Bovine mortality: the utility of two data sources for the provision of population-level surveillance intelligence

Introduction

The use of existing data to provide surveillance intelligence is widely advocated but often presents considerable challenges. Two data sources could be used as proxies for the mortality experienced by the Scottish cattle population: deaths recorded in the mandatory register [Cattle Tracing System (CTS)] and fallen stock collections by the National Fallen Stock Company (NSFCo) with a nationwide voluntary membership.

Methods

Data for the period 2011-2016 were described and compared to establish their strengths and limitations. Similarities and differences in their temporal, seasonal and spatial patterns were examined overall, at postcode area level and for different age groups. Temporal aberration detection algorithms (TADA) were fitted.

Results

Broadly, similar patterns were observed in the two datasets; however, there were some notable differences. The observed seasonal, annual and spatial patterns match expectations, given knowledge of Scottish cattle production systems. The registry data provide more comprehensive coverage of all areas of Scotland, while collections data provide a more comprehensive measure of the mortality experienced in 0-1-month-old calves.

Discussion

Consequently, estimates of early calf mortality and their impact on the livestock sector made using CTS, or successor registers, will be under-estimates. This may apply to other registry-based systems. Fitted TADA detected points of deviations from expected norms some of which coincided in the two datasets; one with a known external event that caused increased mortality. We have demonstrated that both data sources do have the potential to be utilized to provide measures of mortality in the Scottish cattle population that could inform surveillance activities. While neither is perfect, they are complementary. Each has strengths and weaknesses, so ideally, a system where they are analyzed and interpreted in parallel would optimize the information obtained for surveillance purposes for epidemiologists, risk managers, animal health policy-makers and the wider livestock industry sector. This study provides a foundation on which to build an operational system. Further development will require improvements in the timeliness of data availability and further investment of resources.

Phylogenetic relationship and virulence composition of Escherichia coli O26:H11 cattle and human strain collections in Scotland; 2002-2020

O26 is the commonest non-O157 Shiga toxin (stx)-producing Escherichia coli serogroup reported in human infections worldwide. Ruminants, particularly cattle, are the primary reservoir source for human infection. In this study, we compared the whole genomes and virulence profiles of O26:H11 strains (n = 99) isolated from Scottish cattle with strains from human infections (n = 96) held by the Scottish Escherichia coli O157/STEC Reference Laboratory, isolated between 2002 and 2020. Bovine strains were from two national cross-sectional cattle surveys conducted between 2002-2004 and 2014-2015. A maximum likelihood phylogeny was constructed from a core-genome alignment with the O26:H11 strain 11368 reference genome. Genomes were screened against a panel of 2,710 virulence genes using the Virulence Finder Database. All stx-positive bovine O26:H11 strains belonged to the ST21 lineage and were grouped into three main clades. Bovine and human source strains were interspersed, and the stx subtype was relatively clade-specific. Highly pathogenic stx2a-only ST21 strains were identified in two herds sampled in the second cattle survey and in human clinical infections from 2010 onwards. The closest pairwise distance was 9 single-nucleotide polymorphisms (SNPs) between Scottish bovine and human strains and 69 SNPs between the two cattle surveys. Bovine O26:H11 was compared to public EnteroBase ST29 complex genomes and found to have the greatest commonality with O26:H11 strains from the rest of the UK, followed by France, Italy, and Belgium. Virulence profiles of stx-positive bovine and human strains were similar but more conserved for the stx2a subtype. O26:H11 stx-negative ST29 (n = 17) and ST396 strains (n = 5) were isolated from 19 cattle herds; all were eae-positive, and 10 of these herds yielded strains positive for ehxA, espK, and Z2098, gene markers suggestive of enterohaemorrhagic potential. There was a significant association (p < 0.001) between nucleotide sequence percent identity and stx status for the bacteriophage insertion site genes yecE for stx2 and yehV for stx1. Acquired antimicrobial resistance genes were identified in silico in 12.1% of bovine and 17.7% of human O26:H11 strains, with sul2, tet, aph(3″), and aph(6″) being most common. This study describes the diversity among Scottish bovine O26:H11 strains and investigates their relationship to human STEC infections.

Overview of Cattle Diseases Listed Under Category C, D or E in the Animal Health Law for Which Control Programmes Are in Place Within Europe

The COST action “Standardising output-based surveillance to control non-regulated diseases of cattle in the European Union (SOUND control),” aims to harmonise the results of surveillance and control programmes (CPs) for selected cattle diseases to facilitate safe trade and improve overall control of cattle infectious diseases. In this paper we aimed to provide an overview on the diversity of control for these diseases in Europe. A selected cattle disease was defined as an infectious disease of cattle with no or limited control at EU level, which is not included in the European Union Animal health law Categories A or B under Commission Implementing Regulation (EU) 2020/2002. A CP was defined as surveillance and/or intervention strategies designed to lower the incidence, prevalence, mortality or prove freedom from a specific disease in a region or country. Passive surveillance, and active surveillance of breeding bulls under Council Directive 88/407/EEC were not considered as CPs. A questionnaire was designed to obtain country-specific information about CPs for each disease. Animal health experts from 33 European countries completed the questionnaire. Overall, there are 23 diseases for which a CP exists in one or more of the countries studied. The diseases for which CPs exist in the highest number of countries are enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis, bovine viral diarrhoea and anthrax (CPs reported by between 16 and 31 countries). Every participating country has on average, 6 CPs (min–max: 1–13) in place. Most programmes are implemented at a national level (86%) and are applied to both dairy and non-dairy cattle (75%). Approximately one-third of the CPs are voluntary, and the funding structure is divided between government and private resources. Countries that have eradicated diseases like enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis and bovine viral diarrhoea have implemented CPs for other diseases to further improve the health status of cattle in their country. The control of the selected cattle diseases is very heterogenous in Europe. Therefore, the standardising of the outputs of these programmes to enable comparison represents a challenge.

