A mechanistic model captures livestock trading, disease dynamics, and compensatory behaviour in response to control measures.

Trade is a complex, multi-faceted process that can contribute to the spread and persistence of disease. We here develop novel mechanistic models of supply. Our model is framed within a livestock trading system, where farms form and end trade partnerships with rates dependent on current demand, with these trade partnerships facilitating trade between partners. With these time-varying, stock dependent partnership and trade dynamics, our trading model goes beyond current state of the art modelling approaches. By studying instantaneous shocks to farm-level supply and demand we show that behavioural responses of farms lead to trading systems that are highly resistant to shocks with only temporary disturbances to trade observed. Individual adaptation in response to permanent alterations to trading propensities, such that animal flows are maintained, illustrates the ability for farms to find new avenues of trade, minimising disruptions imposed by such alterations to trade that common modelling approaches cannot adequately capture. In the context of endemic disease control, we show that these adaptations hinder the potential beneficial reductions in prevalence such changes to trading propensities have previously been shown to confer. Assessing the impact of a common disease control measure, post-movement batch testing, highlights the ability for our model to measure the stress on multiple components of trade imposed by such control measures and also highlights the temporary and, in some cases, the permanent disturbances to trade that post-movement testing has on the trading system.

Changes in the Ileal, but Not Fecal, Microbiome in Response to Increased Dietary Protein Level and Enterotoxigenic Escherichia coli Exposure in Pigs.

The relationship between porcine gut microbiota composition and health is an important area of research, especially due to the need to find alternatives to antimicrobial use to manage disease in livestock production systems. Previous work has indicated that lower crude dietary protein levels can reduce the impacts of postweaning colibacillosis, which is a porcine diarrheal disease caused by enterotoxigenic Escherichia coli (ETEC). Here, to explore the complex interactions between the gut microbiota, protein nutrition, and ETEC exposure, the microbial compositions of both ileal digesta and feces were analyzed with or without ETEC exposure from pigs fed a low- or high-protein diet. Since ETEC colonization is mostly localized to the ileum, changes in the small intestinal microbiota were expected in response to ETEC exposure. This was supported by the study findings, which identified significant microbiota changes in ileal samples but not in fecal samples. Both increased dietary protein and ETEC exposure impacted on ileal microbiota alpha diversity (richness and diversity indices) and beta diversity (structure, stability, and relative taxon abundances) at certain sampling points, although the combination of a high-protein diet and ETEC exposure had the most profound impact on ileal microbiota composition. An understanding of how infection and nutrition lead to microbiota changes is likely to be required if dietary strategies are to be developed for the management of enteric diseases.IMPORTANCE Gut bacterial communities have been shown to play a key role in pig health and development and are strongly influenced by host diet, but studies highlighting the complex interactions between nutrition, gut infections and the microbiome tend to focus on bacterial populations in the feces and not other important gut locations. We found that alteration of dietary protein level and exposure to a pathogenic microorganism, enterotoxigenic Escherichia coli (ETEC), changed bacterial populations in the distal small intestine (i.e., the ileum). We found that the most profound changes occurred in pigs fed a high-protein diet in combination with exposure to ETEC, showing a clear interaction between dietary composition and exposure to a key pathogen. These changes were not observed in the fecal samples, revealing the importance of studying biologically pertinent sites in the gut, and so the data will help to inform the development of alternative management strategies for enteric disorders.

Survival of Mycobacterium avium subspecies paratuberculosis in retail pasteurised milk.

