Dataset on risk factors for seroconversion against Mycobacterium avium subspecies paratuberculosis in dairy cows.

Johne's disease (JD) is a chronic wasting disease caused by Mycobacterium avium subspecies paratuberculosis (MAP). MAP is responsible for large economic losses for the dairy sector and has been linked to human disease. Susceptibly to MAP is mainly limited to young animals and diagnostic tests are poor at detecting MAP in early stages of infection. Therefore, ascertaining the contribution of the dam to the risk of calf infection and the relative role of the different infection routes is important to inform disease control measures. This data article presents MAP exposures at time of calving on a cohort of 439 calves born between 2012 and 2013 from 6 UK dairy herds. Each calf participated in routine quarterly MAP milk ELISA testing using the IDEXX Porquire ELISA. Each animal was followed until testing MAP positive, being culled or end of follow up (January 2023). The dataset includes risk factors associated with transmission via colostrum route (MAP status of cow giving colostrum); transmission via the dam (MAP status of the dam) and transmission via fecal oral route (whether at birth the calf spent a long time in a dirty yard). Ascertainment of exposure to risk factors involved video recording and self-capture data forms from time of calving in the maternity area of the farms until calf left the area. The dataset provides a unique opportunity to examine MAP infection and its relationship with different exposures at time of birth, where cows were followed up during their entire lives.

Applications of machine learning in animal and veterinary public health surveillance.

Machine learning (ML) is an approach to artificial intelligence characterised by the use of algorithms that improve their own performance at a given task (e.g. classification or prediction) based on data and without being explicitly and fully instructed on how to achieve this. Surveillance systems for animal and zoonotic diseases depend upon effective completion of a broad range of tasks, some of them amenable to ML algorithms. As in other fields, the use of ML in animal and veterinary public health surveillance has greatly expanded in recent years. Machine learning algorithms are being used to accomplish tasks that have become attainable only with the advent of large data sets, new methods for their analysis and increased computing capacity. Examples include the identification of an underlying structure in large volumes of data from an ongoing stream of abattoir condemnation records, the use of deep learning to identify lesions in digital images obtained during slaughtering, and the mining of free text in electronic health records from veterinary practices for the purpose of sentinel surveillance. However, ML is also being applied to tasks that previously relied on traditional statistical data analysis. Statistical models have been used extensively to infer relationships between predictors and disease to inform risk-based surveillance, and increasingly, ML algorithms are being used for prediction and forecasting of animal diseases in support of more targeted and efficient surveillance. While ML and inferential statistics can accomplish similar tasks, they have different strengths, making one or the other more or less appropriate in a given context.

L'apprentissage automatique (AA) est une approche de l'intelligence artificielle caractérisée par l'utilisation d'algorithmes qui améliorent leurs propres performances sur une tâche donnée (par exemple, la classification ou la prédiction) sur la base de données et sans avoir reçu d'instructions spécifiques ou complètes concernant la marche à suivre. Les systèmes de surveillance des maladies animales et des zoonoses sont tributaires de la mise en oeuvre efficace d'un large éventail de tâches, parmi lesquelles certaines sont susceptibles de fonctionner avec des algorithmes d'AA. Comme dans d'autres domaines, l'utilisation de l'AA s'est beaucoup développée ces dernières années dans le secteur de la surveillance de la santé animale et de la santé publique vétérinaire. Les algorithmes d'AA sont utilisés pour accomplir des tâches qui ne sont devenues possibles que grâce à l'arrivée de grandes séries de données, de nouvelles méthodes d'analyse et de capacités informatiques accrues. Parmi les exemples, on peut citer la capacité à déceler une structure sous-jacente dans de grands volumes de données provenant d'un flux continu de registres de saisies d'abattoirs, l'utilisation de l'apprentissage profond pour identifier les lésions révélées par les images numériques obtenues pendant l'abattage et l'extraction de texte libre à partir des registres sanitaires électroniques des cabinets vétérinaires à des fins de surveillance sentinelle. L'AA est cependant également appliqué dans des tâches qui s'appuyaient précédemment sur une analyse classique de données statistiques. Les modèles statistiques ont été largement utilisés pour déduire des relations entre prédicteurs et maladie afin d'étayer la surveillance fondée sur le risque ; les algorithmes d'AA sont de plus en plus utilisés pour prédire et pronostiquer des maladies animales en vue d'une surveillance plus ciblée et efficace. S'il est vrai que l'AA et la statistique inférentielle peuvent accomplir des tâches similaires, chaque approche présente ses propres atouts et pourra se révéler plus ou moins pertinente selon le contexte spécifique.

