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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Complex responses to movement-based disease control: when livestock trading helps.

Livestock disease controls are often linked to movements between farms, for example, via quarantine and pre- or post-movement testing. Designing effective controls, therefore, benefits from accurate assessment of herd-to-herd transmission. Household models of human infections make use of R*, the number of groups infected by an initial infected group, which is a metapopulation level analogue of the basic reproduction number R0 that provides a better characterization of disease spread in a metapopulation. However, existing approaches to calculate R* do not account for individual movements between locations which means we lack suitable tools for livestock systems. We address this gap using next-generation matrix approaches to capture movements explicitly and introduce novel tools to calculate R* in any populations coupled by individual movements. We show that depletion of infectives in the source group, which hastens its recovery, is a phenomenon with important implications for design and efficacy of movement-based controls. Underpinning our results is the observation that R* peaks at intermediate livestock movement rates. Consequently, under movement-based controls, infection could be controlled at high movement rates but persist at intermediate rates. Thus, once control schemes are present in a livestock system, a reduction in movements can counterintuitively lead to increased disease prevalence. We illustrate our results using four important livestock diseases (bovine viral diarrhoea, bovine herpes virus, Johne's disease and Escherichia coli O157) that each persist across different movement rate ranges with the consequence that a change in livestock movements could help control one disease, but exacerbate another.

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.

Climate-driven tipping-points could lead to sudden, high-intensity parasite outbreaks.

Parasitic nematodes represent one of the most pervasive and significant challenges to grazing livestock, and their intensity and distribution are strongly influenced by climate. Parasite levels and species composition have already shifted under climate change, with nematode parasite intensity frequently low in newly colonized areas, but sudden large-scale outbreaks are becoming increasingly common. These outbreaks compromise both food security and animal welfare, yet there is a paucity of predictions on how climate change will influence livestock parasites. This study aims to assess how climate change can affect parasite risk. Using a process-based approach, we determine how changes in temperature-sensitive elements of outbreaks influence parasite dynamics, to explore the potential for climate change to influence livestock helminth infections. We show that changes in temperate-sensitive parameters can result in nonlinear responses in outbreak dynamics, leading to distinct 'tipping-points' in nematode parasite burdens. Through applying two mechanistic models, of varying complexity, our approach demonstrates that these nonlinear responses are robust to the inclusion of a number of realistic processes that are present in livestock systems. Our study demonstrates that small changes in climatic conditions around critical thresholds may result in dramatic changes in parasite burdens.

Stakeholder opinions on the practicality of management interventions to control bovine tuberculosis.

Livestock disease control strategies are usually determined at national and international levels, yet their successful implementation is determined by stakeholders operating at local scales. Such stakeholders may also have detailed knowledge that would contribute to the development of disease control options suited to the socio-cultural and environmental conditions where management is undertaken. The aim of this study was to evaluate stakeholders' opinions of a list of potential bovine tuberculosis (TB) management interventions for South Central Spain. This area has high TB prevalence in wildlife and livestock, so veterinarians, livestock farmers and hunters are all key stakeholders in TB management. A literature review identified possible management activities. The effectiveness of each intervention was ranked by local experts, and practicality was ranked by hunters, cattle farmers and veterinarians, using a best-worst scaling exercise as part of a questionnaire. The most effective intervention, the banning of supplemental feeding of game species, was not considered practical by stakeholders. The most effective and practical interventions were the separation of wildlife and livestock access to waterholes, testing cattle every 3 months on farms with a recent positive TB case and removing gut-piles from the land after hunting events. Although all three of these options were well supported, each stakeholder group supported different approaches more strongly, suggesting that it might be effective to promote different disease management contributions in different stakeholder communities. This integrated approach contributes to the identification of the optimum combination of management tools that can be delivered effectively.

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.

Use of wild bird surveillance, human case data and GIS spatial analysis for predicting spatial distributions of West Nile virus in Greece.

West Nile Virus (WNV) is the causative agent of a vector-borne, zoonotic disease with a worldwide distribution. Recent expansion and introduction of WNV into new areas, including southern Europe, has been associated with severe disease in humans and equids, and has increased concerns regarding the need to prevent and control future WNV outbreaks. Since 2010, 524 confirmed human cases of the disease have been reported in Greece with greater than 10% mortality. Infected mosquitoes, wild birds, equids, and chickens have been detected and associated with human disease. The aim of our study was to establish a monitoring system with wild birds and reported human cases data using Geographical Information System (GIS). Potential distribution of WNV was modelled by combining wild bird serological surveillance data with environmental factors (e.g. elevation, slope, land use, vegetation density, temperature, precipitation indices, and population density). Local factors including areas of low altitude and proximity to water were important predictors of appearance of both human and wild bird cases (Odds Ratio = 1,001 95%CI = 0,723-1,386). Using GIS analysis, the identified risk factors were applied across Greece identifying the northern part of Greece (Macedonia, Thrace) western Greece and a number of Greek islands as being at highest risk of future outbreaks. The results of the analysis were evaluated and confirmed using the 161 reported human cases of the 2012 outbreak predicting correctly (Odds = 130/31 = 4,194 95%CI = 2,841-6,189) and more areas were identified for potential dispersion in the following years. Our approach verified that WNV risk can be modelled in a fast cost-effective way indicating high risk areas where prevention measures should be implemented in order to reduce the disease incidence.

Demographic processes drive increases in wildlife disease following population reduction.

Population reduction is often used as a control strategy when managing infectious diseases in wildlife populations in order to reduce host density below a critical threshold. However, population reduction can disrupt existing social and demographic structures leading to changes in observed host behaviour that may result in enhanced disease transmission. Such effects have been observed in several disease systems, notably badgers and bovine tuberculosis. Here we characterise the fundamental properties of disease systems for which such effects undermine the disease control benefits of population reduction. By quantifying the size of response to population reduction in terms of enhanced transmission within a generic non-spatial model, the properties of disease systems in which such effects reduce or even reverse the disease control benefits of population reduction are identified. If population reduction is not sufficiently severe, then enhanced transmission can lead to the counter intuitive perturbation effect, whereby disease levels increase or persist where they would otherwise die out. Perturbation effects are largest for systems with low levels of disease, e.g. low levels of endemicity or emerging disease. Analysis of a stochastic spatial meta-population model of demography and disease dynamics leads to qualitatively similar conclusions. Moreover, enhanced transmission itself is found to arise as an emergent property of density dependent dispersal in such systems. This spatial analysis also shows that, below some threshold, population reduction can rapidly increase the area affected by disease, potentially expanding risks to sympatric species. Our results suggest that the impact of population reduction on social and demographic structures is likely to undermine disease control in many systems, and in severe cases leads to the perturbation effect. Social and demographic mechanisms that enhance transmission following population reduction should therefore be routinely considered when designing control programmes.