A survey of retail purchased semi-skimmed pasteurised milk (n = 368) for Mycobacterium avium subspecies paratuberculosis (MAP) was conducted between May 2014 and June 2015 across the midlands of England using the Phage-PCR assay. Overall, 10.3% of the total samples collected contained viable MAP cells, confirming that pasteurisation is not capable of fully eliminating human exposure to viable MAP through milk. Comparison of the results gained using the Phage-PCR assay with the results of surveys using either culture or direct PCR suggest that the phage-PCR assay is able to detect lower numbers of cells, resulting in an increase in the number of MAP-positive samples detected. Comparison of viable count and levels of MAP detected in bulk milk samples suggest that MAP is not primarily introduced into the milk by faecal contamination but rather are shed directly into the milk within the udder. In addition results detected an asymmetric distribution of MAP exists in the milk matrix prior to somatic cell lysis, indicating that the bacterial cells in naturally contaminated milk are clustered together and may primarily be located within somatic cells. These latter two results lead to the hypothesis that intracellular MAP within the somatic cells may be protected against heat inactivation during pasteurisation, accounting for the presence of low levels of MAP detected in retail milk.

Using Combined Diagnostic Test Results to Hindcast Trends of Infection from Cross-Sectional Data.

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to 'hindcast' (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time.

Strain-dependent cellular immune responses in cattle following Escherichia coli O157:H7 colonization.

Enterohemorrhagic Escherichia coli (EHEC) O157:H7 causes hemorrhagic diarrhea and potentially fatal renal failure in humans. Ruminants are considered to be the primary reservoir for human infection. Vaccines that reduce shedding in cattle are only partially protective, and their underlying protective mechanisms are unknown. Studies investigating the response of cattle to colonization generally focus on humoral immunity, leaving the role of cellular immunity unclear. To inform future vaccine development, we studied the cellular immune responses of cattle during EHEC O157:H7 colonization. Calves were challenged either with a phage type 21/28 (PT21/28) strain possessing the Shiga toxin 2a (Stx2a) and Stx2c genes or with a PT32 strain possessing the Stx2c gene only. T-helper cell-associated transcripts at the terminal rectum were analyzed by reverse transcription-quantitative PCR (RT-qPCR). Induction of gamma interferon (IFN-γ) and T-bet was observed with peak expression of both genes at 7 days in PT32-challenged calves, while upregulation was delayed, peaking at 21 days, in PT21/28-challenged calves. Cells isolated from gastrointestinal lymph nodes demonstrated antigen-specific proliferation and IFN-γ release in response to type III secreted proteins (T3SPs); however, responsiveness was suppressed in cells isolated from PT32-challenged calves. Lymph node cells showed increased expression of the proliferation marker Ki67 in CD4(+) T cells from PT21/28-challenged calves, NK cells from PT32-challenged calves, and CD8(+) and γδ T cells from both PT21/28- and PT32-challenged calves following ex vivo restimulation with T3SPs. This study demonstrates that cattle mount cellular immune responses during colonization with EHEC O157:H7, the temporality of which is strain dependent, with further evidence of strain-specific immunomodulation.

Social isolation of unfamiliar cattle by groups of familiar cattle.

Domestic herbivores show a strong motivation to form associations with conspecifics and the social dynamics of any group is dependant on the individuals within the group. Thus, common farm management practices such mixing may cause social disruption. Social integration of new group members has previously been defined as a lack of aggressive interactions within the group. However, a lack of aggression among group members may not represent full integration into the social group. Here we observe the impact of disrupting groups of cattle via the introduction of an unfamiliar individual, on the social network patterns of six groups of cattle. Cattle contacts between all individuals in a group were recorded before and after the introduction of the unfamiliar individual. Pre-introduction, resident cattle showed preferential associations with specific individuals in the group. Post-introduction, resident cattle reduced the strength of their contacts (e.g., frequency) with each other relative to the pre-introduction phase. Unfamiliar individuals were socially isolated from the group throughout the trial. The observed social contact patterns suggest that new group members are socially isolated from established groups longer than previously thought, and common farm mixing practices may have negative welfare consequences on introduced individuals.

Impact of external sources of infection on the dynamics of bovine tuberculosis in modelled badger populations.