The Use of Sheep Movement Data to Inform Design and Interpretation of Slaughterhouse-Based Surveillance Activities

The design of surveillance strategies is often a compromise between science, feasibility, and available resources, especially when sampling is based at fixed locations, such as slaughter-houses. Advances in animal identification, movement recording and traceability should provide data that can facilitate the development, design and interpretation of surveillance activities. Here, for the first time since the introduction of electronic identification of sheep, the utility of a statutory sheep movement database to inform the design and interpretation of slaughter-house based surveillance activities has been investigated. Scottish sheep movement records for 2015–2018 were analyzed in combination with several other data sources. Patterns of off-farm movements of Scottish sheep to slaughter were described and the spatial distribution of several distinct slaughter populations, throughputs and catchment areas for Scottish slaughterhouses were determined. These were used to evaluate the coverage of a convenience-sample slaughter-house based survey for antimicrobial resistance (AMR). In addition, non-slaughter sheep movements within and between Scottish regions were described and inter-and intra-regional movement matrices were produced. There is potential at a number of levels for bias in spatially-associated factors for ovine surveillance activities based at Scottish slaughterhouses. The first is intrinsic because the slaughtered in Scotland population differs from the overall Scottish sheep slaughter population. Other levels will be survey-dependent and occur when the catchment area differs from the slaughtered in Scotland population and when the sampled sheep differ from the catchment area. These are both observed in the AMR survey. Furthermore, the Scottish non-slaughter sheep population is dynamic. Inter-regional movements vary seasonally, driven by the sheep calendar year, structure of the Scottish sheep industry and management practices. These sheep movement data provide a valuable resource for surveillance purposes, despite a number of challenges and limitations that were encountered. They can be used to identify and characterize the spatial origin of relevant populations and so inform the interpretation of existing slaughterhouse-based surveillance activities. They can be used to improve future design by exploring the feasibility and cost:benefit of alternative sampling strategies. Further development could also contribute to other surveillance activities, such as situational awareness and resource allocation, for the benefit of stakeholders.

A description and qualitative comparison of the elements of heterogeneous bovine viral diarrhea control programs that influence confidence of freedom

For endemic infections in cattle that are not regulated at the European Union level, such as bovine viral diarrhea virus (BVDV), European Member States have implemented control or eradication programs (CEP) tailored to their specific situations. Different methods are used to assign infection-free status in CEP; therefore, the confidence of freedom associated with the "free" status generated by different CEP are difficult to compare, creating problems for the safe trade of cattle between territories. Safe trade would be facilitated with an output-based framework that enables a transparent and standardized comparison of confidence of freedom for CEP across herds, regions, or countries. The current paper represents the first step toward development of such a framework by seeking to describe and qualitatively compare elements of CEP that contribute to confidence of freedom. For this work, BVDV was used as a case study. We qualitatively compared heterogeneous BVDV CEP in 6 European countries: Germany, France, Ireland, the Netherlands, Sweden, and Scotland. Information about BVDV CEP that were in place in 2017 and factors influencing the risk of introduction and transmission of BVDV (the context) were collected using an existing tool, with modifications to collect information about aspects of control and context. For the 6 participating countries, we ranked all individual elements of the CEP and their contexts that could influence the probability that cattle from a herd categorized as BVDV-free are truly free from infection. Many differences in the context and design of BVDV CEP were found. As examples, CEP were either mandatory or voluntary, resulting in variation in risks from neighboring herds, and risk factors such as cattle density and the number of imported cattle varied greatly between territories. Differences were also found in both testing protocols and definitions of freedom from disease. The observed heterogeneity in both the context and CEP design will create difficulties when comparing different CEP in terms of confidence of freedom from infection. These results highlight the need for a standardized practical methodology to objectively and quantitatively determine confidence of freedom resulting from different CEP around the world.

Improving the Utility of Voluntary Ovine Fallen Stock Collection and Laboratory Diagnostic Submission Data for Animal Health Surveillance Purposes: A Development Cycle

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.

Multilayer network analysis unravels haulage vehicles as a hidden threat to the British swine industry

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 (a) the direct movement of pigs and (b) the shared use of haulage vehicles. The haulage contact definition integrates the date of the move and the duration Δ s that lorries are left contaminated by pathogens, hence accounting for the temporal aspect of contact events. For increasing Δ s , 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 Δ s  < 1 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 British E. coli O157 in cattle study (BECS): factors associated with the occurrence of E. coli O157 from contemporaneous cross-sectional surveys

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.

