Perspectives and challenges in validating new diagnostic technologies.

This paper focuses on several new diagnostic technologies, which are set to dominate the testing landscape in the near future and have applications in animal health diagnostics, namely: next-generation sequencing, assays to detect biomarkers, and point-of-care tests. An example of real-time loop-mediated isothermal amplification validation is also provided. Validating these new technologies presents several challenges, which are addressed in this paper.

Les auteurs s'intéressent à plusieurs nouvelles technologies de diagnostic appelées à occuper, dans un futur proche, une place de choix dans le paysage du dépistage et dont il existe déjà des applications en santé animale, à savoir : le séquençage de nouvelle génération, la détection de biomarqueurs et les tests utilisables sur le lieu des soins. Ils décrivent par ailleurs l'exemple de la validation d'une amplification isotherme à médiation par boucle en temps réel. La validation de ces nouvelles technologies présente un certain nombre de difficultés, que les auteurs examinent en détail.

Los autores se centran en varias tecnologías de nuevo cuño que están llamadas a dominar el panorama de las pruebas de diagnóstico en un futuro próximo y que tienen aplicaciones de diagnóstico en sanidad animal, a saber: la secuenciación de próxima generación, los ensayos de detección de marcadores biológicos y las pruebas practicadas en el lugar de consulta. También ofrecen un ejemplo de validación de una técnica de amplificación isotérmica mediada por bucles en tiempo real. La validación de estas nuevas tecnologías presenta varias dificultades, que los autores examinan en estas líneas.

Bayesian latent class analysis when the reference test is imperfect.

Latent class analysis (LCA) has allowed epidemiologists to overcome the practical constraints faced by traditional diagnostic test evaluation methods, which require both a gold standard diagnostic test and ample numbers of appropriate reference samples. Over the past four decades, LCA methods have expanded to allow epidemiologists to evaluate diagnostic tests and estimate true prevalence using imperfect tests over a variety of complex data structures and scenarios, including during the emergence of novel infectious diseases. The objective of this review is to provide an overview of recent developments in LCA methods, as well as a practical guide to applying Bayesian LCA (BLCA) to the evaluation of diagnostic tests. Before conducting a BLCA, the suitability of BLCA for the pathogen of interest, the availability of appropriate samples, the number of diagnostic tests, and the structure of the data should be carefully considered. While formulating the model, the model's structure and specification of informative priors will affect the likelihood that useful inferences can be drawn. With the growing need for advanced analytical methods to evaluate diagnostic tests for newly emerging diseases, LCA is a promising field of research for both the veterinary and medical disciplines.

L'analyse à classes latentes a permis aux épidémiologistes de surmonter les problèmes concrets posés par les méthodes traditionnelles d'évaluation des essais de diagnostic, qui nécessitent à la fois un test de référence absolue (étalon ou gold standard) et un grand nombre d'échantillons de référence aux caractéristiques appropriées. Au cours des quatre dernières décennies, les méthodes d'analyse à classes latentes ont acquis de l'ampleur et permettent aux épidémiologistes d'évaluer les essais diagnostiques et d'estimer les taux de prévalence réelle tout en recourant à des tests supposés imparfaits, grâce à l'utilisation de données et de scénarios divers et complexes, y compris dans les situations d'émergence de nouvelles maladies infectieuses. Les auteurs font un tour d'horizon des dernières évolutions dans ce domaine et donnent des orientations pratiques concernant la manière d'utiliser l'analyse bayésienne à classes latentes pour évaluer les performances d'un test de diagnostic. Avant de conduire une telle analyse, il convient de déterminer avec soin si elle est adaptée à l'agent pathogène considéré et si les échantillons disponibles sont appropriés et en nombre suffisant ; il convient également de prendre en compte le nombre de tests de diagnostic à évaluer et la structure des données utilisées. Lors de la conception du modèle, sa structure et la définition préalable des données informatives vont affecter la probabilité que le modèle génère des inférences utiles. Face à la nécessité croissante de disposer de méthodes analytiques sophistiquées pour évaluer les tests de diagnostic utilisés pour les maladies émergentes nouvelles, les analyses à classes latentes offrent des perspectives prometteuses pour la recherche, aussi bien dans le domaine de la santé vétérinaire que de la médecine humaine.