BACKGROUND: The persistence of bovine TB (bTB) in various countries throughout the world is enhanced by the existence of wildlife hosts for the infection. In Britain and Ireland, the principal wildlife host for bTB is the badger (Meles meles). The objective of our study was to examine the dynamics of bTB in badgers in relation to both badger-derived infection from within the population and externally-derived, trickle-type, infection, such as could occur from other species or environmental sources, using a spatial stochastic simulation model. RESULTS: The presence of external sources of infection can increase mean prevalence and reduce the threshold group size for disease persistence. Above the threshold equilibrium group size of 6-8 individuals predicted by the model for bTB persistence in badgers based on internal infection alone, external sources of infection have relatively little impact on the persistence or level of disease. However, within a critical range of group sizes just below this threshold level, external infection becomes much more important in determining disease dynamics. Within this critical range, external infection increases the ratio of intra- to inter-group infections due to the greater probability of external infections entering fully-susceptible groups. The effect is to enable bTB persistence and increase bTB prevalence in badger populations which would not be able to maintain bTB based on internal infection alone. CONCLUSIONS: External sources of bTB infection can contribute to the persistence of bTB in badger populations. In high-density badger populations, internal badger-derived infections occur at a sufficient rate that the additional effect of external sources in exacerbating disease is minimal. However, in lower-density populations, external sources of infection are much more important in enhancing bTB prevalence and persistence. In such circumstances, it is particularly important that control strategies to reduce bTB in badgers include efforts to minimise such external sources of infection.

Accounting for uncertainty in model-based prevalence estimation: paratuberculosis control in dairy herds.

BACKGROUND: A common approach to the application of epidemiological models is to determine a single (point estimate) parameterisation using the information available in the literature. However, in many cases there is considerable uncertainty about parameter values, reflecting both the incomplete nature of current knowledge and natural variation, for example between farms. Furthermore model outcomes may be highly sensitive to different parameter values. Paratuberculosis is an infection for which many of the key parameter values are poorly understood and highly variable, and for such infections there is a need to develop and apply statistical techniques which make maximal use of available data. RESULTS: A technique based on Latin hypercube sampling combined with a novel reweighting method was developed which enables parameter uncertainty and variability to be incorporated into a model-based framework for estimation of prevalence. The method was evaluated by applying it to a simulation of paratuberculosis in dairy herds which combines a continuous time stochastic algorithm with model features such as within herd variability in disease development and shedding, which have not been previously explored in paratuberculosis models. Generated sample parameter combinations were assigned a weight, determined by quantifying the model's resultant ability to reproduce prevalence data. Once these weights are generated the model can be used to evaluate other scenarios such as control options. To illustrate the utility of this approach these reweighted model outputs were used to compare standard test and cull control strategies both individually and in combination with simple husbandry practices that aim to reduce infection rates. CONCLUSIONS: The technique developed has been shown to be applicable to a complex model incorporating realistic control options. For models where parameters are not well known or subject to significant variability, the reweighting scheme allowed estimated distributions of parameter values to be combined with additional sources of information, such as that available from prevalence distributions, resulting in outputs which implicitly handle variation and uncertainty. This methodology allows for more robust predictions from modelling approaches by allowing for parameter uncertainty and combining different sources of information, and is thus expected to be useful in application to a large number of disease systems.

Comparative analysis of the anthelmintic efficacy of European heather extracts on Teladorsagia circumcincta and Trichostrongylus colubriformis egg hatching and larval motility.

