Tissue distribution of angiotensin-converting enzyme 2 (ACE2) receptor in wild animals with a focus on artiodactyls, mustelids and phocids.

Natural cases of zooanthroponotic transmission of SARS-CoV-2 to animals have been reported during the COVID-19 pandemic, including to free-ranging white-tailed deer (Odocoileus virginianus) in North America and farmed American mink (Neovison vison) on multiple continents. To understand the potential for angiotensin-converting enzyme 2 (ACE2)-mediated viral tropism we characterised the distribution of ACE2 receptors in the respiratory and intestinal tissues of a selection of wild and semi-domesticated mammals including artiodactyls (cervids, bovids, camelids, suids and hippopotamus), mustelid and phocid species using immunohistochemistry. Expression of the ACE2 receptor was detected in the bronchial or bronchiolar epithelium of several European and Asiatic deer species, Bactrian camel (Camelus bactrianus), European badger (Meles meles), stoat (Mustela erminea), hippopotamus (Hippopotamus amphibious), harbor seal (Phoca vitulina), and hooded seal (Cystophora cristata). Further receptor mapping in the nasal turbinates and trachea revealed sparse ACE2 receptor expression in the mucosal epithelial cells and occasional occurrence in the submucosal glandular epithelium of Western roe deer (Capreolus capreolus), moose (Alces alces alces), and alpaca (Vicunga pacos). Only the European badger and stoat expressed high levels of ACE2 receptor in the nasal mucosal epithelium, which could suggest high susceptibility to ACE2-mediated respiratory infection. Expression of ACE2 receptor in the intestinal cells was ubiquitous across multiple taxa examined. Our results demonstrate the potential for ACE2-mediated viral infection in a selection of wild mammals and highlight the intra-taxon variability of ACE2 receptor expression, which might influence host susceptibility and infection.

Patterns and consequences of age-linked change in local relatedness in animal societies.

The ultimate payoff of behaviours depends not only on their direct impact on an individual, but also on the impact on their relatives. Local relatedness-the average relatedness of an individual to their social environment-therefore has profound effects on social and life history evolution. Recent work has begun to show that local relatedness has the potential to change systematically over an individual's lifetime, a process called kinship dynamics. However, it is unclear how general these kinship dynamics are, whether they are predictable in real systems and their effects on behaviour and life history evolution. In this study, we combine modelling with data from real systems to explore the extent and impact of kinship dynamics. We use data from seven group-living mammals with diverse social and mating systems to demonstrate not only that kinship dynamics occur in animal systems, but also that the direction and magnitude of kinship dynamics can be accurately predicted using a simple model. We use a theoretical model to demonstrate that kinship dynamics can profoundly affect lifetime patterns of behaviour and can drive sex differences in helping and harming behaviour across the lifespan in social species. Taken together, this work demonstrates that kinship dynamics are likely to be a fundamental dimension of social evolution, especially when considering age-linked changes and sex differences in behaviour and life history.

Uptake of baits by wild badgers: Influences of deployment method, badger age and activity patterns on potential delivery of an oral vaccine.

In parts of the United Kingdom and Ireland, the European badger is a wildlife host for Mycobacterium bovis (the causative agent of bovine tuberculosis). Badger vaccination is one management option for reducing disease spread. Vaccination is currently achieved by parenteral vaccination of captured badgers, but an oral vaccine delivered in a bait may provide an additional approach in the future. We conducted two field experiments in wild badger populations to identify factors that influence uptake (% of individuals with evidence of bait consumption) of candidate oral vaccine baits. In both instances, baits containing the biomarker iophenoxic acid (as a proxy for the vaccine) were fed at burrows (setts) associated with badger social groups (study A = 48 groups, study B = 40 groups). Badgers were captured following a period of bait deployment to quantify uptake in relation to age, sex and social group. In addition, groups were allocated different treatments and the bait deployment protocol was varied to identify effects on uptake. Study A tested the effects of season, bait type, bait placement and packaging, while study B investigated the effects of bait quantity and badger activity levels. Overall bait uptake was low (Study A = 24 %, Study B = 37 %) but this varied among treatment groups (range 0-58 %). In both studies, bait uptake was significantly higher in cubs than in adults. Uptake was substantially higher where baits were placed directly into sett entrances (rather than under tiles near setts), and by badgers caught at main setts rather than at outlier setts. Season, bait type and packaging did not influence uptake, while increasing the quantity of bait available increased uptake by cubs but not by adults. Levels of badger activity at setts varied over time (suggesting potential disturbance), but were positively associated with levels of bait uptake.

