Estimation of sensitivity and specificity of bacteriology, histopathology and PCR for the confirmatory diagnosis of bovine tuberculosis using latent class analysis

Bacteriology and histopathology are the most commonly used tests used for official confirmatory diagnosis of bovine tuberculosis (bTB) in cattle in most countries. PCR is also being used increasingly because it allows a fast diagnosis. This test could be applied as a supplement to or replacement for current bTB confirmatory diagnostic tests but its characteristics have first to be evaluated. The aim of this study was to estimate and compare sensitivities and specificities of bacteriology, histopathology and PCR under French field conditions, in the absence of a gold standard using latent class analysis. The studied population consisted of 5,211 animals from which samples were subjected to bacteriology and PCR (LSI VetMAX™ Mycobacterium tuberculosis Complex PCR Kit, Life Technologies) as their herd of origin was either suspected or confirmed infected with bTB or because bTB-like lesions were detected during slaughterhouse inspection. Samples from 697 of these animals (all with bTB-like lesions) were subjected to histopathology. Bayesian models were developed, allowing for dependence between bacteriology and PCR, while assuming independence from histopathology. The sensitivity of PCR was higher than that of bacteriology (on average 87.7% [82.5–92.3%] versus 78.1% [72.9–82.8%]) while specificity of both tests was very good (on average 97.0% for PCR [94.3–99.0%] and 99.1% for bacteriology [97.1–100.0%]). Histopathology was at least as sensitive as PCR (on average 93.6% [89.9–96.9%]) but less specific than the two other tests (on average 83.3% [78.7–87.6%]). These results suggest that PCR has the potential to replace bacteriology to confirm bTB in samples submitted from suspect cattle.

Role of Cattle Movements in Bovine Tuberculosis Spread in France between 2005 and 2014

Live animal movements are a major transmission route for the spread of infectious agents such as Mycobacterium bovis, the main agent of bovine Tuberculosis (bTB). France became officially bTB-free in 2001, but M. bovis is still circulating in the cattle population, with about a hundred of outbreaks per year, most located in a few geographic areas. The aim of this study was to analyse the role of cattle movements in bTB spread in France between 2005 and 2014, using social network analysis and logistic regression models. At a global scale, the trade network was studied to assess the association between several centrality measures and bTB infection though a case-control analysis. The bTB infection status was associated with a higher in-degree (odds-ratio [OR] = 2.4 [1.1–5.4]) and with a higher ingoing contact chain (OR = 2.2 [1.0–4.7]). At a more local scale, a second case-control analysis was conducted to estimate the relative importance of cattle movements and spatial neighbourhood. Only direct purchase from infected herds was shown to be associated with bTB infection (OR = 2.9 [1.7–5.2]), spatial proximity to infected herds being the predominant risk factor, with decreasing ORs when distance increases. Indeed, the population attributable fraction was 12% [5%–18%] for cattle movements and 73% [68%–78%] for spatial neighbourhood. Based on these results, networks of potential effective contacts between herds were built and analysed for the three major spoligotypes reported in France. In these networks, the links representing cattle movements were associated with higher edge betweenness than those representing the spatial proximity between infected herds. They were often links connecting distinct communities and sometimes distinct geographical areas. Therefore, although their role was quantitatively lower than the one of spatial neighbourhood, cattle movements appear to have been essential in the French bTB dynamics between 2005 and 2014.

Spatio-temporal patterns of highly pathogenic avian influenza virus subtype H5N8 spread, France, 2016 to 2017

IntroductionFrance is one of Europe's foremost poultry producers and the world's fifth largest producer of poultry meat. In November 2016, highly pathogenic avian influenza (HPAI) virus subtype H5N8 emerged in poultry in the country. As of 23 March 2017, a total of 484 confirmed outbreaks were reported, with consequences on animal health and socio-economic impacts for producers. Methods: We examined the spatio-temporal distribution of outbreaks that occurred in France between November 2016 and March 2017, using the space-time K-function and space-time permutation model of the scan statistic test. Results: Most outbreaks affected duck flocks in south-west France. A significant space-time interaction of outbreaks was present at the beginning of the epidemic within a window of 8 km and 13 days. This interaction disappeared towards the epidemic end. Five spatio-temporal outbreak clusters were identified in the main poultry producing areas, moving sequentially from east to west. The average spread rate of the epidemic front wave was estimated to be 5.5 km/week. It increased from February 2017 and was negatively associated with the duck holding density. Conclusion: HPAI-H5N8 infections varied over time and space in France. Intense transmission events occurred at the early stages of the epidemic, followed by long-range jumps in the disease spread towards its end. Findings support strict control strategies in poultry production as well as the maintenance of high biosecurity standards for poultry holdings. Factors and mechanisms driving HPAI spread need to be further investigated.