BACKGROUND: Gastrointestinal nematode (GIN) control is traditionally achieved with the use of anthelmintic drugs, however due to regulations in organic farming and the rise in anthelmintic resistance, alternatives are sought after. A promising alternative is the use of bioactive plant feeding due to the presence of plant secondary metabolites (PSMs) such as proanthocyanidins (PAs). This study focussed on the perennial shrub heather (Ericaceae family), a plant rich in PAs, highly abundant across Europe and with previously demonstrated anthelmintic potential. METHODS: In vitro assays were used to investigate heather's anthelmintic efficacy against egg hatching and larval motility. Heather samples were collected from five European countries across two seasons, and extracts were tested against two GIN species: Teladorsagia circumcincta and Trichostrongylus colubriformis. Polyphenol group-specific ultraperformance liquid chromatography-tandem mass spectrometry analysis was performed to identify relevant polyphenol subgroups present, including the PA concentration and size and ratio of the subunits. Partial least squares analysis was performed to associate efficacy with variation in PSM composition. RESULTS: Heather extracts reduced egg hatching of both GIN species in a dose-dependent manner by up to 100%, while three extracts at the highest concentration (10 mg/ml) reduced larval motility to levels that were not significantly different from dead larvae controls. PAs, particularly the procyanidin type, and flavonol derivatives were associated with anthelmintic activity, and the particular subgroup of polyphenols associated with the efficacy was dependent on the GIN species and life stage. CONCLUSIONS: Our results provide in vitro evidence that heather, a widely available plant often managed as a weed in grazing systems, has anthelmintic properties attributed to various groups of PSMs and could contribute to sustainable GIN control in ruminant production systems across Europe.

Milk microbiome in dairy cattle and the challenges of low microbial biomass and exogenous contamination.

BACKGROUND: The blanket usage of antimicrobials at the end of lactation (or "drying off") in dairy cattle is under increasing scrutiny due to concerns about antimicrobial resistance. To lower antimicrobial usage in dairy farming, farmers are now encouraged to use "selective dry cow therapy" whereby only cows viewed as at high risk of mastitis are administered antimicrobial agents. It is important to gain a better understanding of how this practice affects the udder-associated microbiota and the potential knock-on effects on antimicrobial-resistant bacterial populations circulating on the farm. However, there are challenges associated with studying low biomass environments such as milk, due to known contamination effects on microbiome datasets. Here, we obtained milk samples from cattle at drying off and at calving to measure potential shifts in bacterial load and microbiota composition, with a critical assessment of contamination effects. RESULTS: Several samples had no detectable 16S rRNA gene copies and crucially, exogenous contamination was detected in the initial microbiome dataset. The affected samples were removed from the final microbiome analysis, which compromised the experimental design and statistical analysis. There was no significant difference in bacterial load between treatments (P > 0.05), but load was lower at calving than at drying off (P = 0.039). Escherichia coli counts by both sequence and culture data increased significantly in the presence of reduced bacterial load and a decreasing trend of microbiome richness and diversity. The milk samples revealed diverse microbiomes not reflecting a typical infection profile and were largely comprised of gut- and skin-associated taxa, with the former decreasing somewhat after prolonged sealing of the teats. CONCLUSIONS: The drying off period had a key influence on microbiota composition and bacterial load, which appeared to be independent of antimicrobial usage. The interactions between drying off treatment protocol and milk microbiome dynamics are clearly complex, and our evaluations of these interactions were restricted by low biomass samples and contamination effects. Therefore, our analysis will inform the design of future studies to establish whether different selection protocols could be implemented to further minimise antimicrobial usage.

Generative models of network dynamics provide insight into the effects of trade on endemic livestock disease.

We develop and apply analytically tractable generative models of livestock movements at national scale. These go beyond current models through mechanistic modelling of heterogeneous trade partnership network dynamics and the trade events that occur on them. Linking resulting animal movements to disease transmission between farms yields analytical expressions for the basic reproduction number R 0. We show how these novel modelling tools enable systems approaches to disease control, using R 0 to explore impacts of changes in trading practices on between-farm prevalence levels. Using the Scottish cattle trade network as a case study, we show our approach captures critical complexities of real-world trade networks at the national scale for a broad range of endemic diseases. Changes in trading patterns that minimize disruption to business by maintaining in-flow of animals for each individual farm reduce R 0, with the largest reductions for diseases that are most challenging to eradicate. Incentivizing high-risk farms to adopt such changes exploits 'scale-free' properties of the system and is likely to be particularly effective in reducing national livestock disease burden and incursion risk. Encouragingly, gains made by such targeted modification of trade practices scale much more favourably than comparably targeted improvements to more commonly adopted farm-level biosecurity.

Temporal and nutritional effects on the weaner pig ileal microbiota.

