Python farming as a flexible and efficient form of agricultural food security.

Diminishing natural resources and increasing climatic volatility are impacting agri-food systems, prompting the need for sustainable and resilient alternatives. Python farming is well established in Asia but has received little attention from mainstream agricultural scientists. We measured growth rates in two species of large pythons (Malayopython reticulatus and Python bivittatus) in farms in Thailand and Vietnam and conducted feeding experiments to examine production efficiencies. Pythons grew rapidly over a 12-month period, and females grew faster than males. Food intake and growth rates early in life were strong predictors of total lifetime growth, with daily mass increments ranging from 0.24 to 19.7 g/day for M. reticulatus and 0.24 to 42.6 g/day for P. bivittatus, depending on food intake. Pythons that fasted for up to 4.2 months lost an average of 0.004% of their body mass per day, and resumed rapid growth as soon as feeding recommenced. Mean food conversion rate for dressed carcasses was 4.1%, with useable products (dressed carcass, skin, fat, gall bladder) comprising 82% of the mass of live animals. In terms of food and protein conversion ratios, pythons outperform all mainstream agricultural species studied to date. The ability of fasting pythons to regulate metabolic processes and maintain body condition enhances food security in volatile environments, suggesting that python farming may offer a flexible and efficient response to global food insecurity.

A cross-sectional survey of risk factors for the presence of Coxiella burnetii in Australian commercial dairy goat farms.

The largest Australian farm-based outbreak of Q fever originated from a dairy goat herd. We surveyed commercial dairy goat farms across Australia by testing bulk tank milk (BTM) samples using a commercial indirect enzyme-linked immunosorbent assay and two quantitative polymerase chain reactions (PCRs). Of the 66 commercial dairy goat herds on record, managers from 61 herds were contacted and 49 provided BTM samples. Five of the surveyed herds were positive on at least one of the diagnostic tests, thus herd-level apparent prevalence was 10% (95% confidence interval [CI] 4 to 22). True prevalence was estimated to be 3% (95% credible interval: 0 to 18). Herd managers completed a questionnaire on herd management, biosecurity and hygiene practices and risk factors were investigated using multivariable logistic regression. Herds with >900 milking does (the upper quartile) were more likely to be Coxiella burnetii positive (odds ratio = 6.75; 95% CI 1.65 to 27.7) compared with farms with ≤900 milking does. The odds of BTM positivity increased by a factor of 2.53 (95% CI 1.51 to 4.22) for each order of magnitude increase in the number of goats per acre. C. burnetii was not detected in samples from the majority of the Australian dairy goat herds suggesting there is an opportunity to protect the industry and contain this disease with strengthened biosecurity practices. Intensification appeared associated with an increased risk of positivity. Further investigation is required to discriminate the practices associated with an increased risk of introduction to disease-free herds, from practices associated with maintenance of C. burnetii infection in infected dairy goat herds.

Diagnostic likelihood ratio - the next-generation of diagnostic test accuracy measurement.

To select, interpret, and assess the fitness-for-purpose of diagnostic tests, we need to compare the likelihoods of test results being true vs. false across both infected and non-infected individuals. Diagnostic sensitivity (DSe) and specificity (DSp) report the accuracy of classification in infected and non-infected individuals separately and do not compare these likelihoods directly. Positive and negative predictive values combine these likelihoods, but they also heavily depend on the prevalence in the tested populations and, therefore, cannot be generalised. We propose the adoption of the diagnostic likelihood ratio (LR), which balances the likelihoods of true vs. false results and is population independent. As a relative measure, LR ignores the absolute accuracy of tests, and two tests with different accuracy profiles may have the same LR. This can be easily mitigated by using listed complementary measures of accuracy, including DSe and DSp, or ancillary selection criteria. Overall, LR is a more relevant and universal measure of diagnostic test accuracy, which makes it the logical next-generation measure to adopt. We illustrate the applications and benefits of LR using three assays certified by the World Organisation for Animal Health as serological tests for bovine tuberculosis.