Framework for Estimating Indirect Costs in Animal Health Using Time Series Analysis

Traditionally, cost-benefit analyses (CBAs) focus on the direct costs of animal disease, including animal mortality, morbidity, and associated response costs. However, such approaches often fail to capture the wider, dynamic market impacts that could arise. The duration of these market dislocations could last well after an initial disease outbreak. More generally, current approaches also muddle definitions of indirect costs, confusing debate on the scope of the totalities of disease-induced economic impacts. The aim of this work was to clarify definitions of indirect costs in the context of animal diseases and to apply this definition to a time series methodological framework to estimate the indirect costs of animal disease control strategies, using a foot and mouth disease (FMD) outbreak in Scotland as a case study. Time series analysis is an econometric method for analyzing statistical relationships between data series over time, thus allowing insights into how market dynamics may change following a disease outbreak. First an epidemiological model simulated FMD disease dynamics based on alternative control strategies. Output from the epidemiological model was used to quantify direct costs and applied in a multivariate vector error correction model to quantify the indirect costs of alternative vaccine stock strategies as a result of FMD. Indirect costs were defined as the economic losses incurred in markets after disease freedom is declared. As such, our definition of indirect costs captures the knock-on price and quantity effects in six agricultural markets after a disease outbreak. Our results suggest that controlling a FMD epidemic with vaccination is less costly in direct and indirect costs relative to a no vaccination (i.e., "cull only") strategy, when considering large FMD outbreaks in Scotland. Our research clarifies and provides a framework for estimating indirect costs, which is applicable to both exotic and endemic diseases. Standard accounting CBAs only capture activities in isolation, ignore linkages across sectors, and do not consider price effects. However, our framework not only delineates when indirect costs start, but also captures the wider knock-on price effects between sectors, which are often omitted from CBAs but are necessary to support decision-making in animal disease prevention and control strategies.

STOC Free: An Innovative Framework to Compare Probability of Freedom From Infection in Heterogeneous Control Programmes

The existence, stage of eradication and design of control programmes (CPs) for diseases that are not regulated by the EU differ between Member States. When freedom from infection is reached or being pursued, safe trade is essential to protect or reach that status. The aim of STOC free, a collaborative project between six countries, is to develop and validate a framework that enables a transparent and standardized comparison of confidence of freedom for CPs across herds, regions or countries. The framework consists of a model combined with a tool to facilitate the collection of the necessary parameters. All relevant actions taken in a CP are included in a Bayesian network model, which allows prior distributions for most parameters. In addition, frequency of occurrence and risk estimates for factors that influence either the probability of introduction or temporary misclassification leading to delayed detection of the infection are included in the model. Bovine viral diarrhea virus (BVDV) is used as an example disease. Many countries have CPs in place for BVDV and although elements of the CPs are similar, biosecurity measures and testing protocols, including types of tests and testing frequency, as well as target groups, differ widely. Although the initially developed framework is based on BVDV, the aim is to make it sufficiently generic to be adaptable to CPs for other diseases and possibly other species. Thus, STOC free will result in a single general framework, adaptable to multiple disease CPs, which aims to enhance the safety of trade.

Syndromic surveillance by veterinary practitioners: a pilot study in the pig sector

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.

A framework for estimating society's economic welfare following the introduction of an animal disease: The case of Johne's disease

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.

Social and economic aspects of aquatic animal health

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.

Insights for the assessment of the economic impact of endemic diseases: specific adaptation of economic frameworks using the case of bovine viral diarrhoea

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.

Voluntary monitoring systems for pig health and welfare in the UK: Comparative analysis of prevalence and temporal patterns of selected non-respiratory post mortem conditions

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.

Analysis of bovine viral diarrhoea virus: Biobank and sequence database to support eradication in Scotland

Samples from bovine viral diarrhoea virus (BVDV)-positive cattle were gathered by Scottish diagnostic laboratories and used to produce a Biobank of samples with associated location and identification data in support of the Scottish BVDV eradication scheme. The samples were subject to direct amplification and sequencing of the 5'-untranslated region (5'-UTR) to define the viral types and subtypes present. From 2693 samples collected prior to 2016, approximately 2300 sequences were obtained, representing 8 BVDV type 1 subtypes. No BVDV type 2 samples were detected. The samples came from all regions of the UK but 66 per cent were from Scotland. Analysis of the sequences showed great diversity in the 5'-UTR, with 1206 different sequences. Many samples carried virus with identical 5'-UTR sequences; often from single locations, but there were also examples of the same sequence being obtained from samples at several different locations. This work provides a resource that can be used to analyse the movement of BVDV strains both within Scotland and between Scotland and other nations, particularly in the latter stages of the Scottish eradication programme, and so inform the advice available to both livestock keepers and policymakers.