BACKGROUND: The porcine gastrointestinal microbiota has been linked to both host health and performance. Most pig gut microbiota studies target faecal material, which is not representative of microbiota dynamics in other discrete gut sections. The weaning transition period in pigs is a key development stage, with gastrointestinal problems being prominent after often sudden introduction to a solid diet. A better understanding of both temporal and nutritional effects on the small intestinal microbiota is required. Here, the development of the porcine ileal microbiota under differing levels of dietary protein was observed over the immediate post-weaning period. RESULTS: Ileal digesta samples were obtained at post-mortem prior to weaning day (day - 1) for baseline measurements. The remaining pigs were introduced to either an 18% (low) or 23% (high) protein diet on weaning day (day 0) and further ileal digesta sampling was carried out at days 5, 9 and 13 post-weaning. We identified significant changes in microbiome structure (P = 0.01), a reduction in microbiome richness (P = 0.02) and changes in the abundance of specific bacterial taxa from baseline until 13 days post-weaning. The ileal microbiota became less stable after the introduction to a solid diet at weaning (P = 0.036), was highly variable between pigs and no relationship was observed between average daily weight gain and microbiota composition. The ileal microbiota was less stable in pigs fed the high protein diet (P = 0.05), with several pathogenic bacterial genera being significantly higher in abundance in this group. Samples from the low protein and high protein groups did not cluster separately by their CAZyme (carbohydrate-active enzyme) composition, but GH33 exosialidases were found to be significantly more abundant in the HP group (P = 0.006). CONCLUSIONS: The weaner pig ileal microbiota changed rapidly and was initially destabilised by the sudden introduction to feed. Nutritional composition influenced ileal microbiota development, with the high protein diet being associated with an increased abundance of significant porcine pathogens and the upregulation of GH33 exosialidases-which can influence host-microbe interactions and pathogenicity. These findings contribute to our understanding of a lesser studied gut compartment that is not only a key site of digestion, but also a target for the development of nutritional interventions to improve gut health and host growth performance during the critical weaning transition period.

Resistance to change: AMR gene dynamics on a commercial pig farm with high antimicrobial usage.

Group antimicrobial administration is used to control disease in livestock, but we have little insight into how this impacts antimicrobial resistance (AMR) gene dynamics. Here, a longitudinal study was carried out during a single production cycle on a commercial pig unit with high historic and current antimicrobial usage. Quantitative PCR, 16S rRNA gene metabarcoding and shotgun metagenomic sequencing were used to track faecal AMR gene abundance and diversity and microbiome alpha diversity. Shotgun metagenomic sequencing identified 144 AMR genes in total, with higher AMR gene diversity present in young pigs compared to dry sows. Irrespective of in-feed antibiotic treatment or changes in microbiome diversity, mean AMR gene copy number was consistently high, with some AMR genes present at copy numbers comparable to the bacterial 16S rRNA gene. In conclusion, AMR gene prevalence and abundance were not influenced by antibiotic use, either during the production cycle or following whole-herd medication. The high levels of certain genes indicate they are widely disseminated throughout the microbial population, potentially aiding stability. Despite the high and relatively stable levels of resistance genes against the main antimicrobials used, these compounds continue to control production limiting diseases on this unit.

Control of bovine tuberculosis in British livestock: there is no 'silver bullet'.

Bovine tuberculosis (bTB; Mycobacterium bovis) is a bacterial infection of cattle that also affects certain wildlife species. Culling badgers (Meles meles), the principal wildlife host, results in perturbation of the badger population and an increased level of disease in cattle. Therefore, the priority for future management must be to minimize the risk of disease transmission by finding new ways to reduce the contact rate among the host community. At the farm level, targeting those individuals that represent an elevated risk of transmission might prove to be effective. At the landscape level, risk mapping can provide the basis for targeted surveillance of the host community. Here, we review the current evidence for bTB persistence in Britain and make recommendations for future management and research.

Considering appropriate replication in the design of animal social network studies.