El aprendizaje automático es una vertiente de la inteligencia artificial que se caracteriza por el uso de algoritmos capaces de mejorarse a sí mismos en la ejecución de una determinada tarea (p.ej., procesos de clasificación o predicción) con empleo de datos y sin necesidad de recibir instrucciones explícitas y completas sobre la manera de lograrlo. Los sistemas de vigilancia de enfermedades animales y zoonóticas dependen de la ejecución eficaz de numerosas y muy diversas tareas, algunas de las cuales se prestan al uso de algoritmos de aprendizaje automático. Al igual que en otros campos, la aplicación del aprendizaje automático en sanidad animal y salud pública veterinaria se ha extendido sobremanera en los últimos años. Ahora se utilizan algoritmos de aprendizaje automático para realizar tareas que solo han empezado a ser factibles con el advenimiento de ingentes conjuntos de datos, nuevos métodos para analizarlos y una mayor capacidad de tratamiento informático. Entre otros ejemplos, cabe citar la determinación de la estructura subyacente de grandes volúmenes de datos procedentes de un flujo continuo de registros de los descartes de matadero; la utilización del aprendizaje profundo para detectar lesiones en imágenes digitales obtenidas durante las operaciones de sacrificio, o el análisis del texto libre de registros sanitarios electrónicos de procedimientos veterinarios con fines de vigilancia centinela. Con todo, el aprendizaje automático se está aplicando también a tareas que anteriormente reposaban en el análisis estadístico clásico de los datos. Los modelos estadísticos han sido extensamente utilizados para inferir relaciones entre una enfermedad y uno u otro predictor y alimentar a partir de ahí la vigilancia basada en el riesgo. Por otro lado, cada vez más se vienen empleando algoritmos de aprendizaje automático para predecir y anticipar enfermedades animales y conferir así más eficacia y especificidad a las actividades de vigilancia. Aunque el aprendizaje automático y la estadística inferencial realizan tareas parecidas, sus puntos fuertes son distintos, con lo cual, en función del contexto de que se trate, será preferible recurrir a uno u otro método.

Surveillance and risk assessment for early detection of emerging infectious diseases in livestock.

Those who work in the area of surveillance and prevention of emerging infectious diseases (EIDs) face a challenge in accurately predicting where infection will occur and who (or what) it will affect. Establishing surveillance and control programmes for EIDs requires substantial and long-term commitment of resources that are limited in nature. This contrasts with the unquantifiable number of possible zoonotic and non-zoonotic infectious diseases that may emerge, even when the focus is restricted to diseases involving livestock. Such diseases may emerge from many combinations of, and changes in, host species, production systems, environments/habitats and pathogen types. Given these multiple elements, risk prioritisation frameworks should be used more widely to support decision-making and resource allocation for surveillance. In this paper, the authors use recent examples of EID events in livestock to review surveillance approaches for the early detection of EIDs, and highlight the need for surveillance programmes to be informed and prioritised by regularly updated risk assessment frameworks. They conclude by discussing some unmet needs in risk assessment practices for EIDs, and the need for improved coordination in global infectious disease surveillance.

Les personnes travaillant dans le domaine de la surveillance et de la prévention des maladies infectieuses émergentes (MIE) sont confrontées à la difficulté de prédire avec exactitude le lieu d'émergence d'une maladie, ainsi que l'espèce, le système ou le site affectés. La mise en place de programmes de surveillance et de lutte contre les MIE exige une mobilisation conséquente et durable de ressources nécessairement limitées. Par contraste, le nombre des maladies infectieuses zoonotiques et non zoonotiques pouvant se déclarer est impossible à quantifier, même si l'on s'en tient aux seules maladies affectant les animaux d'élevage. Ces maladies surviennent à la faveur des nombreuses et diverses configurations, associations ou modifications qui peuvent se produire parmi les espèces hôtes, les systèmes de production, les environnements ou habitats et les types d'agents pathogènes. Compte tenu de la multiplicité de ces éléments, il devrait être fait plus largement appel à des cadres de priorisation du risque afin de soutenir les processus de prise de décision et d'allocation des ressources en matière de surveillance. Les auteurs s'appuient sur des exemples récents d'événements liés à des MIE pour faire le point sur les méthodes de surveillance appliquées pour la détection précoce de ces maladies et soulignent l'importance de documenter et de prioriser les programmes de surveillance en procédant à des mises à jour régulières des cadres utilisés pour l'évaluation du risque. Ils concluent en évoquant certains aspects importants que les pratiques actuelles d'évaluation du risque ne permettent pas de couvrir lorsqu'il s'agit de MIE, ainsi que l'importance d'améliorer la coordination de la surveillance des maladies infectieuses au niveau mondial.

