feedback from the PVPs indicated that they saw value in syndromic surveillance. Maintenance of anonymity in the outputs would be essential, as would timely access for the PVPs to relevant information on syndromic trends. Further guidance and standardisation would also be required. Syndromic surveillance by PVPs is possible for the pig industry. It has potential to fill current gaps in the collection of animal health data, as long as the engagement and participation of data providers can be obtained and maintained.

[This corrects the article DOI: 10.1371/journal.pone.0198436.].

SUMMARYThe incursion of Bluetongue disease into the UK and elsewhere in Northern Europe in 2008 raised concerns about maintaining an appropriate level of preparedness for the encroachment of exotic diseases as circumstances and risks change. Consequently the Scottish government commissioned the present study to inform policy on the specific threat of Bluetongue virus 8 (BTV8) incursion into Scotland. An interdisciplinary expert panel, including BTV and midge experts, agreed a range of feasible BTV incursion scenarios, patterns of disease spread and specific control strategies. The study was primarily desk-based, applying quantitative methodologies with existing models, where possible, and utilizing data already held by different members of the project team. The most likely distribution of the disease was explored given Scotland's agricultural systems, unique landscape and climate. Epidemiological and economic models are integrated in an ex-ante cost-benefit appraisal of successful prevention of hypothetical BTV8 incursion into Scotland under various feasible incursion scenarios identified by the interdisciplinary panel. The costs of current public and private surveillance efforts are compared to the benefits of the avoided losses of potential disease outbreaks. These avoided losses included the direct costs of alternative vaccination, protection zone (PZ) strategies and their influence on other costs arising from an outbreak as predicted by the epidemiological model. Benefit-cost ratios were ranked within each incursion scenario to evaluate alternative strategies. In all incursion scenarios, the ranking indicated that a strategy, including 100% vaccination within a PZ set at Scottish counties along the England–Scotland border yielded the least benefit in terms of the extent of avoided outbreak losses (per unit cost). The economically optimal vaccination strategy was the scenario that employed 50% vaccination and all Scotland as a PZ. The results provide an indicator of how resources can best be targeted for an efficient ex-ante control strategy.

SUMMARYEscherichia coliO157 are zoonotic bacteria for which cattle are an important reservoir. Prevalence estimates forE. coliO157 in British cattle for human consumption are over 10 years old. A new baseline is needed to inform current human health risk. The BritishE. coliO157 in Cattle Study (BECS) ran between September 2014 and November 2015 on 270 farms across Scotland and England & Wales. This is the first study to be conducted contemporaneously across Great Britain, thus enabling comparison between Scotland and England & Wales. Herd-level prevalence estimates forE. coliO157 did not differ significantly for Scotland (0·236, 95% CI 0·166–0·325) and England & Wales (0·213, 95% CI 0·156–0·283) (P= 0·65). The majority of isolates were verocytotoxin positive. A higher proportion of samples from Scotland were in the super-shedder category, though there was no difference between the surveys in the likelihood of a positive farm having at least one super-shedder sample.E. coliO157 continues to be common in British beef cattle, reaffirming public health policy that contact with cattle and their environments is a potential infection source.

Animal diseases are global issues affecting the productivity and financial profitability of affected farms. Johne’s disease is distributed on farms worldwide and is an endemic contagious bacterial infection in ruminants caused by Mycobacterium avium subspecies paratuberculosis. In cattle, the clinical disease manifests itself as chronic enteritis resulting in reduced production, weight loss, and eventually death. Johne’s disease is prevalent in the UK, including Scotland. Direct costs and losses associated with Johne’s disease have been estimated in previous research, confirming an important economic impact of the disease in UK herds. Despite this, the distributional impact of Johne’s disease among milk consumers and producers in Scotland has not been estimated. In this paper, we evaluate the change in society’s economic welfare, namely to dairy producers (i.e. infected and uninfected herds) and milk consumers in Scotland induced by the introduction of Johne’s disease in the national Scottish dairy herd. At the national-level, we conclude that the economic burden falls mainly on producers of infected herds and, to a lesser extent, milk consumers, while producers of uninfected herds benefit from the presence of Johne’s. An infected producer’s loss per cow is approximately two times larger in magnitude than that of an uninfected producer’s gain. Such economic welfare estimates are an important comparison of the relative costs of national herd prevalence and the wider economic welfare implications for both producers and consumers. This is particularly important from a policy, public good, cost sharing, and human health perspective. The economic welfare framework presented in this paper can be applied to other diseases to examine the relative burden of society’s economic welfare of alternative livestock disease scenarios. In addition, the sensitivity analysis evaluates uncertainty in economic welfare given limited data and uncertainty in the national herd prevalence, and other input parameters, associated with Johne’s disease in Scotland. Therefore, until the prevalence of Johne’s is better understood, the full economic cost to Scottish dairy herds remains uncertain but in the meantime the sensitivity analysis evaluates the robustness of economic welfare to such uncertainties.

