31 research outputs found

    Standardization of canine meningioma grading: Validation of new guidelines for reproducible histopathologic criteria.

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    Canine meningiomas are currently graded using the human grading system. Recently published guidelines have adapted the human grading system for use in dogs. The goal of this study was to validate the new guidelines for canine meningiomas. To evaluate the inter-observer agreement, 5 veterinary surgical pathologists graded 158 canine meningiomas following the human grading system alone or with the new guidelines. The inter-observer agreement for histologic grade and each of the grading criteria (mitotic grade, invasion, spontaneous necrosis, macronucleoli, small cells, hypercellularity, pattern loss and anaplasia) was evaluated using the Fleiss kappa index. The diagnostic accuracy (sensitivity and specificity) was assessed by comparing the diagnoses obtained with the 2 grading systems with a consensus grade (considered the reference classification). The consensus histologic grade was obtained by agreement between 4 experienced veterinary neuropathologists following the guidelines. Compared with the human grading alone, the canine-specific guidelines increased the inter-observer agreement for: histologic grade (Îș = 0.52); invasion (Îș = 0.67); necrosis (Îș = 0.62); small cells (Îș = 0.36); pattern loss (Îș = 0.49) and anaplasia (Îș = 0.55). Mitotic grade agreement remained substantial (Îș = 0.63). The guidelines improved the sensitivity in identifying grade 1 (95.6%) and the specificity in identifying grade 2 (96.2%) meningiomas. In conclusion, the new grading guidelines for canine meningiomas are associated with an overall improvement in the inter-observer agreement and higher diagnostic accuracy in diagnosing grade 1 and grade 2 meningiomas

    Standardization of canine meningioma grading: Validation of new guidelines for reproducible histopathologic criteria

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    Canine meningiomas are currently graded using the human grading system. Recently published guidelines have adapted the human grading system for use in dogs. The goal of this study was to validate the new guidelines for canine meningiomas. To evaluate the inter‐observer agreement, 5 veterinary surgical pathologists graded 158 canine meningiomas following the human grading system alone or with the new guidelines. The inter‐observer agreement for histologic grade and each of the grading criteria (mitotic grade, invasion, spontaneous necrosis, macronucleoli, small cells, hypercellularity, pattern loss and anaplasia) was evaluated using the Fleiss kappa index. The diagnostic accuracy (sensitivity and specificity) was assessed by comparing the diagnoses obtained with the 2 grading systems with a consensus grade (considered the reference classification). The consensus histologic grade was obtained by agreement between 4 experienced veterinary neuropathologists following the guidelines. Compared with the human grading alone, the canine‐specific guidelines increased the inter‐observer agreement for: histologic grade (Îș = 0.52); invasion (Îș = 0.67); necrosis (Îș = 0.62); small cells (Îș = 0.36); pattern loss (Îș = 0.49) and anaplasia (Îș = 0.55). Mitotic grade agreement remained substantial (Îș = 0.63). The guidelines improved the sensitivity in identifying grade 1 (95.6%) and the specificity in identifying grade 2 (96.2%) meningiomas. In conclusion, the new grading guidelines for canine meningiomas are associated with an overall improvement in the inter‐observer agreement and higher diagnostic accuracy in diagnosing grade 1 and grade 2 meningiomas

    Evaluation using latent class models of the diagnostic performances of three ELISA tests commercialized for the serological diagnosis of <i>Coxiella burnetii</i> infection in domestic ruminants

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    International audienceELISA methods are the diagnostic tools recommended for the serological diagnosis of Coxiella burnetii infection in ruminants but their respective diagnostic performances are difficult to assess because of the absence of a gold standard. This study focused on three commercial ELISA tests with the following objectives (1) assess their sensitivity and specificity in sheep, goats and cattle, (2) assess the between-and within-herd seroprevalence distribution in these species, accounting for diagnostic errors, and (3) estimate optimal sample sizes considering sensitivity and specificity at herd level. We comparatively tested 1413 cattle, 1474 goat and 1432 sheep serum samples collected in France. We analyzed the cross-classified test results with a hierarchical zero-inflated beta-binomial latent class model considering each herd as a population and conditional dependence as a fixed effect. Potential biases and coverage probabilities of the model were assessed by simulation. Conditional dependence for truly seropositive animals was high in all species for two of the three ELISA methods. Specificity estimates were high, ranging from 94.8% [92.1; 97.8] to 99.2% [98.5; 99.7], whereas sensitivity estimates were generally low, ranging from 39.3 [30.7; 47.0] to 90.5% [83.3; 93.8]. Betweenand within-herd seroprevalence estimates varied greatly among geographic areas and herds. Overall, goats showed higher within-herd seroprevalence levels than sheep and cattle. The optimal sample size maximizing both herd sensitivity and herd specificity varied from 3 to at least 20 animals depending on the test and ruminant species. This study provides better interpretation of three widely used commercial ELISA tests and will make it possible to optimize their implementation in future studies. The methodology developed may likewise be applied to other human or animal diseases