Cuantos trabajan en el ámbito de la vigilancia y la prevención de enfermedades infecciosas emergentes (EIE) tienen dificultades para predecir con precisión dónde va a surgir y a quién (o qué) afectará una infección. La instauración de programas de vigilancia y control de EIE exige una inversión sustancial y duradera de recursos que por definición son escasos, sobre todo teniendo en cuenta el número incalculable de enfermedades infecciosas zoonóticas y no zoonóticas que pueden aparecer, aun considerando solo aquellas que afectan al ganado. Este tipo de enfermedades pueden surgir como resultado de muchas combinaciones distintas de especie hospedadora, sistema productivo, medio/hábitat y tipo de patógeno o por efecto de cambios que se den en cualquiera de estos elementos. En vista de la multiplicidad de factores que concurren, convendría emplear de modo más generalizado un sistema de jerarquización de los riesgos en el cual fundamentar las decisiones de vigilancia y la distribución de los recursos destinados a ella. Los autores, valiéndose de ejemplos recientes de episodios infecciosos emergentes que afectaron al ganado, pasan revista a distintos métodos de vigilancia para la detección temprana de EIE y recalcan que los programas de vigilancia deben reposar en procedimientos de determinación del riesgo periódicamente actualizados y en las prioridades fijadas a partir de estos procedimientos. Por último, los autores se detienen en algunas necesidades desatendidas en la praxis de la determinación del riesgo de EIE y en la necesidad de una mejor coordinación de la vigilancia mundial de las enfermedades infecciosas.

Modelling the control of bovine brucellosis in India.

Brucellosis imposes substantial impacts on livestock production and public health worldwide. A stochastic, age-structured model incorporating herd demographics was developed describing within- and between-herd transmission of Brucella abortus in dairy cattle herds. The model was fitted to data from a cross-sectional study conducted in Punjab State of India and used to evaluate the effectiveness of control strategies under consideration. Based on model results, stakeholder acceptance and constraints regarding vaccine supply, vaccination of replacement calves in large farms should be prioritized. Test and removal applied at early stages of the control programme where seroprevalence is high would not constitute an effective or acceptable use of resources because significant numbers of animals would be 'removed' (culled or not used for breeding) based on false positive results. To achieve sustained reductions in brucellosis, policymakers must commit to maintaining vaccination in the long term, which may eventually reduce frequency of infection in the livestock reservoir to a low enough level for elimination to be a realistic objective. This work provides key strategic insights into the control of brucellosis in India, which has the largest cattle population globally, and a general modelling framework for evaluating control strategies in endemic settings.

Effect of tuberculin skin testing on serological results against Mycobacterium avium ssp. paratuberculosis (MAP): Evidence of distinct effects in MAP-infected and noninfected cows.

Johne's disease and bovine tuberculosis are diseases of economic, public health, and animal welfare importance. The single intradermal cervical comparative tuberculin (SICCT) test, which is used to determine bovine tuberculosis status as part of eradication schemes in the United Kingdom and some other countries, has been reported to interfere with the results of the widely used ELISA to detect antibodies against Mycobacterium avium ssp. paratuberculosis (MAP) in milk. Better understanding of the relationship between SICCT and MAP tests can improve management and control of Johne's disease. The aim of this study was to characterize the relationship between SICCT testing and milk ELISA performance and to assess whether the immunological response to the SICCT test is different for MAP-infected cows and noninfected cows. We used repeated MAP milk ELISA test results of a cohort of 805,561 cows in the United Kingdom between 2010 and 2018 that had milk ELISA tests within 90 d of SICCT testing to identify cows likely to be infected. We then assessed, separately, for cows deemed to be MAP-infected and noninfected, the association between MAP test results and proximity to SICCT testing by means of survival analysis and generalized additive mixed models. The results were used to quantify the effect SICCT testing may have on performance of milk ELISA tests conducted soon after SICCT testing. At high prevalence levels (20%) of MAP in the infected herd, overall accuracy of the milk ELISA is not reduced when testing occurs within 14 d from SICCT testing. Milk ELISA values of cows deemed to be infected were highest when MAP testing was closer in time to SICCT testing, suggesting the SICCT test enhances antibody response for MAP in infected cows. This corresponds to higher sensitivity of the MAP milk ELISA when testing within 30 d of the SICCT test. For cows deemed to be noninfected, the effect of previous SICCT testing was delayed compared with infected cows, with MAP milk ELISA values peaking at around 15 d post-SICCT testing. For both, MAP-infected and noninfected cows, interference from SICCT test diminished 30 d after SICCT testing, suggesting post 30 d to be the most appropriate time for evaluating the milk ELISA for MAP after SICCT testing. Our results provide strong evidence that the effect of the SICCT test on serological response against MAP is different for MAP-infected versus noninfected cows and that, as a result of this distinct effect, it is possible to improve interpretation of MAP milk ELISA test results (higher accuracy) by taking into consideration time since SICCT testing.