Liver fluke infection causes serious disease (fasciolosis) in cattle and sheep in many regions of the world, resulting in production losses and additional economic consequences due to condemnation of the liver at slaughter. Liver fluke depends on mud snails as an intermediate host and infect livestock when ingested through grazing. Therefore, environmental factors play important roles in infection risk and climate change is likely to modify this. Here, we demonstrate how slaughterhouse data can be integrated with other data, including animal movement and climate variables to identify environmental risk factors for liver fluke in cattle in Scotland. We fitted a generalized linear mixed model to the data, with exposure-weighted random and fixed effects, an approach which takes into account the amount of time cattle spent at different locations, exposed to different levels of risk. This enabled us to identify an increased risk of liver fluke with increased animal age, rainfall, and temperature and for farms located further to the West, in excess of the risk associated with a warmer, wetter climate. This model explained 45% of the variability in liver fluke between farms, suggesting that the unexplained 55% was due to factors not included in the model, such as differences in on-farm management and presence of wet habitats. This approach demonstrates the value of statistically integrating routinely recorded slaughterhouse data with other pre-existing data, creating a powerful approach to quantify disease risks in production animals. Furthermore, this approach can be used to better quantify the impact of projected climate change on liver fluke risk for future studies.

Data from 255 Scottish beef suckler herds and 189 Scottish dairy herds surveyed as part of national bovine viral diarrhoea virus (BVDV) prevalence studies from October 2006 to May 2008 were examined retrospectively to determine the relationship between serological status and key performance indicators derived from national cattle movement records. On average, calf mortality rates were 1.35 percentage points higher in seropositive beef herds and 3.05 percentage points higher in seropositive dairy herds than in negative control herds. Seropositive beef herds were also more likely to show increases in calf mortality rates and culling rates between successive years. There were no discernible effects of BVDV on the average age at first calving or calving interval for either herd type. Accompanying questionnaire data revealed that only 27% of beef farmers and 25% of dairy farmers with seropositive herds thought their cattle were affected by BVDV, which suggests that the clinical effects of exposure may be inapparent under field conditions or masked by other causes of reproductive failure and culling. Beef farmers were significantly more likely to perceive a problem when their herd experienced acute changes in calf mortality rates, culling rates, and calving intervals between successive years. However, only 35% of these perceived positive herds were actually seropositive for BVDV. These findings emphasize both the importance of routinely screening herds to determine their true infection status and the potential for using national cattle movement records to identify herds that may be experiencing outbreaks from BVDV or other infectious diseases that impact herd performance.

The paper analyses the impact of a priori determinants of biosecurity behaviour of farmers in Great Britain. We use a dataset collected through a stratified telephone survey of 900 cattle and sheep farmers in Great Britain (400 in England and a further 250 in Wales and Scotland respectively) which took place between 25 March 2010 and 18 June 2010. The survey was stratified by farm type, farm size and region. To test the influence of a priori determinants on biosecurity behaviour we used a behavioural economics method, structural equation modelling (SEM) with observed and latent variables. SEM is a statistical technique for testing and estimating causal relationships amongst variables, some of which may be latent using a combination of statistical data and qualitative causal assumptions. Thirteen latent variables were identified and extracted, expressing the behaviour and the underlying determining factors. The variables were: experience, economic factors, organic certification of farm, membership in a cattle/sheep health scheme, perceived usefulness of biosecurity information sources, knowledge about biosecurity measures, perceived importance of specific biosecurity strategies, perceived effect (on farm business in the past five years) of welfare/health regulation, perceived effect of severe outbreaks of animal diseases, attitudes towards livestock biosecurity, attitudes towards animal welfare, influence on decision to apply biosecurity measures and biosecurity behaviour. The SEM model applied on the Great Britain sample has an adequate fit according to the measures of absolute, incremental and parsimonious fit. The results suggest that farmers’ perceived importance of specific biosecurity strategies, organic certification of farm, knowledge about biosecurity measures, attitudes towards animal welfare, perceived usefulness of biosecurity information sources, perceived effect on business during the past five years of severe outbreaks of animal diseases, membership in a cattle/sheep health scheme, attitudes towards livestock biosecurity, influence on decision to apply biosecurity measures, experience and economic factors are significantly influencing behaviour (overall explaining 64% of the variance in behaviour). Three other models were run for the individual regions (England, Scotland and Wales). A smaller number of variables were included in each model to account for the smaller sample sizes. Results show lower but still high levels of variance explained for the individual models (about 40% for each country). The individual models’ results are consistent with those of the total sample model. The results might suggest that ways to achieve behavioural change could include ensuring increased access of farmers to biosecurity information and advice sources.