Exposure of wild boar to Mycobacterium tuberculosis complex in France since 2000 is consistent with the distribution of bovine tuberculosis outbreaks in cattle

The Eurasian wild boar (Sus scrofa) is increasingly considered as a relevant actor in the epidemiology of animal tuberculosis (TB). Therefore, monitoring TB in wild boar becomes a key tool for establishing comprehensive control schemes for this disease. To estimate the exposure of free living wild boar to Mycobacterium tuberculosis complex (MTC) in France, a bovine-purified protein derivative based ELISA was used to test 2,080 archived serum samples of hunter-harvested animals in 58 French “départements”. Two cut-off values were used for diagnostic interpretation: 0.2, recommended by the manufacturer (specificity: 96.43%; sensitivity: 72.6%), and 0.5 (specificity: 100%; sensitivity: 64%). During the same period, at the 0.2 cut-off, global true seroprevalence was 5.9% (IC_95%: 4.3%-7.7%) and 76% of the sampled “départements” had seropositive wild boar, including seven cattle TB-free “départements. At the 0.5 cut-off, global true seroprevalence was 2.2% (IC_95%: 1.5-3.2) and positive wild boar belonged to 21% of the “départements”. All but one of these positive “départements” had reported at least one cattle TB outbreak since 2000. A good consistence between seropositive wild boar and TB outbreaks in cattle was found, especially at the 0.5 cut-off value (the mean distance to the nearest cattle TB outbreak was 13km and 27km for seropositive and seronegative wild boar, respectively; P<0.05). The use of an ELISA to detect MTC antibodies in wild boar has permitted the description of the geographic distribution of MTC contact in wild boar in France. Our results suggest that the ELISA could be used as a first screening tool to conduct TB surveillance in wild boar at a population level. High-risk wild boar populations (e.g. overabundant) could be tested and if identified positive by ELISA they should be surveyed in detail by combining pathology and culture.

Modelling the spread of Bovine Viral Diarrhoea Virus (BVDV) in a managed metapopulation of cattle herds

In numerous epidemiological models developed within a metapopulation framework, it is assumed that a single infected individual introduced into a patch infects the whole patch and that the proportion of infected individuals into infected patches is consistent over time and among patches. If this approach is relevant for rapidly spreading pathogens, it is less appropriate for moderately spreading pathogens, like the Bovine Viral Diarrhoea Virus (BVDV), characterized by a variability in within-patch prevalence. Our objective is to study the respective influence of neighbouring relationships and animal movements on the spread of BVDV in a managed metapopulation of 100 cattle herds. Infection dynamics is represented by two coupled stochastic compartmental models in discrete-time: a within-herd and a between-herd models. Animal movements are mechanistically modelled. They largely influence the BVDV persistence, the prevalence in infected herds and the epidemic size. Neighbouring relationships only influence epidemic size. Whatever the neighbouring relationships, the infection does not persist in the metapopulation without animal movement between herds. The proposed model can be easily adapted for different herd contact structures.

Modelling effectiveness of herd level vaccination against Q fever in dairy cattle

Q fever is a worldwide zoonosis caused by the bacterium Coxiella burnetii. The control of this infection in cattle is crucial: infected ruminants can indeed encounter reproductive disorders and represent the most important source of human infection. In the field, vaccination is currently advised in infected herds but the comparative effectiveness of different vaccination protocols has never been explored: the duration of the vaccination programme and the category of animals to be vaccinated have to be determined. Our objective was to compare, by simulation, the effectiveness over 10 years of three different vaccination strategies in a recently infected dairy cattle herd.A stochastic individual-based epidemic model coupled with a model of herd demography was developed to simulate three temporal outputs (shedder prevalence, environmental bacterial load and number of abortions) and to calculate the extinction rate of the infection. For all strategies, the temporal outputs were predicted to strongly decrease with time at least in the first years of vaccination. However, vaccinating only three years was predicted inadequate to stabilize these dynamic outputs at a low level. Vaccination of both cows and heifers was predicted as being slightly more effective than vaccinating heifers only. Although the simulated extinction rate of the infection was high for both scenarios, the outputs decreased slower when only heifers were vaccinated.Our findings shed new light on vaccination effectiveness related to Q fever. Moreover, the model can be further modified for simulating and assessing various Q fever control strategies such as environmental and hygienic measures.