    Review state-of-the-art of output-based methodological approaches for substantiating freedom from infection

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    A wide variety of control and surveillance programmes that are designed and implemented based on country-specific conditions exists for infectious cattle diseases that are not regulated. This heterogeneity renders difficult the comparison of probabilities of freedom from infection estimated from collected surveillance data. The objectives of this review were to outline the methodological and epidemiological considerations for the estimation of probabilities of freedom from infection from surveillance information and review state-of-the-art methods estimating the probabilities of freedom from infection from heterogeneous surveillance data. Substantiating freedom from infection consists in quantifying the evidence of absence from the absence of evidence. The quantification usually consists in estimating the probability of observing no positive test result, in a given sample, assuming that the infection is present at a chosen (low) prevalence, called the design prevalence. The usual surveillance outputs are the sensitivity of surveillance and the probability of freedom from infection. A variety of factors influencing the choice of a method are presented; disease prevalence context, performance of the tests used, risk factors of infection, structure of the surveillance programme and frequency of testing. The existing methods for estimating the probability of freedom from infection are scenario trees, Bayesian belief networks, simulation methods, Bayesian prevalence estimation methods and the STOC free model. Scenario trees analysis is the current reference method for proving freedom from infection and is widely used in countries that claim freedom. Bayesian belief networks and simulation methods are considered extensions of scenario trees. They can be applied to more complex surveillance schemes and represent complex infection dynamics. Bayesian prevalence estimation methods and the STOC free model allow freedom from infection estimation at the herd-level from longitudinal surveillance data, considering risk factor information and the structure of the population. Comparison of surveillance outputs from heterogeneous surveillance programmes for estimating the probability of freedom from infection is a difficult task. This paper is a ‘guide towards substantiating freedom from infection’ that describes both all assumptions-limitations and available methods that can be applied in different settings

    Évaluation et prise en compte de l’incertitude diagnostique des tests utilisĂ©s pour le dĂ©pistage sĂ©rologique des infections par Coxiella burnetii chez les ruminants domestiques