Collection of abattoir data related to public health is common worldwide. Standardised on-going programmes that collect information from abattoirs that inform producers about the presence and frequency of disease that are important to them rather than public health hazards are less common. The three voluntary pig health schemes, implemented in the United Kingdom, are integrated systems which capture information on different macroscopic disease conditions detected in slaughtered pigs. Many of these conditions have been associated with a reduction in performance traits and consequent increases in production costs. The schemes are the Wholesome Pigs Scotland in Scotland, the British Pig Health Scheme in England and Wales and the Pig Regen Ltd. health and welfare checks in Northern Ireland. In this study, four post mortem conditions (pericarditis, milk spots, papular dermatitis and tail damage) were surveyed and analysed over a ten and half year period, with the aim to compare the prevalence, monthly variations, and yearly trends between schemes. Liver milk spot was the most frequently recorded condition while tail damage was the least frequently observed condition. The prevalence of papular dermatitis was relatively low compared to liver milk spot and pericarditis in the three schemes. A general decreasing trend was observed for milk spots and papular dermatitis for all three schemes. The prevalence of pericarditis increased in Northern Ireland and England and Wales; while Scotland in recent years showed a decreasing trend. An increasing trend of tail damage was depicted in Scotland and Northern Ireland until 2013/2014 followed by a decline in recent years compared to that of England and Wales with a decreasing trend over the full study period. Monthly effects were more evident for milk spots and papular dermatitis. Similarity of the modus operandi of the schemes made the comparison of temporal variations and patterns in gross pathology between countries possible over time, especially between countries with similar pig production profile. This study of temporal patterns enables early detection of prevalence increases and alerts industry and researchers to investigate the reasons behind such changes. These schemes are, therefore, valuable assets for endemic disease surveillance, early warning for emerging disease and also for monitoring of welfare outcomes.

Modelling is an important component of contingency planning and control of disease outbreaks. Dynamic network models are considered more useful than static models because they capture important dynamic patterns of farm behaviour as evidenced through animal movements. This study evaluates the usefulness of a dynamic network model of swine fever to predict pre-detection spread via movements of pigs, when there may be considerable uncertainty surrounding the time of incursion of infection. It explores the utility and limitations of animal movement data to inform such models and as such, provides some insight into the impact of improving traceability through real-time animal movement reporting and the use of electronic animal movement databases. The study concludes that the type of premises and uncertainty of the time of disease incursion will affect model accuracy and highlights the need for improvements in these areas.

The eradication of BVD in the UK is technically possible but appears to be socially untenable. The following study explored farmer attitudes to BVD control schemes in relation to advice networks and information sharing, shared aims and goals, motivation and benefits of membership, notions of BVD as a priority disease and attitudes toward regulation. Two concepts from the organisational management literature framed the study: citizenship behaviour where actions of individuals support the collective good (but are not explicitly recognised as such) and peer to peer monitoring (where individuals evaluate other’s behaviour). Farmers from two BVD control schemes in the UK participated in the study: Orkney Livestock Association BVD Eradication Scheme and Norfolk and Suffolk Cattle Breeders Association BVD Eradication Scheme. In total 192 farmers participated in the research (133 in-scheme and 59 out of scheme). The findings revealed that group helping and information sharing among scheme members was low with a positive BVD status subject to social censure. Peer monitoring in the form of gossip with regard to the animal health status of other farms was high. Interestingly, farmers across both schemes supported greater regulation with regard to animal health, largely due to the mistrust of fellow farmers following voluntary disease control measures. While group cohesiveness varied across the two schemes, without continued financial inducements, longer-term sustainability is questionable.

Sheep have been proposed as a source of human verocytotoxigenic Escherichia coli infection on a number of occasions but few prevalence studies have focused on identifying rates of carriage of these pathogens in this species. The purpose of this work was to establish the frequency of excretion of E. coli of serogroups O157, O26, O103, O111 and O145 in sheep presented for slaughter in Scotland and to examine their carriage of known virulence determinants. The study involved microbiological isolation of E. coli from 1082 sheep presented for slaughter in four Scottish abattoirs between July 2005 and June 2006. Using faecal enrichment and immunomagnetic separation, the isolation rate from these samples was 3.4 % for E. coli serogroup O157, 5.2 % for E. coli serogroup O26, 2.3 % for E. coli serogroup O103 and 0.1 % for E. coli serogroup O145. E. coli O111 was not isolated. In the last month of testing, which coincided with sorbitol-fermenting E. coli O157 (SFO157) cases in children in Scotland, all 83 recta received were screened and tested negative for SFO157 strains. The study found no verocytotoxin-positive strains amongst the E. coli serogroup O103 or O145 isolates. Verocytotoxin-positive strains were identified amongst isolates of E. coli serotypes O157 : H7 and O26 : H11. E. coli O157 : H7 was not isolated from samples collected between January and March, a statistically significant drop (P