El análisis de clases latentes ha servido a los epidemiólogos para superar las limitaciones prácticas que imponen los métodos tradicionales de evaluación de pruebas de diagnóstico, que requieren a la vez una prueba de diagnóstico que sirva de patrón de referencia perfecto y un gran número de muestras de referencia adecuadas. En los últimos cuatro decenios, los métodos de análisis de clases latentes se han ido ampliando hasta permitir a los epidemiólogos evaluar pruebas de diagnóstico y calcular la prevalencia real empleando pruebas imperfectas ante muy diversas estructuras de datos y situaciones complejas, incluida la aparición de nuevas enfermedades infecciosas. Los autores, tras presentar a grandes líneas los últimos adelantos en cuanto a métodos de análisis de clases latentes, ofrecen indicaciones prácticas para aplicar el análisis bayesiano de clases latentes a la evaluación de pruebas de diagnóstico. Antes de proceder a un análisis bayesiano de este tipo conviene estudiar con detenimiento la idoneidad del método para el patógeno en cuestión, la disponibilidad de muestras apropiadas, el número de pruebas de diagnóstico y la estructura de los datos. A la hora de formular el modelo, la estructura del propio modelo y la especificación de los elementos informativos previos influirán en la probabilidad de poder extraer conclusiones provechosas. Ante la creciente necesidad de disponer de métodos analíticos avanzados con los que evaluar pruebas de diagnóstico de nuevas enfermedades emergentes, el análisis de clases latentes abre un promisorio campo de investigación para las disciplinas veterinarias y médicas.

Efficacy of a high potency O1 Manisa monovalent vaccine against heterologous challenge with foot-and-mouth disease virus of O/SEA/Mya-98 lineage in sheep.

Potency tests for commercial oil-adjuvanted foot-and-mouth disease (FMD) vaccines are usually carried out in cattle, using a full dose (2 ml) of vaccine and homologous virus challenge. However, in sheep the recommended vaccine dose is half of the cattle dose (1 ml) and most vaccines have not been potency tested for this species, especially with heterologous viruses. To determine the efficacy of a high potency (>6PD50) FMD virus (FMDV) O1Manisa vaccine in sheep, we carried out a study using a heterologous FMDV (FMDV O/SKR/2010 - Mya-98 strain) challenge. Groups of seven animals each were vaccinated with 2×, 1×, 1/2× or 1/4× dose (2 ml, 1 ml, 0.5 ml or 0.25 ml respectively) and challenged at 7 days post vaccination (dpv). Only 3 of the 7 sheep in the group vaccinated with 2 ml were protected. With 2 additional groups, receiving double or single doses and challenged at 14 dpv, 4 of 7 sheep were protected in each group. None of the sheep had measurable neutralising antibodies against the vaccine or challenge virus at 7 dpv. However, all vaccinated animals challenged at 14 dpv had a homologous neutralising response against FMDV O1 Manisa on the day of challenge and all but one animal also had a heterologous response to FMDV O/SKR/2010. Infectious FMDV and viral RNA could be found in nasal swabs between 1 and 6 days post challenge (dpc) in most vaccinated sheep, but those vaccinated with higher doses or challenged at 14 dpv showed significant decreases in the level of FMDV detection. Intermittent virus shedding was noticed between 1 and 35 dpc in all vaccinated groups, but persistent infection could be demonstrated only in 4 sheep (20%). This study showed that at the recommended dose, a high potency (>6 PD50) FMDV O1Manisa vaccine does not protect sheep against a heterologous challenge at 7 dpv. However, partial protection was observed when a double dose was used at 7 dpv or when double or single dose vaccinated sheep were challenged at 14 dpv.

Collection of Oral Fluids Using Cotton Ropes as a Sampling Method to Detect Foot-and-Mouth Disease Virus Infection in Pigs.

In high-density farming practices, it is important to constantly monitor for infectious diseases, especially diseases that have the potential to spread rapidly between holdings. Pigs are known to amplify foot-and-mouth disease (FMD) by excreting large amounts of virus, and it is therefore important to detect the virus quickly and accurately to minimize the spread of disease. Ropes were used to collect oral fluid samples from pigs, and each sample was compared to saliva samples collected from individual animals by detecting FMD virus RNA using real-time PCR. Two different experiments are described where groups of pigs were infected with different serotypes of FMD virus, either with or without vaccination, and unvaccinated pigs were kept in aerosol contact. The sensitivity of the rope sampling varied between 0.67 and 0.92, and the statistical agreement between this method and individual sampling ranged from substantial to moderate for the two different serotypes. The ease of collecting oral fluids using ropes together with the high sensitivity of subsequent FMD detection through PCR indicates that this could be a useful method to monitor pig populations for FMD virus infection. With further validation of the sensitivity of detection of FMD virus RNA, this can be a cost-effective, non-invasive diagnostic tool.