Social network analysis has increasingly been considered a useful tool to interpret the complexity of animal social relationships. However, group composition can affect the contact structure of the network resulting in variation between networks. Replication in contact network studies is rarely done but enables determination of possible variation in response across networks. Here we explore the importance of between-group variability in social behaviour and the impact of replication on hypothesis testing. We use an exemplar study of social contact data collected from six replicated networks of cattle before and after the application of a social disturbance treatment. In this replicated study, subtle but consistent changes in animal contact patterns were detected after the application of a social disturbance treatment. We then quantify both within- and between-group variation in this study and explore the importance of varying the number of replicates and the number of individuals within each network, on the precision of the differences in treatment effects for the contact behaviour of the resident cattle. The analysis demonstrates that reducing the number of networks observed in the study would reduce the probability of detecting treatment differences for social behaviours even if the total number of animals was kept the same.

When to kill a cull: factors affecting the success of culling wildlife for disease control.

Culling wildlife to control disease can lead to both decreases and increases in disease levels, with apparently conflicting responses observed, even for the same wildlife-disease system. There is therefore a pressing need to understand how culling design and implementation influence culling's potential to achieve disease control. We address this gap in understanding using a spatial metapopulation model representing wildlife living in distinct groups with density-dependent dispersal and framed on the badger-bovine tuberculosis (bTB) system. We show that if population reduction is too low, or too few groups are targeted, a 'perturbation effect' is observed, whereby culling leads to increased movement and disease spread. We also demonstrate the importance of culling across appropriate time scales, with otherwise successful control strategies leading to increased disease if they are not implemented for long enough. These results potentially explain a number of observations of the dynamics of both successful and unsuccessful attempts to control TB in badgers including the Randomized Badger Culling Trial in the UK, and we highlight their policy implications. Additionally, for parametrizations reflecting a broad range of wildlife-disease systems, we characterize 'Goldilocks zones', where, for a restricted combination of culling intensity, coverage and duration, the disease can be reduced without driving hosts to extinction.

Effects of host social hierarchy on disease persistence.

The effects of social hierarchy on population dynamics and epidemiology are examined through a model which contains a number of fundamental features of hierarchical systems, but is simple enough to allow analytical insight. In order to allow for differences in birth rates, contact rates and movement rates among different sets of individuals the population is first divided into subgroups representing levels in the hierarchy. Movement, representing dominance challenges, is allowed between any two levels, giving a completely connected network. The model includes hierarchical effects by introducing a set of dominance parameters which affect birth rates in each social level and movement rates between social levels, dependent upon their rank. Although natural hierarchies vary greatly in form, the skewing of contact patterns, introduced here through non-uniform dominance parameters, has marked effects on the spread of disease. A simple homogeneous mixing differential equation model of a disease with SI dynamics in a population subject to simple birth and death process is presented and it is shown that the hierarchical model tends to this as certain parameter regions are approached. Outside of these parameter regions correlations within the system give rise to deviations from the simple theory. A Gaussian moment closure scheme is developed which extends the homogeneous model in order to take account of correlations arising from the hierarchical structure, and it is shown that the results are in reasonable agreement with simulations across a range of parameters. This approach helps to elucidate the origin of hierarchical effects and shows that it may be straightforward to relate the correlations in the model to measurable quantities which could be used to determine the importance of hierarchical corrections. Overall, hierarchical effects decrease the levels of disease present in a given population compared to a homogeneous unstructured model, but show higher levels of disease than structured models with no hierarchy. The separation between these three models is greatest when the rate of dominance challenges is low, reducing mixing, and when the disease prevalence is low. This suggests that these effects will often need to be considered in models being used to examine the impact of control strategies where the low disease prevalence behaviour of a model is critical.

Dynamic interactions among badgers: implications for sociality and disease transmission.