Epidemiology of bovine brucellosis in Hisar, India: identification of risk factors and assessment of knowledge, attitudes, and practices among livestock owners.

Brucellosis caused by facultative intracellular bacteria, Brucella, remains a global threat to both animal and human health. In this study we aimed to identify potential risk factors of bovine brucellosis and to assess the knowledge, attitudes, and practices (KAPs) of livestock keepers in Hisar, India. A standardized questionnaire was used to collate information regarding potential risk factors of bovine brucellosis and livestock owners' KAPs. A total of 127 livestock keepers were involved. Serum samples from their animals (n = 635) were tested for the presence of antibodies against Brucella by Rose Bengal Plate Test (RBPT) and indirect enzyme-linked immunosorbent assay (iELISA). Out of these, 78 (61.4%) of the herds had at least one seropositive animal, and 302 (47.6%) of the cattle were seropositive. Univariate and multivariate analysis revealed significant associations between intensive farm type (OR = 4.6; 95% CI, 1.6-16.7; P = 0.009), hygienic disposal of aborted fetuses (OR = 0.3; 95% CI, 0.08-0.9; P = 0.04) and herd seropositivity for brucellosis. The majority, 96 (75.6%) of the respondents, were males aged 18-50, and 82 (64.6%) owned a small-backyard farm. Only 51 (40.2%) of the participants knew about brucellosis; out of them, 54.9% (28/51) could not identify clinical signs of brucellosis. Six (11.8%) participants indicated abortion as the most noticeable clinical sign, and 45.1% indicated that consumption of raw milk is associated with high risk of contracting brucellosis. A large proportion of respondents confirmed that milk from their animals was regularly consumed (86.6%) and sold (59.8%) to other people. These results suggest that bovine brucellosis is endemic in Haryana, where Brucella-contaminated milk is likely being regularly sold. Brucellosis control efforts in Haryana should include education programs to raise awareness of the disease and means to control it in cattle and to prevent zoonotic transmission.

Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns.

BACKGROUND: Abattoir data are under-used for surveillance. Nationwide surveillance could benefit from using data on meat inspection findings, but several limitations need to be overcome. At the producer level, interpretation of meat inspection findings is a notable opportunity for surveillance with relevance to animal health and welfare. In this study, we propose that discovery and monitoring of relational patterns between condemnation conditions co-present in broiler batches at meat inspection can provide valuable information for surveillance of farmed animal health and welfare. RESULTS: Great Britain (GB)-based integrator meat inspection records for 14,045 broiler batches slaughtered in nine, four monthly intervals were assessed for the presence of surveillance indicators relevant to broiler health and welfare. K-means and correlation-based hierarchical clustering, and association rules analyses were performed to identify relational patterns in the data. Incidence of condemnation showed seasonal and temporal variation, which was detected by association rules analysis. Syndrome-related and non-specific relational patterns were detected in some months of meat inspection records. A potentially syndromic cluster was identified in May 2016 consisting of infection-related conditions: pericarditis, perihepatitis, peritonitis, and abnormal colour. Non-specific trends were identified in some months as an unusual combination of condemnation reasons in broiler batches. CONCLUSIONS: We conclude that the detection of relational patterns in meat inspection records could provide producer-level surveillance indicators with relevance to broiler chicken health and welfare.

Identification of production chain risk factors for slaughterhouse condemnation of broiler chickens'.