Serologic responses correlate with current but not future bacterial shedding in badgers naturally infected with Mycobacterium bovis.

Bovine tuberculosis is a challenging cattle disease with substantial economic costs in affected countries. Eradication in parts of the United Kingdom and Ireland is hindered by transmission of the causative agent Mycobacterium bovis between cattle and European badgers (Meles meles). Diagnostic tests in badgers are of limited accuracy but may help us understand and predict disease progression. This study aimed to determine the practical ability of a commercially available serologic test, the Dual Path Platform VetTB assay (DPP), to predict mycobacterial shedding (i.e. infectiousness) and disease progression in badgers, and whether test outcomes were associated with re-capture. Clinical samples collected from 2014 to 2019 from a wild, naturally infected population of badgers in southwest England were tested using mycobacterial culture (from sputum, urine, faeces, abscesses and bite wounds), an interferon-gamma release assay and the DPP assay. Data were analysed at both individual badger and social group levels using generalised linear and cumulative-link mixed models, and linear regression. Only the highest DPP readings [optical density relative light unit (RLU) levels] were associated with mycobacterial shedding [odds ratio (OR) for DPP levels > 100 RLU in individual badgers: 79.6, 95%CI: 14.7-848; and for social groups: OR: 7.28, 95%CI: 2.94-21.44; compared with levels < 100 RLU]. For individual badgers, RLU levels at first capture were not associated with disease progression at subsequent captures. Finally, badgers with very high DPP levels (> 1000 RLU) were four times less likely to be recaptured (OR: 0.24, 95%CI: 0.07-0.83) than those without a detectable DPP response, which might indicate enhanced mortality. We conclude that DPP levels of > 100 RLU identify badgers that are likely to be shedding M. bovis. Levels of > 1000 RLU identify badgers that are much less likely to be re-captured. These results provide insights into the potential value of existing tests in intervention strategies for managing M. bovis in badgers.

Differential susceptibility of SARS-CoV-2 in animals: Evidence of ACE2 host receptor distribution in companion animals, livestock and wildlife by immunohistochemical characterisation.

Angiotensin converting enzyme 2 (ACE2) is a host cell membrane protein (receptor) that mediates the binding of coronavirus, most notably SARS coronaviruses in the respiratory and gastrointestinal tracts. Although SARS-CoV-2 infection is mainly confined to humans, there have been numerous incidents of spillback (reverse zoonoses) to domestic and captive animals. An absence of information on the spatial distribution of ACE2 in animal tissues limits our understanding of host species susceptibility. Here, we describe the distribution of ACE2 using immunohistochemistry (IHC) on histological sections derived from carnivores, ungulates, primates and chiroptera. Comparison of mink (Neovison vison) and ferret (Mustela putorius furo) respiratory tracts showed substantial differences, demonstrating that ACE2 is present in the lower respiratory tract of mink but not ferrets. The presence of ACE2 in the respiratory tract in some species was much more restricted as indicated by limited immunolabelling in the nasal turbinate, trachea and lungs of cats (Felis catus) and only the nasal turbinate in the golden Syrian hamster (Mesocricetus auratus). In the lungs of other species, ACE2 could be detected on the bronchiolar epithelium of the sheep (Ovis aries), cattle (Bos taurus), European badger (Meles meles), cheetah (Acinonyx jubatus), tiger and lion (Panthera spp.). In addition, ACE2 was present in the nasal mucosa epithelium of the serotine bat (Eptesicus serotinus) but not in pig (Sus scrofa domestica), cattle or sheep. In the intestine, ACE2 immunolabelling was seen on the microvillus of enterocytes (surface of intestine) across various taxa. These results provide anatomical evidence of ACE2 expression in a number of species which will enable further understanding of host susceptibility and tissue tropism of ACE2 receptor-mediated viral infection.