Vulnerability of the British swine industry to classical swine fever

Classical swine fever (CSF) is a notifiable, highly contagious viral disease of swine which results in severe welfare and economic consequences in affected countries. To improve preparedness, it is critical to have some understanding of how CSF would spread should it be introduced. Based on the data recorded during the 2000 epidemic of CSF in Great Britain (GB), a spatially explicit, premises-based model was developed to explore the risk of CSF spread in GB. We found that large outbreaks of CSF would be rare and generated from a limited number of areas in GB. Despite the consistently low vulnerability of the British swine industry to large CSF outbreaks, we identified concerns with respect to the role played by the non-commercial sector of the industry. The model further revealed how various epidemiological features may influence the spread of CSF in GB, highlighting the importance of between-farm biosecurity in preventing widespread dissemination of the virus. Knowledge of factors affecting the risk of spread are key components for surveillance planning and resource allocation, and this work provides a valuable stepping stone in guiding policy on CSF surveillance and control in GB.

Pig Abattoir Inspection Data: Can It Be Used for Surveillance Purposes?

Statutory recording of carcass lesions at the abattoir may have significant potential as a resource for surveillance of livestock populations. Food Standards Agency (FSA) data in Great Britain are not currently used for surveillance purposes. There are concerns that the sensitivity of detection, combined with other issues, may make the outputs unreliable. In this study we postulate that FSA data could be used for surveillance purposes. To test this we compared FSA data with BPHS (a targeted surveillance system of slaughtered pigs) and laboratory diagnostic scanning surveillance (FarmFile) data, from mid-2008 to mid-2012, for respiratory conditions and tail bite lesions in pigs at population level. We also evaluated the agreement/correlation at batch level between FSA and BPHS inspections in four field trials during 2013. Temporal trends and regional differences at population level were described and compared using logistic regression models. Population temporal analysis showed an increase in respiratory disease in all datasets but with regional differences. For tail bite, the temporal trend and monthly patterns were completely different between the datasets. The field trials were run in three abattoirs and included 322 batches. Pearson’s correlation and Cohen’s kappa tests were used to assess correlation/agreement between inspections systems. It was moderate to strong for high prevalence conditions but slight for low prevalence conditions. We conclude that there is potential to use FSA data as a component of a surveillance system to monitor temporal trends and regional differences of chosen indicators at population level. At producer level and for low prevalence conditions it needs further improvement. Overall a number of issues still need to be addressed in order to provide the pig industry with the confidence to base their decisions on these FSA inspection data. Similar conclusions, at national level, may apply to other livestock sectors but require further evaluation of the inspection and data collection processes.

Difficulties arising from the variety of testing schemes used for bovine viral diarrhoea virus (BVDV)

Globally, the eradication of bovine viral diarrhoea virus (BVDV) is still in its infancy, but eradication has been, or is being, adopted by several countries or regions. Comparisons between countries' schemes allow others to assess best practice, and aggregating published results from eradication schemes provides greater statistical power when analysing data. Aggregating data requires that results derived from different testing schemes be calibrated against one another. The authors aimed to evaluate whether relationships between published BVDV test results could be created and present the outcome of a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The results are tabulated, providing a summary of papers where there is potential cross-calibration and a summary of the obstacles preventing such data aggregation. Although differences in measuring BVDV present barriers to academic progress, they may also affect progress within individual eradication schemes. The authors examined the time taken to retest following an initial antibody BVDV test in the Scottish eradication scheme. The authors demonstrate that retesting occurred quicker if the initial not negative test was from blood rather than milk samples. Such differences in the response of farmers/veterinarians to tests may be of interest to the design of future schemes.

Using national movement databases to help inform responses to swine disease outbreaks in Scotland: the impact of uncertainty around incursion time

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.

Applying phylogenomics to understand the emergence of Shiga-toxin-producing Escherichia coli O157:H7 strains causing severe human disease in the UK

Shiga-toxin-producing Escherichia coli (STEC) O157:H7 is a recently emerged zoonotic pathogen with considerable morbidity. Since the emergence of this serotype in the 1980s, research has focussed on unravelling the evolutionary events from the E. coli O55:H7 ancestor to the contemporaneous globally dispersed strains observed today. In this study, the genomes of over 1000 isolates from both human clinical cases and cattle, spanning the history of STEC O157:H7 in the UK, were sequenced. Phylogenetic analysis revealed the ancestry, key acquisition events and global context of the strains. Dated phylogenies estimated the time to evolution of the most recent common ancestor of the current circulating global clone to be 175 years ago. This event was followed by rapid diversification. We show the acquisition of specific virulence determinates has occurred relatively recently and coincides with its recent detection in the human population. We used clinical outcome data from 493 cases of STEC O157:H7 to assess the relative risk of severe disease including haemolytic uraemic syndrome from each of the defined clades in the population and show the dramatic effect Shiga toxin repertoire has on virulence. We describe two strain replacement events that have occurred in the cattle population in the UK over the last 30 years, one resulting in a highly virulent strain that has accounted for the majority of clinical cases in the UK over the last decade. There is a need to understand the selection pressures maintaining Shiga-toxin-encoding bacteriophages in the ruminant reservoir and the study affirms the requirement for close surveillance of this pathogen in both ruminant and human populations.