Spread of Q fever within dairy cattle herds: key parameters inferred using a Bayesian approach

Q fever is a worldwide zoonosis caused by Coxiella burnetii. Although ruminants are recognized as the most important source of human infection, no previous studies have focused on assessing the characteristics of the bacterial spread within a cattle herd and no epidemic model has been proposed in this context. We assess the key epidemiological parameters from field data in a Bayesian framework that takes into account the available knowledge, missing data and the uncertainty of the observation process owing to the imperfection of diagnostic tests. We propose an original individual-based Markovian model in discrete time describing the evolution of the infection for each animal. Markov chain Monte Carlo methodology is used to estimate parameters of interest from data consisting of individual health states of 217 cows of five chronically infected dairy herds sampled every week for a four-week period. Outputs are the posterior distributions of the probabilities of transition between health states and of the environmental bacterial load. Our findings show that some herds are characterized by a very low infection risk while others have a mild infection risk and a non-negligible intermittent shedding probability. Moreover, the antibody status seems to be a key point in the bacterial spread (shedders with antibodies shed for a longer period of time than shedders without antibodies). In addition to the biological insights, these estimates also provide information for calibrating simulation models to assess control strategies for C. burnetii infection.

Highly pathogenic avian influenza H5N8 in south-west France 2016-2017: A modeling study of control strategies

In the winter 2016-2017 the largest epidemic of highly pathogenic avian influenza (HPAI) ever recorded in the European Union spread to all 28 member states. France was hit particularly hard and reported a total of 484 infected premises (IPs) by March 2017. We developed a mathematical model to analyze the spatiotemporal evolution of the epidemic and evaluate the impact of control strategies. We estimated that farms rearing ducks were on average 2.5 times more infectious and 5.0 times more susceptible to HPAI than farms rearing other avian species. The implementation of surveillance zones around IPs reduced transmission by a factor of 1.8 on average. Compared to the strengthening of pre-emptive culling measures enforced by French authorities in February 2017, we found that a faster depopulation of diagnosed IPs would have had a larger impact on the total number of infections. For example, halving the time delay from detection to slaughter of infected animals would have reduced the total number of IPs by 52% and total cull numbers by 50% on average. This study showcases the possible contribution of modeling to inform and optimize control strategies during an outbreak.

The Distribution of Bovine Tuberculosis in Cattle Farms Is Linked to Cattle Trade and Badger-Mediated Contact Networks in South-Western France, 2007-2015

Bovine tuberculosis (bTB), mainly caused by Mycobacterium bovis, can affect domestic and wild animals as well as humans. Identifying the major transmission mechanisms in an area is necessary for disease control and management. In this study, we aimed to evaluate the involvement of different types of contact in M. bovis transmission between cattle farms of south-western France between 2007 and 2015. We analyzed an empirical contact network of cattle farms as nodes, with known infection status and molecular types (16 circulated during the study period of which 14 affected only cattle and two both badgers and cattle). Edges were based on cattle trade data (T-edges) and on spatial neighborhood relationships between farms, either direct (P-edges) or badger-mediated, when two farms neighbored the same badger home range (B-edges), or two distinct but neighboring badger home ranges (D-edges). Edge types were aggregated so that the contact network contained only unique edges labeled by one or several edge types. The association between the contact network structure and bTB infection status was assessed using a non-parametric test, each molecular type being considered a marker of an independent epidemic. Using a logistic regression model, we estimated the contribution of each edge type to the probability for an edge originating from an infected farm to end at another infected farm. A total number of 1946 cattle farms were included in the study and were linked by 54,243 edges. Within this contact network, infected farms (whatever the molecular type) always belonged to the same component, suggesting the contact network may have supported bTB spread among those farms. A significant association between the pattern of bTB-infected farms and the structure of the contact network was observed when all the molecular types were simultaneously considered. The logistic regression model showed a significant association between M. bovis infection in direct neighbors of infected farms and the connection by T-, B- and D-edges, with odds-ratios of 7.4, 1.9, and 10.4, respectively. These results indicate a multifactorial M. bovis transmission between cattle farms of the studied area, with varying implication levels of the trade, pasture and badger networks according to the molecular type.