Spatial and temporal variation in proximity networks of commercial dairy cattle in Great Britain.

The nature of contacts between hosts can be important in facilitating or impeding the spread of pathogens within a population. Networks constructed from contacts between hosts allow examination of how individual variation might influence the spread of infections. Studying the contact networks of livestock species managed under different conditions can additionally provide insight into their influence on these contact structures. We collected high-resolution proximity and GPS location data from nine groups of domestic cattle (mean group size = 85) in seven dairy herds employing a range of grazing and housing regimes. Networks were constructed from cattle contacts (defined by proximity) aggregated by different temporal windows (2 h, 24 h, and approximately 1 week) and by location within the farm. Networks of contacts aggregated over the whole study were highly saturated but dividing contacts by space and time revealed substantial variation in cattle interactions. Cows showed statistically significant variation in the frequency of their contacts and in the number of cows with which they were in contact. When cows were in buildings, compared to being on pasture, contact durations were longer and cows contacted more other cows. A small number of cows showed evidence of consistent relationships but the majority of cattle did not. In one group where management allowed free access to all farm areas, cows showed asynchronous space use and, while at pasture, contacted fewer other cows and showed substantially greater between-individual variation in contacts than other groups. We highlight the degree to which variations in management (e.g. grazing access, milking routine) substantially alter cattle contact patterns, with potentially major implications for infection transmission and social interactions. In particular, where individual cows have free choice of their environment, the resulting contact networks may have a less-risky structure that could reduce the likelihood of direct transmission of infections.

Characterization of potential superspreader farms for bovine tuberculosis: A review.

BACKGROUND: Variation in host attributes that influence their contact rates and infectiousness can lead some individuals to make disproportionate contributions to the spread of infections. Understanding the roles of such 'superspreaders' can be crucial in deciding where to direct disease surveillance and controls to greatest effect. In the epidemiology of bovine tuberculosis (bTB) in Great Britain, it has been suggested that a minority of cattle farms or herds might make disproportionate contributions to the spread of Mycobacterium bovis, and hence might be considered 'superspreader farms'. OBJECTIVES AND METHODS: We review the literature to identify the characteristics of farms that have the potential to contribute to exceptional values in the three main components of the farm reproductive number - Rf : contact rate, infectiousness and duration of infectiousness, and therefore might characterize potential superspreader farms for bovine tuberculosis in Great Britain. RESULTS: Farms exhibit marked heterogeneity in contact rates arising from between-farm trading of cattle. A minority of farms act as trading hubs that greatly augment connections within cattle trading networks. Herd infectiousness might be increased by high within-herd transmission or the presence of supershedding individuals, or infectiousness might be prolonged due to undetected infections or by repeated local transmission, via wildlife or fomites. CONCLUSIONS: Targeting control methods on putative superspreader farms might yield disproportionate benefits in controlling endemic bovine tuberculosis in Great Britain. However, real-time identification of any such farms, and integration of controls with industry practices, present analytical, operational and policy challenges.

Identifying likely transmissions in Mycobacterium bovis infected populations of cattle and badgers using the Kolmogorov Forward Equations.

Established methods for whole-genome-sequencing (WGS) technology allow for the detection of single-nucleotide polymorphisms (SNPs) in the pathogen genomes sourced from host samples. The information obtained can be used to track the pathogen's evolution in time and potentially identify 'who-infected-whom' with unprecedented accuracy. Successful methods include 'phylodynamic approaches' that integrate evolutionary and epidemiological data. However, they are typically computationally intensive, require extensive data, and are best applied when there is a strong molecular clock signal and substantial pathogen diversity. To determine how much transmission information can be inferred when pathogen genetic diversity is low and metadata limited, we propose an analytical approach that combines pathogen WGS data and sampling times from infected hosts. It accounts for 'between-scale' processes, in particular within-host pathogen evolution and between-host transmission. We applied this to a well-characterised population with an endemic Mycobacterium bovis (the causative agent of bovine/zoonotic tuberculosis, bTB) infection. Our results show that, even with such limited data and low diversity, the computation of the transmission probability between host pairs can help discriminate between likely and unlikely infection pathways and therefore help to identify potential transmission networks. However, the method can be sensitive to assumptions about within-host evolution.