Not all cows are epidemiologically equal: quantifying the risks of bovine viral diarrhoea virus (BVDV) transmission through cattle movements

Many economically important cattle diseases spread between herds through livestock movements. Traditionally, most transmission models have assumed that all purchased cattle carry the same risk of generating outbreaks in the destination herd. Using data on bovine viral diarrhoea virus (BVDV) in Scotland as a case example, this study provides empirical and theoretical evidence that the risk of disease transmission varies substantially based on the animal and herd demographic characteristics at the time of purchase. Multivariable logistic regression analysis revealed that purchasing pregnant heifers and open cows sold with a calf at foot were associated with an increased risk of beef herds being seropositive for BVDV. Based on the results from a dynamic within-herd simulation model, these findings may be partly explained by the age-related probability of animals being persistently infected with BVDV as well as the herd demographic structure at the time of animal introductions. There was also evidence that an epidemiologically important network statistic, "betweenness centrality" (a measure frequently associated with the potential for herds to acquire and transmit disease), was significantly higher for herds that supplied these particular types of replacement beef cattle. The trends for dairy herds were not as clear, although there was some evidence that open heifers and open lactating cows were associated with an increased risk of BVDV. Overall, these findings have important implications for developing simulation models that more accurately reflect the industry-level transmission dynamics of infectious cattle diseases.

Replicating disease spread in empirical cattle networks by adjusting the probability of infection in random networks

Comparisons between mass-action or "random" network models and empirical networks have produced mixed results. Here we seek to discover whether a simulated disease spread through randomly constructed networks can be coerced to model the spread in empirical networks by altering a single disease parameter - the probability of infection. A stochastic model for disease spread through herds of cattle is utilised to model the passage of an SEIR (susceptible-latent-infected-resistant) through five networks. The first network is an empirical network of recorded contacts, from four datasets available, and the other four networks are constructed from randomly distributed contacts based on increasing amounts of information from the recorded network. A numerical study on adjusting the value of the probability of infection was conducted for the four random network models. We found that relative percentage reductions in the probability of infection, between 5.6% and 39.4% in the random network models, produced results that most closely mirrored the results from the empirical contact networks. In all cases tested, to reduce the differences between the two models, required a reduction in the probability of infection in the random network.

How commercial and non-commercial swine producers move pigs in Scotland: a detailed descriptive analysis

Background

The impact of non-commercial producers on disease spread via livestock movement is related to their level of interaction with other commercial actors within the industry. Although understanding these relationships is crucial in order to identify likely routes of disease incursion and transmission prior to disease detection, there has been little research in this area due to the difficulties of capturing movements of small producers with sufficient resolution. Here, we used the Scottish Livestock Electronic Identification and Traceability (ScotEID) database to describe the movement patterns of different pig production systems which may affect the risk of disease spread within the swine industry. In particular, we focused on the role of small pig producers.

Results

Between January 2012 and May 2013, 23,169 batches of pigs were recorded moving animals between 2382 known unique premises. Although the majority of movements (61%) were to a slaughterhouse, the non-commercial and the commercial sectors of the Scottish swine industry coexist, with on- and off-movement of animals occurring relatively frequently. For instance, 13% and 4% of non-slaughter movements from professional producers were sent to a non-assured commercial producer or to a small producer, respectively; whereas 43% and 22% of movements from non-assured commercial farms were sent to a professional or a small producer, respectively. We further identified differences between producer types in several animal movement characteristics which are known to increase the risk of disease spread. Particularly, the distance travelled and the use of haulage were found to be significantly different between producers.

Conclusions

These results showed that commercial producers are not isolated from the non-commercial sector of the Scottish swine industry and may frequently interact, either directly or indirectly. The observed patterns in the frequency of movements, the type of producers involved, the distance travelled and the use of haulage companies provide insights into the structure of the Scottish swine industry, but also highlight different features that may increase the risk of infectious diseases spread in both Scotland and the UK. Such knowledge is critical for developing more robust biosecurity and surveillance plans and better preparing Scotland against incursions of emerging swine diseases.

E. coli O157 on Scottish cattle farms: evidence of local spread and persistence using repeat cross-sectional data

Background

Escherichia coli (E. coli) O157 is a virulent zoonotic strain of enterohaemorrhagic E. coli. In Scotland (1998-2008) the annual reported rate of human infection is 4.4 per 100,000 population which is consistently higher than other regions of the UK and abroad. Cattle are the primary reservoir. Thus understanding infection dynamics in cattle is paramount to reducing human infections.

A large database was created for farms sampled in two cross-sectional surveys carried out in Scotland (1998 - 2004). A statistical model was generated to identify risk factors for the presence of E. coli O157 on farms. Specific hypotheses were tested regarding the presence of E. coli O157 on local farms and the farms previous status. Pulsed-field gel electrophoresis (PFGE) profiles were further examined to ascertain whether local spread or persistence of strains could be inferred.

Results

The presence of an E. coli O157 positive local farm (average distance: 5.96km) in the Highlands, North East and South West, farm size and the number of cattle moved onto the farm 8 weeks prior to sampling were significant risk factors for the presence of E. coli O157 on farms. Previous status of a farm was not a significant predictor of current status (p = 0.398). Farms within the same sampling cluster were significantly more likely to be the same PFGE type (p < 0.001), implicating spread of strains between local farms. Isolates with identical PFGE types were observed to persist across the two surveys, including 3 that were identified on the same farm, suggesting an environmental reservoir. PFGE types that were persistent were more likely to have been observed in human clinical infections in Scotland (p < 0.001) from the same time frame.