Quantitative Outcomes of a One Health approach to Study Global Health Challenges

Having gained momentum in the last decade, the One Health initiative promotes a holistic approach to address complex global health issues. Before recommending its adoption to stakeholders, however, it is paramount to first compile quantitative evidence of the benefit of such an approach. The aim of this scoping review was to identify and summarize primary research that describes monetary and non-monetary outcomes following adoption of a One Health approach. An extensive literature search yielded a total of 42,167 references, of which 85 were included in the final analysis. The top two biotic health issues addressed in these studies were rabies and malaria; the top abiotic health issue was air pollution. Most studies described collaborations between human and animal (n = 42), or human and environmental disciplines (n = 41); commonly reported interventions included vector control and animal vaccination. Monetary outcomes were commonly expressed as cost-benefit or cost-utility ratios; non-monetary outcomes were described using disease frequency or disease burden measurements. The majority of the studies reported positive or partially positive outcomes. This paper illustrates the variety of health challenges that can be addressed using a One Health approach, and provides tangible quantitative measures that can be used to evaluate future implementations of the One Health approach.

Dairy goat demography and Q fever infection dynamics

Between 2007 and 2009, the largest human Q fever epidemic ever described occurred in the Netherlands. The source was traced back to dairy goat farms, where abortion storms had been observed since 2005. Since one putative cause of these abortion storms is the intensive husbandry systems in which the goats are kept, the objective of this study was to assess whether these could be explained by herd size, reproductive pattern and other demographic aspects of Dutch dairy goat herds alone. We adapted an existing, fully parameterized simulation model for Q fever transmission in French dairy cattle herds to represent the demographics typical for Dutch dairy goat herds. The original model represents the infection dynamics in a herd of 50 dairy cows after introduction of a single infected animal; the adapted model has 770 dairy goats. For a full comparison, herds of 770 cows and 50 goats were also modeled. The effects of herd size and goat versus cattle demographics on the probability of and time to extinction of the infection, environmental bacterial load and abortion rate were studied by simulation. The abortion storms could not be fully explained by demographics alone. Adequate data were lacking at the moment to attribute the difference to characteristics of the pathogen, host, within-herd environment, or a combination thereof. The probability of extinction was higher in goat herds than in cattle herds of the same size. The environmental contamination was highest within cattle herds, which may be taken into account when enlarging cattle farming systems.

Modelling the effect of heterogeneity of shedding on the within herd Coxiella burnetii spread and identification of key parameters by sensitivity analysis

Coxiella burnetii is the bacterium responsible for Q fever, a worldwide zoonosis. Ruminants, especially cattle, are recognized as the most important source of human infections. Although a great heterogeneity between shedder cows has been described, no previous studies have determined which features such as shedding route and duration or the quantity of bacteria shed have the strongest impact on the environmental contamination and thus on the zoonotic risk. Our objective was to identify key parameters whose variation highly influences C. burnetii spread within a dairy cattle herd, especially those related to the heterogeneity of shedding. To compare the impact of epidemiological parameters on different dynamical aspects of C. burnetii infection, we performed a sensitivity analysis on an original stochastic model describing the bacterium spread and representing the individual variability of the shedding duration, routes and intensity as well as herd demography. This sensitivity analysis consisted of a principal component analysis followed by an ANOVA. Our findings show that the most influential parameters are the probability distribution governing the levels of shedding, especially in vaginal mucus and faeces, the characteristics of the bacterium in the environment (i.e. its survival and the fraction of bacteria shed reaching the environment), and some physiological parameters related to the intermittency of shedding (transition probability from a non-shedding infected state to a shedding state) or to the transition from one type of shedder to another one (transition probability from a seronegative shedding state to a seropositive shedding state). Our study is crucial for the understanding of the dynamics of C. burnetii infection and optimization of control measures. Indeed, as control measures should impact the parameters influencing the bacterium spread most, our model can now be used to assess the effectiveness of different control strategies of Q fever within dairy cattle herds.