Estimating wildlife vaccination coverage using genetic methods.

Vaccination is a useful approach for the control of disease in wildlife populations. However, its effectiveness is dependent in part on delivery to a sufficient proportion of the target population. Measuring the proportions of wild animal populations that have been vaccinated is challenging and so there is a need to develop robust approaches that can contribute to our understanding of the likely efficacy of wildlife vaccination campaigns. We used a modified capture mark recapture technique to estimate vaccine coverage in a wild population of European badgers (Meles meles) vaccinated by live-trapping and injecting with Bacillus Calmette-Guérin as part of a bovine tuberculosis control initiative in Wales, United Kingdom. Our approach used genetic matching of vaccinated animals to a sample of the wider population to estimate the percentage of badgers that had been vaccinated. Individual-specific genetic profiles were obtained using microsatellite genotyping of hair samples, which were collected directly from trapped and vaccinated badgers and non-invasively from the wider population using hair traps deployed at badger burrows (setts). With two nights of trapping at each sett in an annual campaign, an estimated 50 % (95 % confidence interval 40-60 %) of the badger population received at least one dose of vaccine in a single year. Using a simple population model this suggested that the proportion of the population that would have received at least one dose of vaccine over the course of the four year vaccination campaign was between 67 % and 83 %. This is the first attempt, outside of field trials, to quantify the level of vaccine coverage achieved by trapping and injecting badgers, which is currently the only option for delivering BCG vaccine to this species. The results therefore have specific application to bTB control policy and the novel approach may have wider value in wildlife management and research.

Evaluation of the Dual Path Platform (DPP) VetTB assay for the detection of Mycobacterium bovis infection in badgers.

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, represents a major animal health issue. In the United Kingdom and the Republic of Ireland, European badgers (Meles meles) have been shown to act as a reservoir of M. bovis infection, hindering the eradication of bTB in livestock. The availability of suitable diagnostic assays, particularly those that may be applied in a "trap-side" setting, would facilitate the implementation of a wider range of disease control strategies. Here we evaluate the Dual Path Platform (DPP) VetTB assay, a lateral-flow type test for detecting antibodies to M. bovis antigens (MPB83 and ESAT-6/CFP-10). Both serum and whole blood were evaluated as diagnostic samples. Additionally, two methods were evaluated for interpretation of test results (qualitative interpretation by eye and quantitative measurement using an optical reader). The antibody response to MPB83 detected by the DPP VetTB assay increased significantly following experimental M. bovis infection of badgers, whilst the response to ESAT-6/CFP-10 showed no significant change. In sera from TB-free captive and naturally M. bovis infected wild badgers the MPB83 response exhibited a sensitivity of 55 % by eye and quantitative reader (95 % CI: 40-71 and 38-71, respectively), with slightly lower specificity when read by eye (93 % compared to 98 %; 95 % CI: 85-100 and 90-100, respectively). In whole blood, the DPP VetTB assay MPB83 response exhibited a sensitivity of 65 % (95 % CI: 50-80) when interpreted by eye and 53 % (95 % CI: 36-69) using quantitative values, whilst the specificity was 94 % and 98 % respectively (95 % CI: 88-100 and 90-100). Comparison with contemporaneous diagnostic test results from putatively naturally infected and TB-free badgers demonstrated varying levels of agreement. Using sera from naturally M. bovis infected and TB-free badgers, with post mortem confirmation of disease status, the DPP VetTB assay exhibited a sensitivity of 60 % (95 % CI: 41-77) when interpreted using quantitative values (specificity 95 %; 95 % CI: 76-100), and 67 % (95 % CI: 50-84) when read by eye (specificity 95 %; 95 % CI: 86-100). Further work is required to robustly characterize the DPP VetTB assay's performance in a wider selection of samples, and in the practical and epidemiological contexts in which it may be applied.