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    Q fever is a zoonotic disease, caused by the bacterium Coxiella burnetii. Most of human clinical cases are related to an exposition to domestic ruminants. Because domestic ruminants may be latently infected or intermittently shed the bacterium, serological methods such as ELISA are recommended by the OIE for the detection of past or present infections by C. burnetii. However, no gold standard method is available to assess with certainty the serological status of an animal. To date, three ELISA tests (later referred to as test 1, 2 and 3) are commercialized in Europe but their diagnostic performances are not well known. The thesis manuscript is divided into three parts, with the objectives: (1) to assess the diagnostic performances of the three ELISA tests commercialized for the serological diagnosis of C. burnetii infection in cattle, sheep and goats; (2) to assess true seroprevalence levels in these three domestic ruminant species based on test 2 while accounting for the diagnostic uncertainty of this test; (3) to develop an online tool to help stakeholders interpreting the results of a serological screening plan based on the results obtained in parts 1 and 2.This work is based on data collected for the Q fever surveillance program performed between 2012 and 2014 in 10 French departments. The database includes serological results from 9,972 cattle, 5,024 goats and 7,632 sheep sampled from 1,602 herds randomly selected. All samples were analyzed with test 2 and approximately 20% (n= 4,319) were also analyzed with tests 1, 2 and 3 at the French national reference laboratory for Q fever.Diagnostic performances of the three ELISA tests were assessed using a latent class model accounting for the diagnostic accuracy between the three tests. Diagnostic uncertainty values estimated for test 2 were used to model the distribution of the proportion of true seropositive herds in each department (within-herd seroprevalence) and the proportion of true seropositive animals in seropositive herds (within-herd seroprevalence) for each ruminant species. Finally, a freely accessible Shiny application was designed so that stakeholders may assess the probability that an animal tested or a herd screened is truly seropositive given the herd’s characteristics, the epidemiological context and the results of the screening plan performed. This work allows better interpreting ELISA results obtained as part of a Q fever targeted screening plan or surveillance program at the scale of herds, regions or even countries. It provides first answers to the mandatory requirements related to the recent application of the EU 2018/1882 regulation, which classifies Q fever as a category E disease with a need for surveillance.La fiĂšvre Q est une maladie zoonotique causĂ©e par la bactĂ©rie Coxiella burnetii. La plupart des cas cliniques humains recensĂ©s sont liĂ©s Ă  une exposition Ă  des ruminants domestiques excrĂ©teurs de la bactĂ©rie. Chez les ruminants domestiques, en raison de la prĂ©sence de porteurs latents et de l’excrĂ©tion intermittente de la bactĂ©rie, les tests sĂ©rologiques de type ELISA sont recommandĂ©s par l’OIE pour tĂ©moigner d’infections passĂ©es ou en cours. Cependant, il n’existe pas de mĂ©thode gold standard permettant de dĂ©terminer avec certitude le statut sĂ©rologique des individus. À ce jour, trois tests ELISA (ci-aprĂšs nommĂ©s test 1, 2, 3) sont commercialisĂ©s en Europe, mais leurs performances diagnostiques sont mal connues. La thĂšse est divisĂ©e en trois parties avec respectivement pour objectifs : (1) d’estimer les performances diagnostiques chez les bovins, ovins et caprins des trois tests ELISA commercialisĂ©s en Europe pour le diagnostic sĂ©rologique des infections par C. burnetii ; (2) d’estimer les sĂ©roprĂ©valences rĂ©elles des infections par C. burnetii chez ces trois espĂšces de ruminants domestiques sur la base du test 2 en prenant en compte son incertitude diagnostique ; (3) de construire un outil en ligne d’aide Ă  l’interprĂ©tation des plans de dĂ©pistage sĂ©rologique en intĂ©grant les estimations rĂ©alisĂ©es dans les parties 1 et 2. Les travaux s’appuient sur les donnĂ©es collectĂ©es dans le cadre du dispositif de surveillance de la fiĂšvre Q mis en place entre 2012 et 2014 dans dix dĂ©partements français. La base de donnĂ©es comprend 9 972 bovins, 5 024 caprins et 7 632 ovins Ă©chantillonnĂ©s dans 1 602 Ă©levages sĂ©lectionnĂ©s de façon alĂ©atoire. Tous les Ă©chantillons de sĂ©rum ont Ă©tĂ© analysĂ©s avec le test 2 par un panel de laboratoires d’analyses vĂ©tĂ©rinaires et environ 20 % (n= 4 319) ont Ă©galement Ă©tĂ© analysĂ©s avec les tests 1, 2 et 3 au laboratoire national de rĂ©fĂ©rence de la fiĂšvre Q. Les performances diagnostiques des trois tests ELISA pour chaque espĂšce de ruminant ont Ă©tĂ© estimĂ©es Ă  l’aide d’un modĂšle Ă  classes latentes prenant en compte la dĂ©pendance conditionnelle entre les trois tests. L’incertitude diagnostique estimĂ©e pour le test 2 a permis d’étudier la distribution de la proportion d’élevages sĂ©ropositifs selon les dĂ©partements (sĂ©roprĂ©valence inter-Ă©levage) et la proportion d’animaux sĂ©ropositifs selon les Ă©levages (sĂ©roprĂ©valence intra-Ă©levage) pour chacune des espĂšces. Enfin, une application Shiny libre d’accĂšs Ă  destination des acteurs de terrain a Ă©tĂ© dĂ©veloppĂ©e pour permettre d’estimer la probabilitĂ© que l’individu testĂ© ou le troupeau dĂ©pistĂ© soit rĂ©ellement sĂ©ropositif sachant les caractĂ©ristiques de l’élevage, le contexte Ă©pidĂ©miologique et les rĂ©sultats du plan de dĂ©pistage rĂ©alisĂ©. L’ensemble de ces travaux permet de mieux interprĂ©ter les rĂ©sultats obtenus avec ces tests ELISA dans le cadre d’un dĂ©pistage ciblĂ© ou d’un programme de surveillance de la fiĂšvre Q Ă  l’échelle d’élevages, de rĂ©gions, voire de pays. Ils proposent donc des Ă©lĂ©ments de rĂ©ponses aux exigences rĂ©glementaires rĂ©cemment mises en application dans le cadre du RĂšglement (UE) 2018/1882 et catĂ©gorisant la fiĂšvre Q comme une maladie de catĂ©gorie E Ă  surveillance obligatoire