Conclusions

The results of this study demonstrate the spread of E. coli O157 between local farms and highlight the potential link between persistent cattle strains and human clinical infections in Scotland. This novel insight into the epidemiology of Scottish E. coli O157 paves the way for future research into the mechanisms of transmission which should help with the design of control measures to reduce E. coli O157 from livestock-related sources.

Systems approaches to animal disease surveillance and resource allocation: methodological frameworks for behavioral analysis

While demands for animal disease surveillance systems are growing, there has been little applied research that has examined the interactions between resource allocation, cost-effectiveness, and behavioral considerations of actors throughout the livestock supply chain in a surveillance system context. These interactions are important as feedbacks between surveillance decisions and disease evolution may be modulated by their contextual drivers, influencing the cost-effectiveness of a given surveillance system. This paper identifies a number of key behavioral aspects involved in animal health surveillance systems and reviews some novel methodologies for their analysis. A generic framework for analysis is discussed, with exemplar results provided to demonstrate the utility of such an approach in guiding better disease control and surveillance decisions.

Vaccination against foot-and-mouth disease: do initial conditions affect its benefit?

When facing incursion of a major livestock infectious disease, the decision to implement a vaccination programme is made at the national level. To make this decision, governments must consider whether the benefits of vaccination are sufficient to outweigh potential additional costs, including further trade restrictions that may be imposed due to the implementation of vaccination. However, little consensus exists on the factors triggering its implementation on the field. This work explores the effect of several triggers in the implementation of a reactive vaccination-to-live policy when facing epidemics of foot-and-mouth disease. In particular, we tested whether changes in the location of the incursion and the delay of implementation would affect the epidemiological benefit of such a policy in the context of Scotland. To reach this goal, we used a spatial, premises-based model that has been extensively used to investigate the effectiveness of mitigation procedures in Great Britain. The results show that the decision to vaccinate, or not, is not straightforward and strongly depends on the underlying local structure of the population-at-risk. With regards to disease incursion preparedness, simply identifying areas of highest population density may not capture all complexities that may influence the spread of disease as well as the benefit of implementing vaccination. However, if a decision to vaccinate is made, we show that delaying its implementation in the field may markedly reduce its benefit. This work provides guidelines to support policy makers in their decision to implement, or not, a vaccination-to-live policy when facing epidemics of infectious livestock disease.

Relative associations of cattle movements, local spread, and biosecurity with bovine viral diarrhoea virus (BVDV) seropositivity in beef and dairy herds

The success of bovine viral diarrhoea virus (BVDV) eradication campaigns can be undermined by spread through local transmission pathways and poor farmer compliance with biosecurity recommendations. This work combines recent survey data with cattle movement data to explore the issues likely to impact on the success of BVDV control in Scotland. In this analysis, data from 249 beef suckler herds and 185 dairy herds in Scotland were studied retrospectively to determine the relative influence of cattle movements, local spread, and biosecurity on BVDV seropositivity. Multivariable logistic regression models revealed that cattle movement risk factors had approximately 3 times greater explanatory power than risk factors for local spread amongst beef suckler herds, but approximately the same explanatory power as risk factors for local spread amongst dairy herds. These findings are most likely related to differences in cattle husbandry practices and suggest that where financial prioritization is required, focusing on reducing movement-based risk is likely to be of greatest benefit when applied to beef suckler herds. The reported use of biosecurity measures such as purchasing cattle from BVDV accredited herds only, performing diagnostic screening at the time of sale, implementing isolation periods for purchased cattle, and installing double fencing on shared field boundaries had minimal impact on the risk of beef or dairy herds being seropositive for BVDV. Only 28% of beef farmers and 24% of dairy farmers with seropositive herds recognized that their cattle were affected by BVDV and those that did perceive a problem were no less likely to sell animals as replacement breeding stock and no more likely to implement biosecurity measures against local spread than farmers with no perceived problems. In relation to the current legislative framework for BVDV control in Scotland, these findings emphasize the importance of requiring infected herds take appropriate biosecurity measures to prevent further disease transmission and conducting adequate follow-up to ensure that biosecurity measures are being implemented correctly in the field.

Determinants of biosecurity behaviour of British cattle and sheep farmers-a behavioural economics analysis

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.

Prevalence of antibodies to bovine viral diarrhoea virus in bulk tank milk and associated risk factors in Scottish dairy herds

Bulk tank milk samples were collected from 374 dairy farms in Scotland in 2007/2008 along with questionnaire data relating to the management of the farm. Milk samples were tested for antibodies to bovine viral diarrhoea virus (BVDV) using a commercially available (Svanova) kit and percentage positivity scores calculated according to the manufacturer's guidelines. There were 220 farms that did not routinely vaccinate for bovine viral diarrhoea (BVD), and these were distributed according to the Swedish BVD eradication classes as 12.7 per cent, 22.3 per cent, 44.5 per cent and 20.5 per cent for Classes 0, 1, 2 and 3, respectively. A more sophisticated statistical method (finite mixture modelling) which does not depend on arbitrary thresholds and categories suggested a 73 per cent prevalence of herds with high mean levels of antibodies. Risk factor analysis suggested that routine vaccination for BVD, suspicion of BVD, housing of pregnant cows with calves, total number of cows and the proportion of cows that were dry were all associated with increased BVDV antibodies in bulk milk. The inclusion of BVD within the farm's health plan was associated with decreased BVDV antibodies in the bulk milk.