Effects of trading networks on the risk of bovine tuberculosis incidents on cattle farms in Great Britain.

Trading animals between farms and via markets can provide a conduit for spread of infections. By studying trading networks, we might better understand the dynamics of livestock diseases. We constructed ingoing contact chains of cattle farms in Great Britain that were linked by trading, to elucidate potential pathways for the transmission of infection and to evaluate their effect on the risk of a farm experiencing a bovine tuberculosis (bTB) incident. Our findings are consistent with variation in bTB risk associated with region, herd size, disease risk area and history of previous bTB incidents on the root farm and nearby farms. However, we also identified effects of both direct and indirect trading patterns, such that connections to more farms in the England High-Risk Area up to three movements away from the root farm increased the odds of a bTB incident, while connections with more farms in the England Low-Risk Area up to eight movements away decreased the odds. Relative to other risk factors for bTB, trading behaviours are arguably more amenable to change, and consideration of risks associated with indirect trading, as well direct trading, might therefore offer an additional approach to bTB control in Great Britain.

Combining genomics and epidemiology to analyse bi-directional transmission of Mycobacterium bovis in a multi-host system.

Quantifying pathogen transmission in multi-host systems is difficult, as exemplified in bovine tuberculosis (bTB) systems, but is crucial for control. The agent of bTB, Mycobacterium bovis, persists in cattle populations worldwide, often where potential wildlife reservoirs exist. However, the relative contribution of different host species to bTB persistence is generally unknown. In Britain, the role of badgers in infection persistence in cattle is highly contentious, despite decades of research and control efforts. We applied Bayesian phylogenetic and machine-learning approaches to bacterial genome data to quantify the roles of badgers and cattle in M. bovis infection dynamics in the presence of data biases. Our results suggest that transmission occurs more frequently from badgers to cattle than vice versa (10.4x in the most likely model) and that within-species transmission occurs at higher rates than between-species transmission for both. If representative, our results suggest that control operations should target both cattle and badgers.

No energetic cost of tuberculosis infection in European badgers (Meles meles).

Energy availability and energy use directly influence an organism's life history, fitness and ecological function. In wild animals, abiotic factors such as ambient temperature, season and rainfall, and biotic factors such as body mass, age, social group size and disease status, all potentially influence energy balance. Relatively few studies have examined the effects of disease on the energy expenditure of wild animals. Such studies could further our understanding of factors influencing the transmission of zoonotic diseases. The European badger (Meles meles) is a medium-sized carnivore that occurs in mixed-sex, familial groups across much of its range. In the UK, they are a protected species but are also involved in the epidemiology of bovine tuberculosis (TB) in cattle. We measured the daily energy expenditure (DEE) and resting metabolic rate (RMR) of wild badgers and related this to their TB infection status and a range of other interacting factors including season, group size, disease status, sex, age, body mass and body fat. Individuals were larger and fatter when they were older, and fatter during the winter. Males were also heavier than females during the summer. In addition, individuals from smaller groups that were exposed to TB tended to have lower body mass. There were no direct effects of disease status on DEE or RMR; however, there was a significant interaction whereby DEE increased with body mass in small groups but decreased with body mass in large groups. Results are consistent with the costs of TB infection being met by compensatory mechanisms enabling badgers to survive for extended periods without exhibiting measurable energetic consequences.

Integrating social behaviour, demography and disease dynamics in network models: applications to disease management in declining wildlife populations.

The emergence and spread of infections can contribute to the decline and extinction of populations, particularly in conjunction with anthropogenic environmental change. The importance of heterogeneity in processes of transmission, resistance and tolerance is increasingly well understood in theory, but empirical studies that consider both the demographic and behavioural implications of infection are scarce. Non-random mixing of host individuals can impact the demographic thresholds that determine the amplification or attenuation of disease prevalence. Risk assessment and management of disease in threatened wildlife populations must therefore consider not just host density, but also the social structure of host populations. Here we integrate the most recent developments in epidemiological research from a demographic and social network perspective, and synthesize the latest developments in social network modelling for wildlife disease, to explore their applications to disease management in populations in decline and at risk of extinction. We use simulated examples to support our key points and reveal how disease-management strategies can and should exploit both behavioural and demographic information to prevent or control the spread of disease. Our synthesis highlights the importance of considering the combined impacts of demographic and behavioural processes in epidemics to successful disease management in a conservation context. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'.