Afin de sélectionner, interpréter et évaluer l'aptitude à l'emploi de tests diagnostiques, nous devons comparer les probabilités de vrais vs faux résultats tant chez les individus infectés que chez les individus non infectés. La sensibilité diagnostique (DSe) et la spécificité diagnostique (DSp) correspondent à la capacité de classifier correctement les individus infectés ou non infectés séparément, sans toutefois comparer directement ces probabilités. Les valeurs prédictives positive et négative combinent ces probabilités mais sont fortement tributaires de la prévalence au sein de la population testée et par conséquent ne peuvent être généralisées. Les auteurs proposent d'adopter le ratio de vraisemblance diagnostique (likehood ratio : LR), qui compare les probabilités que les résultats diagnostiques soient vrais ou faux indépendamment de la population testeé. En tant que mesure relative, le LR ignore l'exactitude absolue d'un test, de sorte que deux tests présentant des profils d'exactitude différents peuvent avoir le même LR. Ces cas peuvent être résolus en faisant appel à d'autres mesures d'exactitude, y compris la DSe et la DSp, ou à des critères alternatifs. Globalement, le LR constitue une mesure plus pertinente et universelle, ce qui justifie son adoption comme la nouvelle génération de mesure pour l'exactitude diagnostique. Les auteurs illustrent les applications et les avantages du LR à travers l'exemple de trois tests validés par l'Organisation mondiale de la santé animale pour la sérologie de la tuberculose bovine.

Para seleccionar e interpretar pruebas de diagnóstico y valorar en qué medida cumplen su propósito debemos poder comparar la probabilidad de que los resultados que deparen sean verdaderos o falsos, y ello en individuos tanto infectados como no infectados. La sensibilidad y la especificidad de diagnóstico dan cuenta de la exactitud con que se pueden catalogar los individuos como infectados y no infectados separadamente, sin comparación directa entre estas dos probabilidades. Los valores predictivos positivos y negativos combinan ambas probabilidades, pero son muy dependientes de la prevalencia en la población analizada, por lo que no es posible generalizarlos. Los autores proponen que se adopte la razón de verosimilitudes (likelihood ratio: LR) del diagnóstico, que da cuenta de la probabilidad de obtener un resultado verdadero frente a la de obtener un resultado falso con independencia de la población de que se trate. Siendo un parámetro relativo, la LR es ajena a la exactitud absoluta de la prueba. Puede ocurrir por lo tanto que dos pruebas con distintas características de exactitud presenten la misma LR, extremo que se puede paliar fácilmente empleando una lista de medidas complementarias de la exactitud, entre ellas la DSe y la DSp, o criterios de selección auxiliares. Globalmente, la LR ofrece una medida más pertinente y universal de la exactitud de una prueba de diagnóstico, con lo que es lógico que sea adoptada como parámetro de próxima generación. Los autores ilustran las aplicaciones y ventajas de la LR aplicándola a tres ensayos aprobados por la Organización Mundial de Sanidad Animal como pruebas serológicas de detección de la tuberculosis bovina.

Introduction - Validation of tests for OIE-listed diseases as fit-for-purpose in a world of evolving diagnostic technologies.

The World Organisation for Animal Health (OIE) has made leading contributions to the discipline of test validation science by providing standards and guidelines that inform the test validation process in terrestrial and aquatic animals. The OIE Manual of Diagnostic Tests and Vaccines for Terrestrial Animals, and the Manual of Diagnostic Tests for Aquatic Animals describe the test validation pathway in the context of fitness for purpose, elaborate on the importance of diagnostic sensitivity (DSe) and specificity (DSp) as measures of test accuracy, and designate additional factors (e.g. test cost, laboratory throughput capacity and rapidity of test results) that influence choices of a single test over others or the inclusion of a new test in a diagnostic process that includes multiple tests. This paper provides examples of each of the six main testing purposes listed in the Terrestrial Manual and describes additional metrics such as ruggedness and robustness that should be included in the validation of point-of-care tests. Challenges associated with new diagnostic technologies and platforms are described. Validated tests with estimates of DSe and DSp are needed to measure confidence in test results for OIE-listed diseases, to facilitate risk assessments related to animal movement, to estimate true prevalence, and for certification of disease freedom and use in epidemiological (risk factor) studies.