Slaughterhouse condemnation of broiler chickens results from identification of polymorphic pathological conditions during meat inspection from arrival and on the slaughter line. While conditions that result in condemnation are multifactorial, identification of factors that are common for a number of categories could be valuable for developing strategies to reduce total condemnation. This study aimed to identify those condemnation categories that were most common in batches of broiler chickens and to determine and compare associated risk factors. In the first step, retrospective meat inspection records for 55,918 broiler batches from one large broiler integrator for 2015-2017 were used for association rules analysis. Results identified a network of nine associated condemnation categories: whole carcass condemnation for ascites, abnormal colour, perihepatitis, cellulitis, hard breast, tumours and dead on arrival, and liver only and heart only most often associated with hepatitis and pericarditis, respectively. Secondly, a longitudinal study collected data on 109 explanatory variables from broiler parental flocks to slaughterhouse characteristics between January 2015 and December 2017. Condemnation outcome data were obtained from meat inspection records for 539 broiler batches participating in the study. Parental flock-, rearing farm-, shed- and transport-level risk factors were assessed for each outcome using mixed-effects multivariable Poisson regression including shed and farm as random effects. A Poisson regression tree method was used as the first step to identify variables most relevant for analysis and comparison across the outcomes. No single production factor was associated with all nine of the condemnation outcomes investigated in this study, although some were shared across multiple outcomes: age of parental flock at time of lay, flock-level Campylobacter spp. frequency, broiler chick weight at seven days of age, weight at slaughter, type of broiler removal (i.e. thinning, final depopulation), catcher team, number of birds per transport crate, slaughterhouse shift number, and type of slaughterhouse line. Broiler chickens removed during final depopulation were at greatest risk of condemnation. Condemnation rates for cellulitis and tumours were found to be higher in broilers inspected by night shift at the slaughterhouse. Discovery of an apparent protective effect of a higher number of broilers per transport crate was unexpected. These findings provide information for the broiler industry on production chain factors that might be amenable to targeted intervention to improve future efforts for control of condemnation.

Mycobacterium avium paratuberculosis infection of calves - The impact of dam infection status.

Johne's disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a chronic condition of dairy cattle, and is endemic in the UK. Lack of understanding of the relative importance of different transmission routes reduces the impact of control scheme recommendations. The long incubation period for Johne's disease makes evaluation of control schemes difficult, and so this long-term cohort study offers a rare and valuable insight into the disease epidemiology. A longitudinal study was carried out following a cohort of 440 UK dairy cows in 6 herds recruited in 2012-2013. Individuals entering the milking herd were routinely monitored for the presence of MAP using quarterly milk ELISA testing. Using a Cox proportional-hazards regression model the relationship between time until first detection of infection and dam MAP status was investigated. We then compared the magnitude of the effect of dam status with that of other risk factors in order to understand its relative importance. Dam status was found to be the only observed factor that was significantly associated with time to an individual testing MAP-positive (p = 0.012). When compared to negative dams, we found a marginally significant effect of having a positive dam at time of calving, that increased the hazard of an individual testing positive by a factor of 2.6 (95% confidence interval: 0.89-7.79, p = 0.081). Further positive associations were found with dams becoming positive after the birth of the subject; a dam seroconverting within 12 months post parturition being associated with a 3.6 fold increase in hazard (95% confidence interval: 1.32-9.77, p = 0.013), and dams seroconverting more than a year after calving increased the hazard by a factor of 2.8 (95% confidence interval: 1.39-5.76, p = 0.004). These results suggest that cows may be transmitting MAP to their offspring at an earlier stage than had previously been thought, and so raise important questions about how this transmission may be occurring. The results of the study may have important practical implications for the management on-farm of the offspring of MAP-positive animals, with the potential to vastly reduce the time required to eliminate this chronic disease.

The relationship between the presence of antibodies and direct detection of Toxoplasma gondii in slaughtered calves and cattle in four European countries.

In cattle, antibodies to Toxoplasma gondii infection are frequently detected, but evidence for the presence of T. gondii tissue cysts in cattle is limited. To study the concordance between the presence of anti-T. gondii IgG and viable tissue cysts of T. gondii in cattle, serum, liver and diaphragm samples of 167 veal calves and 235 adult cattle were collected in Italy, the Netherlands, Romania and the United Kingdom. Serum samples were tested for anti-T. gondii IgG by the modified agglutination test and p30 immunoblot. Samples from liver were analyzed by mouse bioassay and PCR after trypsin digestion. In addition, all diaphragms of cattle that had tested T. gondii-positive (either in bioassay, by PCR on trypsin-digested liver or serologically by MAT) and a selection of diaphragms from cattle that had tested negative were analyzed by magnetic capture quantitative PCR (MC-PCR). Overall, 13 animals were considered positive by a direct detection method: seven out of 151 (4.6%) by MC-PCR and six out of 385 (1.6%) by bioassay, indicating the presence of viable parasites. As cattle that tested positive in the bioassay tested negative by MC-PCR and vice-versa, these results demonstrate a lack of concordance between the presence of viable parasites in liver and the detection of T. gondii DNA in diaphragm. In addition, the probability to detect T. gondii parasites or DNA in seropositive and seronegative cattle was comparable, demonstrating that serological testing by MAT or p30 immunoblot does not provide information about the presence of T. gondii parasites or DNA in cattle and therefore is not a reliable indicator of the risk for consumers.