Predicting badger visits to farm yards and making predictions available to farmers.

The use of agricultural resources or environments by wildlife may result in opportunities for transmission of infections amongst wild animals, livestock and humans. Targeted use of biosecurity measures may therefore reduce disease risks, although this requires practical knowledge of where such measures would be most effective, and effective means of communicating risks so that stakeholders can make informed decisions about such investment. In parts of Europe, the European badger Meles meles may act as a wildlife reservoir for Mycobacterium bovis, the causative agent of bovine tuberculosis, and badger visits to farmyards may provide potential opportunities for transmission of M. bovis to cattle. Biosecurity measures are effective in reducing badger activity in farmyards, although it is unclear which farms should be targeted with such measures. We used cameras to monitor badger activity in 155 farmyards in south west England and Wales, and related variations in the presence and frequency of badger visits to farm characteristics. Badgers were recorded on camera in 40% of farmyards monitored. However, the frequency of visits was highly variable, with badgers recorded on >50% of nights in only 10% of farms. The presence of badgers in farmyards was positively associated with the density of badger setts, the number of feed stores and the number of cattle sheds, and negatively associated with the distance to the nearest active badger sett, the presence of a house/dwelling and the number of cattle housed on the farm. The frequency of visits was negatively associated with the distance to the nearest active badger sett and the number of cattle housed. Models predicted the presence/absence of badgers in farmyards with 73% accuracy (62% sensitivity, 81% specificity, using a cut off value of 0.265). Models could not distinguish between farms with low/high frequency of visits, although farms predicted as having badgers present typically had a higher frequency of visits than those that were not. We developed and present an interactive web based application: the Badger Farm Assessment Tool (BFAT), to allow users to enter the characteristics of a farm and generate a relative risk score describing the likelihood of badger visits.

Contact chains of cattle farms in Great Britain.

Network analyses can assist in predicting the course of epidemics. Time-directed paths or 'contact chains' provide a measure of host-connectedness across specified timeframes, and so represent potential pathways for spread of infections with different epidemiological characteristics. We analysed networks and contact chains of cattle farms in Great Britain using Cattle Tracing System data from 2001 to 2015. We focused on the potential for between-farm transmission of bovine tuberculosis, a chronic infection with potential for hidden spread through the network. Networks were characterized by scale-free type properties, where individual farms were found to be influential 'hubs' in the network. We found a markedly bimodal distribution of farms with either small or very large ingoing and outgoing contact chains (ICCs and OCCs). As a result of their cattle purchases within 12-month periods, 47% of British farms were connected by ICCs to more than 1000 other farms and 16% were connected to more than 10 000 other farms. As a result of their cattle sales within 12-month periods, 66% of farms had OCCs that reached more than 1000 other farms and 15% reached more than 10 000 other farms. Over 19 000 farms had both ICCs and OCCs reaching more than 10 000 farms for two or more years. While farms with more contacts in their ICCs or OCCs might play an important role in disease spread, farms with extensive ICCs and OCCs might be particularly important by being at higher risk of both acquiring and disseminating infections.

The diversity of population responses to environmental change.

The current extinction and climate change crises pressure us to predict population dynamics with ever-greater accuracy. Although predictions rest on the well-advanced theory of age-structured populations, two key issues remain poorly explored. Specifically, how the age-dependency in demographic rates and the year-to-year interactions between survival and fecundity affect stochastic population growth rates. We use inference, simulations and mathematical derivations to explore how environmental perturbations determine population growth rates for populations with different age-specific demographic rates and when ages are reduced to stages. We find that stage- vs. age-based models can produce markedly divergent stochastic population growth rates. The differences are most pronounced when there are survival-fecundity-trade-offs, which reduce the variance in the population growth rate. Finally, the expected value and variance of the stochastic growth rates of populations with different age-specific demographic rates can diverge to the extent that, while some populations may thrive, others will inevitably go extinct.