L'Organisation mondiale de la santé animale (OIE) a apporté d'importantes contributions dans le domaine de la validation des tests en élaborant des normes et des lignes directrices qui informent sur le processus de validation des tests chez les animaux terrestres et aquatiques. Le Manuel des tests de diagnostic et des vaccins pour les animaux terrestres et le Manuel des tests de diagnostic pour les animaux aquatiques de l'OIE décrivent le processus de validation des tests dans le contexte de leur aptitude à l'emploi, expliquent l'importance de la sensibilité (DSe) et de la spécificité (DSp) diagnostiques pour mesurer l'exactitude des tests, et désignent d'autres facteurs (ex. coût des tests, capacité de traitement des laboratoires et rapidité d'obtention des résultats des tests) qui influencent le choix d'un test par rapport à un autre ou l'inclusion d'un nouveau test dans un processus de diagnostic composé de multiples tests. Le présent article fournit des exemples pour chacun des six principaux objectifs définis pour les tests figurant dans le Manuel terrestre et décrit des mesures supplémentaires, telle la robustesse (aussi bien interne qu'externe), qu'il conviendrait d'inclure dans la validation des tests au point d'intervention. Il aborde également les défis soulevés par les nouvelles technologies et plateformes de diagnostic. Des tests validés accompagnés d'estimations de la DSe et de la DSp sont nécessaires pour mesurer la fiabilité des résultats des tests pour les maladies listées par l'OIE, faciliter les évaluations des risques associés aux mouvements des animaux, estimer le véritable taux de prévalence et certifier l'absence de maladies ; ils sont également indispensables pour les études (des facteurs de risque) épidémiologiques.

La Organización Mundial de Sanidad Animal (OIE), con su labor de elaboración de normas y directrices que fundamentan el proceso de validación de pruebas para enfermedades de los animales terrestres y acuáticos, ha hecho aportaciones punteras a la disciplina científica que se ocupa de la validación de pruebas. En su Manual de las Pruebas de Diagnóstico y de las Vacunas para los Animales Terrestres y su Manual de las Pruebas de Diagnóstico para los Animales Acuáticos, la OIE describe el procedimiento de validación de pruebas en clave de idoneidad para determinados propósitos, ahonda en la importancia de la sensibilidad y la especificidad diagnósticas (DSe y DSp) como medidas de la exactitud de una prueba y señala otros factores (como el costo de la prueba, la productividad del laboratorio o la rapidez de los resultados) que también influyen en la elección de una determinada prueba por delante de otras o en la inclusión de una nueva prueba en un proceso de diagnóstico que entraña el uso de varias. Los autores ofrecen ejemplos de cada uno de los seis principales propósitos con las que puede utilizarse una prueba, según vienen enunciados en el Manual Terrestre, y describen otros parámetros que es preciso tener en cuenta a la hora de validar pruebas practicadas en el punto de consulta, como la robustez o también la solidez (ruggedness en inglés; llamada a veces «robustez interlaboratorios¼). También describen las dificultades ligadas a nuevas tecnologías y plataformas de diagnóstico. Se necesitan pruebas validadas y acompañadas de un cálculo de la DSe y la DSp para fines tan diversos e importantes como medir la confianza que merecen los resultados de pruebas para enfermedades inscritas en las listas de la OIE, facilitar la evaluación del riesgo ligado al desplazamiento de animales, estimar la prevalencia real, certificar la ausencia de enfermedad o realizar estudios epidemiológicos (factores de riesgo).