Bovine viral diarrhoea (BVD) is an endemic disease of cattle that causes substantial losses to both beef and dairy production worldwide. The goal of this study was to estimate the prevalence of active BVD virus (BVDV) infection in beef suckler herds in Scotland. Information was collected from 301 herds using a stratified random sampling design based on agricultural census data. Herds were classified as with and without active infection based on the within-herd BVDV seroprevalence in young stock using Bayesian finite mixture modelling. This method accounted for within- and between-herd variability and allowed for classification error by the diagnostic tests. The observed sample data enabled the discrimination of three distinct seroprevalence cohorts. The results provided evidence of active BVDV infection in 16% of herds and no evidence of recent exposure in approximately two thirds of herds. The epidemiological significance of the further 16% of herds containing young stock with a median BVDV seroprevalence of 26.3–38.5% remains unclear. The fact that a large percentage of herds did not show evidence of recent infection is encouraging from an animal health and welfare perspective and the study provides a model for the further exploration of strategies aimed at BVD control at national level.

The prevalence of Pasteurella multocida, a cause of bovine respiratory disease, was studied in a random sample of beef suckler and dairy farms throughout Scotland, by means of a cross-sectional survey. A total of 637 calves from 68 farms from six geographical regions of Scotland were sampled between February and June 2008. Deep nasal swabs were taken, and samples that were culture-positive for P multocida were confirmed by PCR. Prevalence of P multocida was 17 per cent (105 of 616 calves); 47 per cent of farms had at least one positive animal. A higher prevalence was detected in dairy calves than beef calves (P=0.04). It was found that P multocida was associated with Mycoplasma-like organisms (P=0.06) and bovine parainfluenza type 3 virus (BPI-3) (P=0.04), detected by culture and quantitative PCR of nasal swabs, respectively. Detection of P multocida was not associated with bovine respiratory syncytial virus (BRSV), bovine herpesvirus type 1 (BoHV-1) or bovine viral diarrhoea virus (BVDV). Mycoplasma-like organisms, BPI-3, BRSV, BoHV-1 and BVDV were detected in 58, 17, four, 0 and eight calves, on 25, five, two, 0 and five of the 68 farms, respectively.

Ascariosis is the most important internal parasitism present worldwide in farmed pigs. Milk spots are healing lesions occurring when Ascaris suum larvae migrate through the liver. This study aimed to identify current husbandry practices (e.g. wet/compound feeding, outdoors/indoors production, bedded/slatted floors) that influence the prevalence of milk spots in batches of slaughtered pigs, accounting for geographical locations and seasonality. Farm information was accessed through the British farm quality assurance programmes (QAPs) and information on milk spots was obtained from the pig abattoir based health schemes. Two working datasets were created. The first consisted of 505 farms recruited from the whole of Great Britain (GB). The second combined 338 farms from England and Wales (EW) with housing and feed category-specific information (e.g. for growers and finishers separately), which was not fully available for inclusion in the previous dataset. The variables were studied in multivariable beta-binomial models with the presence of milk spots being the response variable. Solid floor with bedding appeared as a risk factor, OR 1.52 (95% confidence intervals (CI) 1.26–1.85) for the GB sample, and OR 1.47 (CI 1.19–1.81) for the EW subset. Those GB herds that had all the stages of production indoors appeared to be at lower risk of milk spots (OR 0.4, CI 0.32–0.49). Changes were detected within year, with higher risk of milk spots in the second 6 months of the year OR 1.17 (CI 1.02–1.35) in the GB sample and 1.21 (95% CI 1.04–1.41) in EW farms. Overall this study suggests that those husbandry practices facilitating optimal levels of hygiene posed lower risk of milk spots in slaughtered pigs, potentially reflecting lower levels of ascariosis in the later stages of production.

Following the arrival of bluetongue virus serotype 8 (BTV-8) in southeast England in September 2007, the Scottish Government commissioned research to assess the economic consequences of a BTV-8 incursion to Scotland. Here we present the first component of the assessment, which entailed identifying feasible incursion scenarios for the virus. Our analyses focused on three routes of introduction: wind-borne dispersal of infected vectors, import of infected animals and northwards spread of BTV from affected areas in GB. These analyses were further refined by considering the spatial and temporal variation in the probability of onward transmission from an initial incursion. Keywords: Epidemiology, Culicoides, Wind-borne dispersal, Animal movements