The transmission dynamics of Campylobacter jejuni among broilers in semi-commercial farms in Jordan.

Campylobacter is the leading cause of foodborne bacterial gastroenteritis in humans worldwide, often associated with the consumption of undercooked poultry. In Jordan, the majority of broiler chicken production occurs in semi-commercial farms, where poor housing conditions and low bio-security are likely to promote campylobacter colonisation. While several studies provided estimates of the key parameters describing the within-flock transmission dynamics of campylobacter in typical high-income countries settings, these data are not available for Jordan and Middle-East in general. A Bayesian model framework was applied to a longitudinal dataset on Campylobacter jejuni infection in a Jordan flock to quantify the transmission rate of C. jejuni in broilers within the farm, the day when the flock first became infected, and the within-flock prevalence (WFP) at clearance. Infection with C. jejuni is most likely to have occurred during the first 8 days of the production cycle, followed by a transmission rate value of 0.13 new infections caused by one infected bird/day (95% CI 0.11-0.17), and a WFP at clearance of 34% (95% CI 0.24-0.47). Our results differ from published studies conducted in intensive poultry production systems in high-income countries but are well aligned with the expectations obtained by means of structured questionnaires submitted to academics with expertise on campylobacter in Jordan. This study provides for the first time the most likely estimates and credible intervals of key epidemiological parameters driving the dynamics of C. jejuni infection in broiler production systems commonly found in Jordan and the Middle-East and could be used to inform Quantitative Microbial Risk Assessment models aimed to assess the risk of human exposure/infection to campylobacter through consumption of poultry meat.

Exploring sub-individual variability: role of ontogeny, abiotic environment and seed-dispersing birds.

Within-individual trait variation - otherwise known as sub-individual variation - is an important component of phenotypic variation, with both a genetic and epigenetic basis. We explore its adaptive value and the effects of ontogeny and the environment on sub-individual variability. We conducted a field study to analyse the effects of tree age, soil pH, soil water content and soil nutrients on sub-individual variability in fruit size of hawthorn (Crataegus monogyna) in three sites in northwest Spain. Additionally, we examined how bird-mediated selection influences average and sub-individual variation in fruit size. Results show that average and sub-individual variations in fruit size were related to fitness affecting seed dispersal. Older trees produced larger fruits, but tree age did not affect sub-individual variation in fruit size. Abiotic environmental factors differently affected sub-individual variation and average fruit size. Seed-dispersing birds exerted correlated selection on average and variation in fruit size, favouring trees with larger and less variable fruit size at one site. Our work suggests that the fruit size variation within individual trees, the sub-individual variation, is modified by abiotic environmental factors and, additionally, is an adaptive trait that responds to natural selection.

The applicability of animal health surveillance systems for post-market monitoring of potential adverse effects of genetically modified (GM) feed.

A facultative post market monitoring of potential health impacts of genetically modified (GM) feedstuffs on livestock consuming these feeds after pre-market risk assessment is under ongoing consideration. Within the IPAFEED database, scientific studies on health effects beyond performance in livestock and the results of a systematic search for evidence of outcome effects due to GM feed are consolidated. These outcomes were reviewed and checked for consistency in order to identify plausible syndromes suitable for conducting surveillance. The 24 selected studies showed no consistent changes in any health parameter. There were no repeated studies in any species by GM crop type and animal species. As such, there is insufficient evidence to inform the design of surveillance systems for detecting known adverse effects. Animal health surveillance systems have been proposed for the post market monitoring of potential adverse effects in animals. Such systems were evaluated for their applicability to the detection of hypothetical adverse effects and their strengths and weaknesses to detect syndromes of concern are presented. For known adverse effects, applied controlled post-market studies may yield conclusive and high-quality evidence. For detecting unknown adverse effects, the use of existing surveillance systems may still be of interest. A simulation tool developed within the project can be adapted and applied to existing surveillance systems to explore their applicability to the detection of potential adverse effects of GM feed.

A probabilistic approach to the interpretation of milk antibody results for diagnosis of Johne's disease in dairy cattle.