Impacts of major health conditions affecting the Australian sheepmeat value chain: a review.

Major health conditions in sheep contribute to substantial economic losses throughout the sheepmeat supply chain in Australia. A systematic review was undertaken to explore the measurable impact of six conditions: arthritis, sheep measles, pleurisy, pneumonia, grass seeds and rib fractures, on the production of lamb and mutton across the meat value chain. Peer-reviewed scientific literature from three databases and non-peer-reviewed articles and reports from Australian government and non-government websites were searched between 11 and 17 November 2019. Original articles, including studies conducted in Australia and New Zealand, that had measurable impacts on conditions of interest were included. The search yielded 16 articles and reports and were classified as producer impact and/or processor impact studies. Mortalities were quantified for pneumonia and arthritis, with pneumonia having the highest impact for producers. Grass seed infestation resulted in the highest impact on carcase and liveweight losses compared to arthritis and pneumonia. Arthritis had the highest trim weight losses for both lamb and mutton and the highest rate of carcase condemnation. Grass seed was the only condition where other impacts on the processor (chain speed and staff relocation to the boning room) were quantified. Although quantifiable production and processing losses were available for some conditions, this review has highlighted that limited quantifiable data based on scientifically sound research were not available for other conditions. The evidence for some conditions found in this review can be used to target future research activities and to further assist producers in making informed management decisions on prevention and control.

No Evidence of Toxoplasma Gondii Exposure in South Australian Koalas (Phascolarctos cinereus).

Infection with the cat-borne parasite Toxoplasma gondii has been detected in numerous Australian marsupials and can lead to severe disease (toxoplasmosis) in some cases. The seroprevalence of Toxoplasma on Kangaroo Island, South Australia has been reported to be higher than the South Australian mainland in macropods, cats, and sheep, suggesting an increased risk of infection on this island. However, Toxoplasma seroprevalence in small- and medium-sized terrestrial mammals was almost zero on the island and did not differ from that on the mainland. We surveyed Toxoplasma seroprevalence in koala (Phascolarctos cinereus) populations on the island and on the mainland and assessed their risk of infection and their role in the life cycle of Toxoplasma. All screened koalas from the island (n = 94) and the mainland (n = 63) were seronegative. This represents the largest Toxoplasma seroprevalence survey in this species and provided sufficient evidence to confidently demonstrate freedom from parasite exposure in both island and mainland populations at the time of the survey. Because koalas are extensively arboreal and predominately consume tree foliage, they appear to be at negligible risk of Toxoplasma infection. Furthermore, as koalas are rarely consumed by cats, we suggest that they have a minor role in the parasite's life cycle.

Random and systematic sampling error when hooking fish to monitor skin fluke (Benedenia seriolae) and gill fluke (Zeuxapta seriolae) burden in Australian farmed yellowtail kingfish (Seriola lalandi).

The Australian farmed yellowtail kingfish (Seriola lalandi, YTK) industry monitor skin fluke (Benedenia seriolae) and gill fluke (Zeuxapta seriolae) burden by pooling the fluke count of 10 hooked YTK. The random and systematic error of this sampling strategy was evaluated to assess potential impact on treatment decisions. Fluke abundance (fluke count per fish) in a study cage (estimated 30,502 fish) was assessed five times using the current sampling protocol and its repeatability was estimated the repeatability coefficient (CR) and the coefficient of variation (CV). Individual body weight, fork length, fluke abundance, prevalence, intensity (fluke count per infested fish) and density (fluke count per Kg of fish) were compared between 100 hooked and 100 seined YTK (assumed representative of the entire population) to estimate potential selection bias. Depending on the fluke species and age category, CR (expected difference in parasite count between 2 sampling iterations) ranged from 0.78 to 114 flukes per fish. Capturing YTK by hooking increased the selection of fish of a weight and length in the lowest 5th percentile of the cage (RR = 5.75, 95% CI: 2.06-16.03, P-value = 0.0001). These lower end YTK had on average an extra 31 juveniles and 6 adults Z. seriolae per Kg of fish and an extra 3 juvenile and 0.4 adult B. seriolae per Kg of fish, compared to the rest of the cage population (P-value < 0.05). Hooking YTK on the edge of the study cage biases sampling towards the smallest and most heavily infested fish in the population, resulting in poor repeatability (more variability amongst sampled fish) and an overestimation of parasite burden in the population. In this particular commercial situation these finding supported that health management program, where the finding of an underestimation of parasite burden could provide a production impact on the study population. In instances where fish populations and parasite burdens are more homogenous, sampling error may be less severe. Sampling error when capturing fish from sea cage is difficult to predict. The amplitude and direction of this error should be investigated for a given cultured fish species across a range of parasite burden and fish profile scenarios.