    Evaluation and consideration of the diagnostic uncertainty of tests used for the serological screening of Coxiella burnetii infections in domestic ruminants

    No full text
    La fiĂšvre Q est une maladie zoonotique causĂ©e par la bactĂ©rie Coxiella burnetii. La plupart des cas cliniques humains recensĂ©s sont liĂ©s Ă  une exposition Ă  des ruminants domestiques excrĂ©teurs de la bactĂ©rie. Chez les ruminants domestiques, en raison de la prĂ©sence de porteurs latents et de l’excrĂ©tion intermittente de la bactĂ©rie, les tests sĂ©rologiques de type ELISA sont recommandĂ©s par l’OIE pour tĂ©moigner d’infections passĂ©es ou en cours. Cependant, il n’existe pas de mĂ©thode gold standard permettant de dĂ©terminer avec certitude le statut sĂ©rologique des individus. À ce jour, trois tests ELISA (ci-aprĂšs nommĂ©s test 1, 2, 3) sont commercialisĂ©s en Europe, mais leurs performances diagnostiques sont mal connues. La thĂšse est divisĂ©e en trois parties avec respectivement pour objectifs : (1) d’estimer les performances diagnostiques chez les bovins, ovins et caprins des trois tests ELISA commercialisĂ©s en Europe pour le diagnostic sĂ©rologique des infections par C. burnetii ; (2) d’estimer les sĂ©roprĂ©valences rĂ©elles des infections par C. burnetii chez ces trois espĂšces de ruminants domestiques sur la base du test 2 en prenant en compte son incertitude diagnostique ; (3) de construire un outil en ligne d’aide Ă  l’interprĂ©tation des plans de dĂ©pistage sĂ©rologique en intĂ©grant les estimations rĂ©alisĂ©es dans les parties 1 et 2. Les travaux s’appuient sur les donnĂ©es collectĂ©es dans le cadre du dispositif de surveillance de la fiĂšvre Q mis en place entre 2012 et 2014 dans dix dĂ©partements français. La base de donnĂ©es comprend 9 972 bovins, 5 024 caprins et 7 632 ovins Ă©chantillonnĂ©s dans 1 602 Ă©levages sĂ©lectionnĂ©s de façon alĂ©atoire. Tous les Ă©chantillons de sĂ©rum ont Ă©tĂ© analysĂ©s avec le test 2 par un panel de laboratoires d’analyses vĂ©tĂ©rinaires et environ 20 % (n= 4 319) ont Ă©galement Ă©tĂ© analysĂ©s avec les tests 1, 2 et 3 au laboratoire national de rĂ©fĂ©rence de la fiĂšvre Q. Les performances diagnostiques des trois tests ELISA pour chaque espĂšce de ruminant ont Ă©tĂ© estimĂ©es Ă  l’aide d’un modĂšle Ă  classes latentes prenant en compte la dĂ©pendance conditionnelle entre les trois tests. L’incertitude diagnostique estimĂ©e pour le test 2 a permis d’étudier la distribution de la proportion d’élevages sĂ©ropositifs selon les dĂ©partements (sĂ©roprĂ©valence inter-Ă©levage) et la proportion d’animaux sĂ©ropositifs selon les Ă©levages (sĂ©roprĂ©valence intra-Ă©levage) pour chacune des espĂšces. Enfin, une application Shiny libre d’accĂšs Ă  destination des acteurs de terrain a Ă©tĂ© dĂ©veloppĂ©e pour permettre d’estimer la probabilitĂ© que l’individu testĂ© ou le troupeau dĂ©pistĂ© soit rĂ©ellement sĂ©ropositif sachant les caractĂ©ristiques de l’élevage, le contexte Ă©pidĂ©miologique et les rĂ©sultats du plan de dĂ©pistage rĂ©alisĂ©. L’ensemble de ces travaux permet de mieux interprĂ©ter les rĂ©sultats obtenus avec ces tests ELISA dans le cadre d’un dĂ©pistage ciblĂ© ou d’un programme de surveillance de la fiĂšvre Q Ă  l’échelle d’élevages, de rĂ©gions, voire de pays. Ils proposent donc des Ă©lĂ©ments de rĂ©ponses aux exigences rĂ©glementaires rĂ©cemment mises en application dans le cadre du RĂšglement (UE) 2018/1882 et catĂ©gorisant la fiĂšvre Q comme une maladie de catĂ©gorie E Ă  surveillance obligatoire.Q fever is a zoonotic disease, caused by the bacterium Coxiella burnetii. Most of human clinical cases are related to an exposition to domestic ruminants. Because domestic ruminants may be latently infected or intermittently shed the bacterium, serological methods such as ELISA are recommended by the OIE for the detection of past or present infections by C. burnetii. However, no gold standard method is available to assess with certainty the serological status of an animal. To date, three ELISA tests (later referred to as test 1, 2 and 3) are commercialized in Europe but their diagnostic performances are not well known. The thesis manuscript is divided into three parts, with the objectives: (1) to assess the diagnostic performances of the three ELISA tests commercialized for the serological diagnosis of C. burnetii infection in cattle, sheep and goats; (2) to assess true seroprevalence levels in these three domestic ruminant species based on test 2 while accounting for the diagnostic uncertainty of this test; (3) to develop an online tool to help stakeholders interpreting the results of a serological screening plan based on the results obtained in parts 1 and 2.This work is based on data collected for the Q fever surveillance program performed between 2012 and 2014 in 10 French departments. The database includes serological results from 9,972 cattle, 5,024 goats and 7,632 sheep sampled from 1,602 herds randomly selected. All samples were analyzed with test 2 and approximately 20% (n= 4,319) were also analyzed with tests 1, 2 and 3 at the French national reference laboratory for Q fever.Diagnostic performances of the three ELISA tests were assessed using a latent class model accounting for the diagnostic accuracy between the three tests. Diagnostic uncertainty values estimated for test 2 were used to model the distribution of the proportion of true seropositive herds in each department (within-herd seroprevalence) and the proportion of true seropositive animals in seropositive herds (within-herd seroprevalence) for each ruminant species. Finally, a freely accessible Shiny application was designed so that stakeholders may assess the probability that an animal tested or a herd screened is truly seropositive given the herd’s characteristics, the epidemiological context and the results of the screening plan performed. This work allows better interpreting ELISA results obtained as part of a Q fever targeted screening plan or surveillance program at the scale of herds, regions or even countries. It provides first answers to the mandatory requirements related to the recent application of the EU 2018/1882 regulation, which classifies Q fever as a category E disease with a need for surveillance