Johne's disease is a serious wasting disease of ruminants that is of high economic importance for the dairy sector in particular. The chronic nature of the disease, the fluctuations in antibody levels and the limited ability of diagnostic tests to identify cows at early stages of infection are huge challenges for the control of the disease. In the United Kingdom, the latter is commonly based on repeated milk ELISA testing of lactating cows, followed by selected culling and improved management practices around calving. In this paper, the dataset built through a large quarterly screening programme conducted in the United Kingdom since 2010 is used to investigate the use of milk ELISA testing for Johne's disease management. Over the study period, 13,509 out of 281,558 cows were identified as high-risk of being infected and shedding mycobacteria in the faeces, based on a case definition of at least two consecutive positive milk ELISA results. Around a third of them were kept in the dairy herd a year or more after being classified as high-risk. However, 16% of these cows did not have any further positive test, suggesting that they might be uninfected animals. The mean specificity and sensitivity of the milk ELISA test were estimated at 99.5% and 61.8%, respectively. The cows in the dataset are categorised in different result groups according to the number of positive test results and whether they are classified as high-risk according to the programme's case definition. The posterior probability of infection is calculated after each test in order to investigate the impact of repeated testing on the belief in a cow's infection status. The interpretation of the results show that most cows classified as high-risk are very likely to be infected, while some other groups that do not match the case definition could reasonably be considered as infected too. Our results show that there is considerable potential for more targeted use of serological testing, including adjusting the testing frequency and implementing the posterior probability approach.

Brucellosis in West and Central Africa: A review of the current situation in a changing landscape of dairy cattle systems.

Brucellosis is a neglected endemic zoonosis in West and Central Africa. In this narrative review, evidence of livestock and human infection is presented along with details of past and current control strategies in 14 selected countries. Data from available literature is combined with expert opinion elicited during a regional workshop on brucellosis diagnostics. Demographic changes that affect both the epidemiology of brucellosis and the success of control or surveillance are also considered. The evidence suggests that brucellosis prevalence in emerging peri-urban dairy cattle systems may be higher than that found in traditional transhumant extensive systems. Accurate microbiological and epidemiological evidence across the region is lacking but it appears there is inherent interest in controlling the disease. There are many data gaps which require collaborative future research to evaluate fully the social and economic impact of the disease in an evolving livestock sector heavily influenced by high rates of urbanisation and regional population growth.

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata.

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining 'big' data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype.

Knowledge gaps in host-parasite interaction preclude accurate assessment of meat-borne exposure to Toxoplasma gondii.

Toxoplasma gondii is recognized as a widely prevalent zoonotic parasite worldwide. Although several studies clearly identified meat products as an important source of T. gondii infections in humans, quantitative understanding of the risk posed to humans through the food chain is surprisingly scant. While probabilistic risk assessments for pathogens such as Campylobacter jejuni, Listeria monocytogenes or Escherichia coli have been well established, attempts to quantify the probability of human exposure to T. gondii through consumption of food products of animal origin are at early stages. The biological complexity of the life cycle of T. gondii and limited understanding of several fundamental aspects of the host/parasite interaction, require the adoption of numerous critical assumptions and significant simplifications. In this study, we present a hypothetical quantitative model for the assessment of human exposure to T. gondii through meat products. The model has been conceptualized to capture the dynamics leading to the presence of parasite in meat and, for illustrative purposes, used to estimate the probability of at least one viable cyst occurring in 100g of fresh pork meat in England. Available data, including the results of a serological survey in pigs raised in England were used as a starting point to implement a probabilistic model and assess the fate of the parasite along the food chain. Uncertainty distributions were included to describe and account for the lack of knowledge where necessary. To quantify the impact of the key model inputs, sensitivity and scenario analyses were performed. The overall probability of 100g of a hypothetical edible tissue containing at least 1 cyst was 5.54%. Sensitivity analysis indicated that the variables exerting the greater effect on the output mean were the number of cysts and number of bradyzoites per cyst. Under the best and the worst scenarios, the probability of a single portion of fresh pork meat containing at least 1 viable cyst resulted 1.14% and 9.97% indicating that the uncertainty and lack of data surrounding key input parameters of the model preclude accurate estimation of T. gondii exposure through consumption of meat products. The hypothetical model conceptualized here is coherent with current knowledge of the biology of the parasite. Simulation outputs clearly identify the key gaps in our knowledge of the host-parasite interaction that, when filled, will support quantitative assessments and much needed accurate estimates of the risk of human exposure.

Eimeria species occurrence varies between geographic regions and poultry production systems and may influence parasite genetic diversity.