Modeling tuberculosis dynamics, detection and control in cattle herds

Epidemiological models are key tools for designing and evaluating detection and control strategies against animal infectious diseases. In France, after decades of decrease of bovine tuberculosis (bTB) incidence, the disease keeps circulating. Increasing prevalence levels are observed in several areas, where the detection and control strategy could be adapted. The objective of this work was to design and calibrate a model of the within-herd transmission of bTB. The proposed model is a stochastic model operating in discrete-time. Three health states were distinguished: susceptible, latent and infected. Dairy and beef herd dynamics and bTB detection and control programs were explicitly represented. Approximate Bayesian computation was used to estimate three model parameters from field data: the transmission parameter when animals are inside (β_inside) and outside (β_outside) buildings, and the duration of the latent phase. An independent dataset was used for model validation. The estimated median was 0.43 [0.16–0.84] month⁻¹ for β_inside and 0.08 [0.01–0.32] month⁻¹ for β_outside. The median duration of the latent period was estimated 3.5 [2]–[8] months. The sensitivity analysis showed only minor influences of fixed parameter values on these posterior estimates. Validation based on an independent dataset showed that in more than 80% of herds, the observed proportion of animals with detected lesions was between the 2.5% and 97.5% percentiles of the simulated distribution. In the absence of control program and once bTB has become enzootic within a herd, the median effective reproductive ratio was estimated to be 2.2 in beef herds and 1.7 in dairy herds. These low estimates are consistent with field observations of a low prevalence level in French bTB-infected herds.

Analysis of the Spatial Organization of Pastures as a Contact Network, Implications for Potential Disease Spread and Biosecurity in Livestock, France, 2010

The use of pastures is part of common herd management practices for livestock animals, but contagion between animals located on neighbouring pastures is one of the major modes of infectious disease transmission between herds. At the population level, this transmission is strongly constrained by the spatial organization of pastures. The aim of this study was to answer two questions: (i) is the spatial configuration of pastures favourable to the spread of infectious diseases in France? (ii) would biosecurity measures allow decreasing this vulnerability? Based on GIS data, the spatial organization of pastures was represented using networks. Nodes were the 3,159,787 pastures reported in 2010 by the French breeders to claim the Common Agricultural Policy subsidies. Links connected pastures when the distance between them was below a predefined threshold. Premises networks were obtained by aggregating into a single node all the pastures under the same ownership. Although the pastures network was very fragmented when the distance threshold was short (1.5 meters, relevant for a directly-transmitted disease), it was not the case when the distance threshold was larger (500 m, relevant for a vector-borne disease: 97% of the nodes in the largest connected component). The premises network was highly connected as the largest connected component always included more than 83% of the nodes, whatever the distance threshold. Percolation analyses were performed to model the population-level efficacy of biosecurity measures. Percolation thresholds varied according to the modelled biosecurity measures and to the distance threshold. They were globally high (e.g. >17% of nodes had to be removed, mimicking the confinement of animals inside farm buildings, to obtain the disappearance of the large connected component). The network of pastures thus appeared vulnerable to the spread of diseases in France. Only a large acceptance of biosecurity measures by breeders would allow reducing this structural risk.

Tuberculosis in the wild boar: Frequentist and Bayesian estimations of diagnostic test parameters when Mycobacterium bovis is present in wild boars but at low prevalence

The Eurasian wild boar (Sus scrofa) is increasingly considered as a relevant actor in the epidemiology of animal tuberculosis (TB). Therefore, monitoring TB in this species is key when establishing comprehensive control schemes for this disease still present in Europe. No data are available on direct and indirect TB diagnostic methods in wild boars in epidemiological contexts where TB is endemic in cattle and detected in wild boars at low prevalence. We aimed to estimate and compare sensitivity and specificity values for bacterial culture, PCR and three commercial ELISAs, i.e. the TB ELISA-VK (using the bPPD antigen), INgezim TB Porcine and IDEXX M. bovis Ab Test (both using the MPB83 and MPB70 antigens), under field conditions in France. We used frequentist methods, with bacteriology as the gold standard, and a Bayesian formulation of the latent class analysis (LCA), without using a gold standard. Submandibular lymph nodes and sera from 495 wild boars hunter-harvested in three endemic areas (Aquitaine region, Côte d’Or region, and Corsica region) were collected between 2014 and 2016. Only eight individuals were positive for M. bovis by bacteriology (1.61%; CI_95% 0.70–3.51%). The LCA method provided high specificities (99.2%; CI_95% 98.2–99.8% for INgezim TB Porcine and 99.7%; CI_95% 98.8–100% for IDEXX M. bovis Ab Test) and sensitivities (78.5%; CI_95% 65.1–88.8% for INgezim TB Porcine and 83.9%; CI_95% 58.9–97.2% for IDEXX M. bovis Ab Test) for both ELISAs using the MPB83 and MPB70 antigens. Bacterial culture showed limited sensitivity (42.8%; CI_95% 19.0–70.6%), estimated as the probability of a positive result in an animal exposed to M. bovis. PCR and ELISA using the bPPD antigens demonstrated high specificities, and sensitivities intermediates between culture and the ELISAs using the MPB83 and MPB70 antigens. These results suggest that ELISA tests using the MPB83 and MPB70 antigens are useful to detect and monitor TB exposure of wild boar populations in field conditions in France.