Identifying associations between pig pathologies using a multi-dimensional machine learning methodology

Background

Abattoir detected pathologies are of crucial importance to both pig production and food safety. Usually, more than one pathology coexist in a pig herd although it often remains unknown how these different pathologies interrelate to each other. Identification of the associations between different pathologies may facilitate an improved understanding of their underlying biological linkage, and support the veterinarians in encouraging control strategies aimed at reducing the prevalence of not just one, but two or more conditions simultaneously.

Results

Multi-dimensional machine learning methodology was used to identify associations between ten typical pathologies in 6485 batches of slaughtered finishing pigs, assisting the comprehension of their biological association. Pathologies potentially associated with septicaemia (e.g. pericarditis, peritonitis) appear interrelated, suggesting on-going bacterial challenges by pathogens such as Haemophilus parasuis and Streptococcus suis. Furthermore, hepatic scarring appears interrelated with both milk spot livers (Ascaris suum) and bacteria-related pathologies, suggesting a potential multi-pathogen nature for this pathology.

Conclusions

The application of novel multi-dimensional machine learning methodology provided new insights into how typical pig pathologies are potentially interrelated at batch level. The methodology presented is a powerful exploratory tool to generate hypotheses, applicable to a wide range of studies in veterinary research.

Predicted costs and benefits of eradicating BVDV from Ireland

Bovine viral diarrhoea virus (BVDV) causes an economically important endemic disease (BVD) of cattle in Ireland and worldwide. Systematic eradication by detection and removal of infectious (BVDV carrier) cattle has been successful in several regions. We therefore assessed the benefits (disease losses avoided) and costs (testing and culling regime) of a potential eradication programme in Ireland. Published bio-economic models of BVDV spread in beef suckler herds and dairy herds were adapted to estimate potential benefits of eradication in Ireland. A simple model of BVDV spread in beef finisher herds was devised to estimate the benefits of eradication in this sector. A six year eradication programme consisting of 5 inter-related virological and serological testing programmes is outlined and costed. We found that the annualised benefits of BVDV eradication in Ireland exceeded the costs by a factor of 5 in the beef suckler sector and a factor of 14 in the dairy sector. Corresponding payback periods were 1.2 and 0.5 years respectively. These results highlight the significant economic impact of BVDV on the Irish cattle industry and suggest a clear economic benefit to eradication using the proposed approach. This type of cost-benefit analysis is considered an essential prerequisite prior to undertaking an eradication campaign of this magnitude.

Impacts of climate, host and landscape factors on Culicoides species in Scotland

Culicoides biting midges (Diptera: Ceratopogonidae) vector a wide variety of internationally important arboviral pathogens of livestock and represent a widespread biting nuisance. This study investigated the influence of landscape, host and remotely-sensed climate factors on local abundance of livestock-associated species in Scotland, within a hierarchical generalized linear model framework. The Culicoides obsoletus group and the Culicoides pulicaris group accounted for 56% and 41%, respectively, of adult females trapped. Culicoides impunctatus Goetghebuer and C. pulicaris s.s. Linnaeus were the most abundant and widespread species in the C. pulicaris group (accounting for 29% and 10%, respectively, of females trapped). Abundance models performed well for C. impunctatus, Culicoides deltus Edwards and Culicoides punctatus Meigen (adjusted R(2) : 0.59-0.70), but not for C. pulicaris s.s. (adjusted R(2) : 0.36) and the C. obsoletus group (adjusted R(2) : 0.08). Local-scale abundance patterns were best explained by models combining host, landscape and climate factors. The abundance of C. impunctatus was negatively associated with cattle density, but positively associated with pasture cover, consistent with this species' preference in the larval stage for lightly grazed, wet rush pasture. Predicted abundances of this species varied widely among farms even over short distances (less than a few km). Modelling approaches that may facilitate the more accurate prediction of local abundance patterns for a wider range of Culicoides species are discussed.

The influence of empirical contact networks on modelling diseases in cattle

We present two stochastic models of the passage of an SEIR (susceptible-latent-infected-resistant) disease through herds of cattle. One model is based on a contact network constructed via continuously recorded interaction data from two herds of cattle, the other, a matching network constructed using the principles of mass-action mixing. The recorded contact data were produced by attaching proximity data loggers to two separate herds of cattle during two separate recording periods. The network constructed using the principles of mass-action mixing uses the same number of contacts as the recorded network but distributes them randomly amongst the animals. The recorded networks had a greater number of repeated contacts, lower closeness and clustering scores and greater average path length than the mass-action networks. A lower proportion of simulations of the recorded network produce any disease spread when compared to those simulations of the mass-action network and, of those that did, fewer infected animals were predicted. For all parameter values tested, within the sensitivity analysis, similar differences were found between the recorded and mass-action network models.