1. Direct interactions between individuals play an important part in the sociality of group-living animals, their mating system and disease transmission. Here, we devise a methodology to quantify relative rates of proximity interaction from radio-tracking data and highlight potential asymmetries within the contact network of a moderate-density badger population in the north-east of England. 2. We analysed radio-tracking data from four contiguous social groups, collected over a 3-year period. Dynamic interaction analysis of badger dyads was used to assess the movement of individuals in relation to the movement of others, both within and between social groups. Dyads were assessed with regard to season, sex, age and sett use pattern of the badgers involved. 3. Intragroup separation distances were significantly shorter than intergroup separation distances, and interactions between groups were rare. Within groups, individuals interacted with each other more often than expected, and interaction patterns varied significantly with season and sett use pattern. Non-mover dyads (using the main sett for day-resting on > 50% of occasions) interacted more frequently than mover dyads (using an outlier sett for day-resting on > 50% of occasions) or mover-non-mover dyads. Interactions between group members occurred most frequently in winter. 4. Of close intragroup interactions (< 50 m separation distance), 88.6% were associated with a main sett and only 4.4% with outlier setts. Non-mover dyads and non-mover-mover dyads interacted significantly more often at the main sett than mover-only dyads. These results highlight the importance of the main sett to badger sociality and support the suggestion that badger social groups are comprised of different subgroups, in our case based on differential sett use patterns. 5. Asymmetries in contact structure within a population will affect the way in which diseases are transmitted through a social network. Assessment of these networks is essential for understanding the persistence and spread of disease within populations which do not mix freely or which exhibit heterogeneities in their spatial or social behaviour.

Counterintuitive increase in observed Mycobacterium avium subspecies paratuberculosis prevalence in sympatric rabbits following the introduction of paratuberculosis control measures in cattle.

Paratuberculosis (Johne's disease) is caused by the bacterium Mycobacterium avium subspecies paratuberculosis (Map). Achieving herd-level control of mycobacterial infection is notoriously difficult, despite widespread adoption of test-and-cull-based control strategies. The presence of infection in wildlife populations could be contributing to this difficulty. Rabbits are naturally infected with the same Map strain as cattle, and can excrete high levels in their faeces. The aim of this study is to determine if implementation of paratuberculosis control in cattle leads to a decline in Map infection levels in rabbits. An island-wide, test-and-cull-based paratuberculosis control programme was initiated on a Scottish island in 2008. In this study annual tests were obtained from 15 cattle farms, from 2008 to 2011, totalling 2609 tests. Rabbits (1564) were sampled from the 15 participating farms, from 2008 to 2011, and Map was detected by faecal culture. Map seroprevalence in cattle decreased from 16 to 7.2 per cent, while Map prevalence in rabbits increased from 10.3 to 20.3 per cent. Results indicate that efforts to control paratuberculosis in cattle do not reduce Map levels in sympatric rabbits. This adds to mounting evidence that if Map becomes established in wild rabbit populations, rabbits represent a persistent and widespread source of infection, potentially impeding livestock control strategies.

Analysis of temporal fecal microbiota dynamics in weaner pigs with and without exposure to enterotoxigenic Escherichia coli1,2.

The primary aim of this work was to study potential effects of subclinical enterotoxigenic Escherichia coli (ETEC) exposure on porcine fecal microbiota composition, with a secondary aim of profiling temporal shifts in bacterial communities over the weaning transition period. 16S rRNA gene metabarcoding and quantitative PCR (qPCR) were used to profile the fecal microbiota and quantify ETEC excretion in the feces, respectively. Temporal shifts in fecal microbiota structure and stability were observed across the immediate postweaning period (P < 0.05), including significant shifts in the relative levels of specific bacterial phylotypes (P < 0.05). ETEC exposure did not change the fecal microbiota structure (P > 0.05), but significant variations in fecal community structure and stability were linked to variations in ETEC excretion level at particular time points (P < 0.05). In this study, marked temporal changes in microbiota structure and stability were evident over the short weaning transition period, with a relationship between ETEC excretion level and fecal microbiota composition being observed. This study has provided a detailed analysis of fecal microbiota dynamics in the pig, which should help to inform the development of novel management strategies for enteric disorders based on an improved understanding of microbial populations during the challenging postweaning period.