Modeling as a Decision Support Tool for Bovine TB Control Programs in Wildlife.

Computer modeling has a long history of association with epidemiology, and has improved our understanding of the theory of disease dynamics and provided insights into wildlife disease management. A summary of badger bovine TB models and their role in decision making is presented, from a simple initial SEI model, to SEIR (inclusion of a recovered category) and SEI1I2 (inclusion of two stages of disease progression) variants, and subsequent spatially-explicit individual-based models used to assess historical badger management strategies. The integration of cattle into TB models allowed comparison of the predicted impacts of different badger management strategies on cattle herd breakdown rates, and provided an economic dimension to the outputs. Estimates of R0 for bovine TB in cattle and badgers are little higher than unity implying that the disease should be relatively easy to control, which is at odds with practical experience. A cohort of recent models have suggested that combined strategies, involving management of both host species and including vaccination may be most effective. Future models of badger vaccination will need to accommodate the partial protection from infection and likely duration of immunity conferred by the currently available vaccine (BCG). Descriptions of how models could better represent the ecological and epidemiological complexities of the badger-cattle TB system are presented, along with a wider discussion of the utility of modeling for bovine TB management interventions. This includes consideration of the information required to maximize the utility of the next generation of models.

Bait uptake by wild badgers and its implications for oral vaccination against tuberculosis.

The deployment of baits containing vaccines or toxins has been used successfully in the management of wildlife populations, including for disease control. Optimisation of deployment strategies seeks to maximise uptake by the targeted population whilst ensuring cost-effectiveness. Tuberculosis (TB) caused by infection with Mycobacterium bovis affects a broad range of mammalian hosts across the globe, including cattle, wildlife and humans. The control of TB in cattle in the UK and Republic of Ireland is hampered by persistent infection in European badgers (Meles meles). The present study aimed to determine the best strategy for maximising uptake of an oral vaccine by wild badgers, using a surrogate novel bait deployed at 40 badger social groups. Baits contained a blood-borne biomarker (Iophenoxic Acid, IPA) in order to measure consumption in badgers subsequently cage trapped at targeted setts. Evidence for the consumption of bait was found in 83% (199/240) of captured badgers. The probability that badgers had consumed at least one bait (IPA >10 µg ml-1) was significantly higher following deployment in spring than in summer. Lower uptake amongst social groups where more badgers were captured, suggested competition for baits. The probability of bait consumption was significantly higher at groups where main and outlier setts were provided with baits than at those where outliers were present but not baited. Badgers captured 10-14 days post bait feeding had significantly higher levels of bait uptake compared to those caught 24-28 days later. Uptake rates did not vary significantly in relation to badger age and whether bait was placed above ground or down setts. This study suggests that high levels of bait uptake can be achieved in wild badger populations and identifies factors influencing the potential success of different deployment strategies. The implications for the development of an oral badger vaccine are discussed.

Investigation into the genetic diversity in toll-like receptors 2 and 4 in the European badger Meles meles.

The Toll-like receptor (TLR) genes are a conserved family of genes central to the innate immune response to pathogen infection. They encode receptor proteins, recognise pathogen associated molecular patterns (PAMPs) and trigger initial immune responses. In some host-pathogen systems, it is reported that genetic differences, such as single nucleotide polymorphisms (SNPs), associate with disease resistance or susceptibility. Little is known about TLR gene diversity in the European badger (Meles meles). We collected DNA from UK badgers, carried out PCR amplification of the badger TLR2 gene and exon 3 of TLR4 and determined DNA sequences for individual badgers for TLR2 (n = 61) and TLR4 exon 3 (n = 59). No polymorphism was observed in TLR4. Three TLR2 amino acid haplotype variants were found. Ninety five percent of badgers were homozygous for one common haplotype (H1), the remaining three badgers had genotypes H1/H3, H1/H2 and H2/H2. By broad comparison with other species, diversity in TLR genes in badgers seems low. This could be due to a relatively localised sampling or inherent low genetic diversity. Further studies are required to assess the generality of the low observed diversity and the relevance to the immunological status of badgers.