The British pig health schemes: integrated systems for large-scale pig abattoir lesion monitoring

Pig health schemes based on abattoir inspections provide an integrated system to optimise the postmortem detection and the reporting of pathological lesions. In Great Britain, two initiatives have been implemented by the pig industry: Wholesome Pigs Scotland (WPS) and the BPEX Pig Health Scheme (BPHS). These schemes record the presence of a range of pathological lesions detected by means of detailed inspection of the pluck and the skin of the slaughtered pigs. The lesions are those associated with a reduction in performance traits or are indicators of animal welfare problems. This paper aims to provide an overview of the objectives behind the BPHS and their activities, outlining similarities and differences between WPS and BPHS on five main operational topics: the lesions monitored, the administration of the schemes, flow of the information, inspection strategies and the major idiosyncratic characteristics of the schemes. These initiatives inform individual producers and their veterinarians of the occurrence of pathological conditions affecting their pig herds. Additionally, they offer the added value of providing nationwide disease monitoring information and have the potential to be a useful surveillance tool for emerging and enzootic conditions.

National monitoring of Ascaris suum related liver pathologies in English abattoirs: a time-series analysis, 2005-2010

Ascaris suum is the most important internal parasite in farmed pigs world-wide. In England, the BPEX Pig Health Scheme (BPHS) monitors the prevalence of ascariosis in slaughtered finished pigs by identifying milk spots - the healing lesions caused by A. suum larvae migration through the liver. This study investigates the trend of milk spot lesions from July 2005 to December 2010 to identify the progress made by the industry in controlling this parasitic disease. For visual explorations, the monthly prevalence for milk spots was modelled using "STL", a seasonal-trend decomposition method based on locally weighted regression. Random effects binomial modelling accounting for clustering at batch level was used to test the significance of the trend and seasonality. Additionally, the differences in the milk spot prevalence trends for BPHS members (those that joined the scheme) and non-members were investigated and tested. A mean of 12,442 pigs was assessed per month (in 290 batches) across 12 pig abattoirs over the study period, from which a monthly mean of 7102 pigs (159 batches) came from BPHS members. A mild overall decrease in prevalence of milk spots over the monitored period was identified as well as a seasonal variation which showed peaks in summer and at the beginning of autumn. BPHS members maintained a lower prevalence than non-members. The results from this work illustrate ascariosis as a persistent problem in current farm production.

Structure discovery in Bayesian networks: an analytical tool for analysing complex animal health data

Analysing animal health data can be a complex task as the health status of individuals or groups of animals, might depend on many inter-related variables. The objective is to differentiate variables that are directly associated with health status and therefore promising targets for intervention, from variables that are indirectly associated with health status and can therefore at best only affect this indirectly through association with other variables. Bayesian network (BN) modelling is a machine learning technique for empirically identifying associations in complex and high dimensional data, so-called "structure discovery". An introduction to structure discovery using BN modelling is presented, comprising the key assumptions required by the methodology, along with a discussion of advantages and limitations. To demonstrate the various steps required to apply BN structure discovery to animal health data, illustrative analyses of data collected during a previously published study concerned with exposure to bovine viral diarrhoea virus in beef cow-calf herds in Scotland are presented.

Eradication programme for bovine viral diarrhoea virus in Orkney 2001 to 2008

The strategies used and the results obtained in Orkney's bovine viral diarrhoea virus (BVDV) eradication programme over eight years (2001 to 2008) are presented and discussed. The venture was undertaken by local veterinary practices and the Orkney Livestock Association (OLA) with the financial support of the Orkney Islands Council. Participation is voluntary; the programme comprises screening of youngstock, a whole-herd test if required, elimination of persistently infected animals and strict biosecurity measures and/or vaccination. BVDV-free herds are certified, and certification is updated annually by retesting the youngstock. The programme aims to minimise economic losses, thereby increasing the competitiveness of the Orcadian cattle industry and to improve animal health and welfare by eliminating virus circulation. Information from databases of the Scottish Agricultural College, Biobest Laboratories and OLA show that despite a significant reduction in the overall prevalence of BVDV on Orkney during the initial stages of the eradication programme, there has been little progress made since 2006 and that some difficulties have been encountered, with herd BVDV breakdowns following initial eradication. These results highlight the need for continued motivation of farmers, strict application of biosecurity measures and/or systematic vaccination of all seronegative breeding animals.

Prevalence of Pasteurella multocida and other respiratory pathogens in the nasal tract of Scottish calves

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.

Identification of factors influencing the occurrence of milk spot livers in slaughtered pigs: A novel approach to understanding Ascaris suum epidemiology in British farmed pigs

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.

Assessing the consequences of an incursion of a vector-borne disease. II. Spread of bluetongue in Scotland and impact of vaccination

Bluetongue is a viral disease of ruminants transmitted by Culicoides biting midges, which has spread across Europe over the past decade. The disease arrived in south-east England in 2007, raising the possibility that it could pose a risk to the valuable Scottish livestock industry. As part of an assessment of the economic consequences of a bluetongue virus incursion into Scotland commissioned by Scottish Government, we investigated a defined set of feasible incursion scenarios under different vaccination strategies. Our epidemiological simulations, based on expert knowledge, highlighted that infection will rarely spread in Scotland after the initial incursion and will be efficiently controlled by vaccination.