Cross-sectional observational survey of serum biochemistry values in a population of 69 adult female alpacas (Vicugna pacos) in South Australia.

Blood samples were collected from 69 'healthy' female alpacas aged ≥12 months from 11 properties in South Australia. The 10-90 percentile ranges of the 16/19 analytes measured in this sample population were within the published ranges of four healthy alpaca populations from other geographic locations. Marginal exceptions were glutamate dehydrogenase and bicarbonate. Potassium was notably elevated, probably because of haemolysis of some samples. The sample size was insufficient to provide the appropriate statistical power to define diagnostic references ranges according to international standards. The health status of the sample population of alpacas was presumptive based on a physical examination.

Identification of periparturient mare and foal associated predictors of post parturient immunoglobulin A concentrations in Thoroughbred foals.

REASONS FOR PERFORMING THE STUDY: Prior to the start of endogenous production of immunoglobulins (Igs), absorption of maternal Igs is important to protect against pathogens in the early neonatal period. It is possible that mare- or foal-associated factors may influence neonatal IgA concentrations. OBJECTIVES: The temporal relationships among serum and milk IgA concentrations in Thoroughbred mare-foal pairs were explored to determine if periparturient mare- and foal-associated factors contribute to the prediction of foal serum IgA concentrations. METHODS: Blood and milk samples as well as complete veterinary records, were collected for 84 Thoroughbred mare-foal pairs from one month before to 2 months after parturition. Samples were tested using enzyme-linked immunosorbent assay (ELISA) for concentrations of IgA. Pairwise correlation coefficients were estimated (P < 0.01) and simple linear regression used to investigate unconditional associations between mare IgA levels, mare and foal risk factors and foal serum IgA concentration at 12 h. Backwards, stepwise elimination of nonsignificant factors was used to create a final model. RESULTS: There were significant temporal relationships among mare serum IgA and among colostrum and milk IgA concentrations within mares (P < 0.01). Mare serum IgA concentrations up to one month before parturition were associated with foal serum IgA concentrations at all time points and with colostrum and milk IgA concentrations. Mare serum IgA at -28 days and parity were associated with foal serum IgA concentration at 12 h (P < 0.001). CONCLUSIONS: Mare serum IgA concentrations up to 28 days before parturition, together with mare parity, are indicative of neonatal foal serum IgA concentrations. POTENTIAL RELEVANCE: Mare serum and colostrum IgA concentrations may be useful peripartum predictors of neonatal mucosal immune status, enabling earlier intervention to prevent the consequences of mucosal infections.

Lexicon of disease spread modelling terms.

Over the past decade there has been a notable increase in the magnitude and variety of modelling work in the realm of animal health. Similarly, there has been an increase in the extent to which modelling is used as a component in the development of animal health policy. The increased dependency on modelling creates a need to enhance understanding and linkages between policy-makers (those that pose the policy or scientific questions, commission modelling work and use model outputs in the development of policy), intermediaries (those that are responsible for working with modellers and communicating model results to policy-makers), and modellers. Development of a lexicon of disease spread modelling terms can help support clear communication and collaboration between all players.