    Évaluation et prise en compte de l’incertitude diagnostique des tests utilisĂ©s pour le dĂ©pistage sĂ©rologique des infections par Coxiella burnetii chez les ruminants domestiques

    No full text
    Q fever is a zoonotic disease, caused by the bacterium Coxiella burnetii. Most of human clinical cases are related to an exposition to domestic ruminants. Because domestic ruminants may be latently infected or intermittently shed the bacterium, serological methods such as ELISA are recommended by the OIE for the detection of past or present infections by C. burnetii. However, no gold standard method is available to assess with certainty the serological status of an animal. To date, three ELISA tests (later referred to as test 1, 2 and 3) are commercialized in Europe but their diagnostic performances are not well known. The thesis manuscript is divided into three parts, with the objectives: (1) to assess the diagnostic performances of the three ELISA tests commercialized for the serological diagnosis of C. burnetii infection in cattle, sheep and goats; (2) to assess true seroprevalence levels in these three domestic ruminant species based on test 2 while accounting for the diagnostic uncertainty of this test; (3) to develop an online tool to help stakeholders interpreting the results of a serological screening plan based on the results obtained in parts 1 and 2.This work is based on data collected for the Q fever surveillance program performed between 2012 and 2014 in 10 French departments. The database includes serological results from 9,972 cattle, 5,024 goats and 7,632 sheep sampled from 1,602 herds randomly selected. All samples were analyzed with test 2 and approximately 20% (n= 4,319) were also analyzed with tests 1, 2 and 3 at the French national reference laboratory for Q fever.Diagnostic performances of the three ELISA tests were assessed using a latent class model accounting for the diagnostic accuracy between the three tests. Diagnostic uncertainty values estimated for test 2 were used to model the distribution of the proportion of true seropositive herds in each department (within-herd seroprevalence) and the proportion of true seropositive animals in seropositive herds (within-herd seroprevalence) for each ruminant species. Finally, a freely accessible Shiny application was designed so that stakeholders may assess the probability that an animal tested or a herd screened is truly seropositive given the herd’s characteristics, the epidemiological context and the results of the screening plan performed. This work allows better interpreting ELISA results obtained as part of a Q fever targeted screening plan or surveillance program at the scale of herds, regions or even countries. It provides first answers to the mandatory requirements related to the recent application of the EU 2018/1882 regulation, which classifies Q fever as a category E disease with a need for surveillance.La fiĂšvre Q est une maladie zoonotique causĂ©e par la bactĂ©rie Coxiella burnetii. La plupart des cas cliniques humains recensĂ©s sont liĂ©s Ă  une exposition Ă  des ruminants domestiques excrĂ©teurs de la bactĂ©rie. Chez