Analysis of a multi-type resurgence of Mycobacterium bovis in cattle and badgers in Southwest France, 2007-2019

Although control measures to tackle bovine tuberculosis (bTB) in cattle have been successful in many parts of Europe, this disease has not been eradicated in areas where Mycobacterium bovis circulates in multi-host systems. Here we analyzed the resurgence of 11 M. bovis genotypes (defined based on spoligotyping and MIRU-VNTR) detected in 141 farms between 2007 and 2019, in an area of Southwestern France where wildlife infection was also detected from 2012 in 65 badgers. We used a spatially-explicit model to reconstruct the simultaneous diffusion of the 11 genotypes in cattle farms and badger populations. Effective reproduction number R was estimated to be 1.34 in 2007-2011 indicating a self-sustained M. bovis transmission by a maintenance community although within-species Rs were both < 1, indicating that neither cattle nor badger populations acted as separate reservoir hosts. From 2012, control measures were implemented, and we observed a decrease of R below 1. Spatial contrasts of the basic reproduction ratio suggested that local field conditions may favor (or penalize) local spread of bTB upon introduction into a new farm. Calculation of generation time distributions showed that the spread of M. bovis has been more rapid from cattle farms (0.5-0.7 year) than from badger groups (1.3-2.4 years). Although eradication of bTB appears possible in the study area (since R < 1), the model suggests it is a long-term prospect, because of the prolonged persistence of infection in badger groups (2.9-5.7 years). Supplementary tools and efforts to better control bTB infection in badgers (including vaccination for instance) appear necessary.

In silico Comparison of Test-and-Cull Protocols for Bovine Tuberculosis Control in France

Whole depopulation of cattle herds (WHD) confirmed infected by bovine tuberculosis (bTB) has led since the 1950s to a drop of herd incidence in France below 0.1% in 2000, justifying the current officially bTB free (OTF) status of the country. However, this protocol is expensive, ethically questionable, and difficult for breeders to accept because the number of confirmed animals in an infected herd is often very low. A test-and-cull protocol combining at least three screening sessions of the entire herd followed by the slaughter of all the non-negative animals has been used for some years. The aim of this work was to evaluate in silico the epidemiological effectiveness, the public costs and the acceptability to farmers of this test-and-cull protocol as well as of several ones. A stochastic compartmental model of within-herd bTB spread was used. Six test-and-cull protocols were compared: two versions of the official protocol and four alternatives with varying delays between screenings, and varying tests used. Protocols were simulated for an average French beef herd, and compared to WHD. Three key indicators were computed: the failure probability of the protocol (a failure being defined as an herd recovering its OTF status recovery while still infected, indicator of epidemiological effectiveness), its overall public cost and the percentage of farmers who would have dropped it to switch to WHD (indicator of acceptability to farmers). Failure probability ranged from 1.4 to 12.4% and was null (by definition) for WHD. The median cost varied between 2.7 and 78 K€ for the test-and-cull protocols, vs. 120 K€ for WHD. The percentage of dropout ranged from 7.8 to 22%. The optimal tradeoff between epidemiological effectiveness, public costs, and acceptability to farmers was obtained for protocols with an increased delay (6 months instead of 2 in the currently used protocol) between the last two screening sessions, with either 3 or 2 screening sessions. This study may help improving the official test-and-cull protocol applied in France under European Union regulation, by suggesting alternative protocols, very effective, cheaper, and more acceptable than WHD.