Coccidiosis is one of the biggest challenges faced by the global poultry industry. Recent studies have highlighted the ubiquitous distribution of all Eimeria species which can cause this disease in chickens, but intriguingly revealed a regional divide in genetic diversity and population structure for at least one species, Eimeria tenella. The drivers associated with such distinct geographic variation are unclear, but may impact on the occurrence and extent of resistance to anticoccidial drugs and future subunit vaccines. India is one of the largest poultry producers in the world and includes a transition between E. tenella populations defined by high and low genetic diversity. The aim of this study was to identify risk factors associated with the prevalence of Eimeria species defined by high and low pathogenicity in northern and southern states of India, and seek to understand factors which vary between the regions as possible drivers for differential genetic variation. Faecal samples and data relating to farm characteristics and management were collected from 107 farms from northern India and 133 farms from southern India. Faecal samples were analysed using microscopy and PCR to identify Eimeria occurrence. Multiple correspondence analysis was applied to transform correlated putative risk factors into a smaller number of synthetic uncorrelated factors. Hierarchical cluster analysis was used to identify poultry farm typologies, revealing three distinct clusters in the studied regions. The association between clusters and presence of Eimeria species was assessed by logistic regression. The study found that large-scale broiler farms in the north were at greatest risk of harbouring any Eimeria species and a larger proportion of such farms were positive for E. necatrix, the most pathogenic species. Comparison revealed a more even distribution for E. tenella across production systems in south India, but with a lower overall occurrence. Such a polarised region- and system-specific distribution may contribute to the different levels of genetic diversity observed previously in India and may influence parasite population structure across much of Asia and Africa. The findings of the study can be used to prioritise target farms to launch and optimise appropriate anticoccidial strategies for long-term control.

Effect of enhanced biosecurity and selected on-farm factors on Campylobacter colonization of chicken broilers.

Human campylobacteriosis is the most commonly reported gastrointestinal bacterial infection in the EU; poultry meat has been identified as the main source of infection. We tested the hypothesis that enhanced biosecurity and other factors such as welfare status, breed, the practice of partial depopulation and number of empty days between flocks may prevent Campylobacter spp. caecal colonization of poultry batches at high levels (>123 000 c.f.u./g in pooled caecal samples). We analysed data from 2314 poultry batches sampled at slaughter in the UK in 2011-2013. We employed random-effects logistic regression to account for clustering of batches within farms and adjust for confounding. We estimated population attributable fractions using adjusted risk ratios. Enhanced biosecurity reduced the odds of colonization at partial depopulation [odds ratio (OR) 0·25, 95% confidence interval (CI) 0·14-0·47] and, to a lesser extent, at final depopulation (OR 0·47, 95% CI 0·25-0·89). An effect of the type of breed was also found. Under our assumptions, approximately 1/3 of highly colonized batches would be avoided if they were all raised under enhanced biosecurity or without partial depopulation. The results of the study indicate that on-farm measures can play an important role in reducing colonization of broiler chickens with Campylobacter spp. and as a result human exposure.

Risk factors for Taenia saginata cysticercus infection in cattle in the United Kingdom: A farm-level case-control study and assessment of the role of movement history, age and sex.

Bovine cysticercosis is caused by Taenia saginata cysticercus, the larval stage of the human tapeworm Taenia saginata. Recent European initiatives have highlighted the poor sensitivity of current surveillance for this parasite in cattle at slaughter; calling for more targeted, risk based and cost effective methods of T. saginata cysticercus detection. The aim of this study was to provide evidence that could inform such improved meat inspection activities in the United Kingdom (UK). The study included three components: (i) a farm-level case control study; (ii) the characterization of the network of movements of T. saginata cysticercus infected and non-infected animals, and an assessment of the strength of association between having passed through a farm that had previously originated an infected animal and the risk of infection; (iii) the assessment of the relationship between bovine age and gender and risk of infection. Abattoir records and cattle movement history data were used to identify farms of likely acquisition of infection (case farms) and a suitable control group. A questionnaire was used to gather farm-level characteristics and logistic regression was carried out to identify farm-level risk factors for the production of cattle found to be infected at slaughter. The case-control study provided evidence that farms situated close to a permanent potential source of human faecal contamination, and farms which used manure from animals other than cattle, were at higher risk of producing cattle later found to be infected with T. saginata cysticercus at slaughter. No other farm characteristics were identified as a risk factor for this. Analysis of the networks of animal movements showed that some individual farms played a key role as a source of T. saginata cysticercus infection; it was estimated that cattle with a history of being on a farm which previously appeared in the movement history of an infected animal were 4.27 times (P<0.001; 95% CI: 3.3-5.52) more likely to be diagnosed with T. saginata cysticercus infection at meat inspection. Male cattle aged 20 months or younger at the time of slaughter were found at lower risk of T. saginata cysticercus infection by comparison to other sex or age groups of cattle. These results, in combination with the consultation of experts and stakeholders, led to the conclusion that abattoir-based surveillance in low T. saginata cysticercus prevalence settings, such as Great Britain, could be made more targeted by stratifying cattle based on their individual movement history, sex and age characteristics.