les ruminants domestiques, en raison de la prĂ©sence de porteurs latents et de l’excrĂ©tion intermittente de la bactĂ©rie, les tests sĂ©rologiques de type ELISA sont recommandĂ©s par l’OIE pour tĂ©moigner d’infections passĂ©es ou en cours. Cependant, il n’existe pas de mĂ©thode gold standard permettant de dĂ©terminer avec certitude le statut sĂ©rologique des individus. À ce jour, trois tests ELISA (ci-aprĂšs nommĂ©s test 1, 2, 3) sont commercialisĂ©s en Europe, mais leurs performances diagnostiques sont mal connues. La thĂšse est divisĂ©e en trois parties avec respectivement pour objectifs : (1) d’estimer les performances diagnostiques chez les bovins, ovins et caprins des trois tests ELISA commercialisĂ©s en Europe pour le diagnostic sĂ©rologique des infections par C. burnetii ; (2) d’estimer les sĂ©roprĂ©valences rĂ©elles des infections par C. burnetii chez ces trois espĂšces de ruminants domestiques sur la base du test 2 en prenant en compte son incertitude diagnostique ; (3) de construire un outil en ligne d’aide Ă  l’interprĂ©tation des plans de dĂ©pistage sĂ©rologique en intĂ©grant les estimations rĂ©alisĂ©es dans les parties 1 et 2. Les travaux s’appuient sur les donnĂ©es collectĂ©es dans le cadre du dispositif de surveillance de la fiĂšvre Q mis en place entre 2012 et 2014 dans dix dĂ©partements français. La base de donnĂ©es comprend 9 972 bovins, 5 024 caprins et 7 632 ovins Ă©chantillonnĂ©s dans 1 602 Ă©levages sĂ©lectionnĂ©s de façon alĂ©atoire. Tous les Ă©chantillons de sĂ©rum ont Ă©tĂ© analysĂ©s avec le test 2 par un panel de laboratoires d’analyses vĂ©tĂ©rinaires et environ 20 % (n= 4 319) ont Ă©galement Ă©tĂ© analysĂ©s avec les tests 1, 2 et 3 au laboratoire national de rĂ©fĂ©rence de la fiĂšvre Q. Les performances diagnostiques des trois tests ELISA pour chaque espĂšce de ruminant ont Ă©tĂ© estimĂ©es Ă  l’aide d’un modĂšle Ă  classes latentes prenant en compte la dĂ©pendance conditionnelle entre les trois tests. L’incertitude diagnostique estimĂ©e pour le test 2 a permis d’étudier la distribution de la proportion d’élevages sĂ©ropositifs selon les dĂ©partements (sĂ©roprĂ©valence inter-Ă©levage) et la proportion d’animaux sĂ©ropositifs selon les Ă©levages (sĂ©roprĂ©valence intra-Ă©levage) pour chacune des espĂšces. Enfin, une application Shiny libre d’accĂšs Ă  destination des acteurs de terrain a Ă©tĂ© dĂ©veloppĂ©e pour permettre d’estimer la probabilitĂ© que l’individu testĂ© ou le troupeau dĂ©pistĂ© soit rĂ©ellement sĂ©ropositif sachant les caractĂ©ristiques de l’élevage, le contexte Ă©pidĂ©miologique et les rĂ©sultats du plan de dĂ©pistage rĂ©alisĂ©. L’ensemble de ces travaux permet de mieux interprĂ©ter les rĂ©sultats obtenus avec ces tests ELISA dans le cadre d’un dĂ©pistage ciblĂ© ou d’un programme de surveillance de la fiĂšvre Q Ă  l’échelle d’élevages, de rĂ©gions, voire de pays. Ils proposent donc des Ă©lĂ©ments de rĂ©ponses aux exigences rĂ©glementaires rĂ©cemment mises en application dans le cadre du RĂšglement (UE) 2018/1882 et catĂ©gorisant la fiĂšvre Q comme une maladie de catĂ©gorie E Ă  surveillance obligatoire
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