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Sainte-Foy-lès-Lyon, France

Among global changes induced by human activities, association of breakdown of geographical barriers and impoverishered biodiversity of agroecosystems may have a strong evolutionary impact on pest species. As a consequence of trade networks' expansion, secondary contacts between incipient species, if hybrid incompatibility is not yet reached, may result in hybrid swarms, even more when empty niches are available as usual in crop fields and farms. By providing important sources of genetic novelty for organisms to adapt in changing environments, hybridization may be strongly involved in the emergence of invasive populations. Because national and international trade networks offered multiple hybridization opportunities during the previous and current centuries, population structure of many pest species is expected to be the most intricate and its inference often blurred when using fast-evolving markers. Here we show that mito-nuclear sequence datasets may be the most helpful in disentangling successive layers of admixture in the composition of pest populations. As a model we used D. gallinae s. l., a mesostigmatid mite complex of two species primarily parasitizing birds, namely D. gallinae L1 and D. gallinae s. str. The latter is a pest species, considered invading layer farms in Brazil. The structure of the pest as represented by isolates from both wild and domestic birds, from European (with a focus on France), Australian and Brazilian farms, revealed past hybridization events and very recent contact between deeply divergent lineages. The role of wild birds in the dissemination of mites appears to be null in European and Australian farms, but not in Brazilian ones. In French farms, some recent secondary contact is obviously consecutive to trade flows. Scenarios of populations' history were established, showing five different combinations of more or less dramatic bottlenecks and founder events, nearly interspecific hybridizations and recent population mixing within D. gallinae s. str. © 2011 Roy, Buronfosse. Source


Vergne T.,Laboratoire Of Sante Animale | Vergne T.,CIRAD - Agricultural Research for Development | Calavas D.,Anses Lyon | Cazeau G.,Anses Lyon | And 3 more authors.
Preventive Veterinary Medicine | Year: 2012

Capture-recapture (CR) methods are used to study populations that are monitored with imperfect observation processes. They have recently been applied to the monitoring of animal diseases to evaluate the number of infected units that remain undetected by the surveillance system. This paper proposes three Bayesian models to estimate the total number of scrapie-infected holdings in France from CR count data obtained from the French classical scrapie surveillance programme. We fitted two zero-truncated Poisson (ZTP) models (with and without holding size as a covariate) and a zero-truncated negative binomial (ZTNB) model to the 2006 national surveillance count dataset. We detected a large amount of heterogeneity in the count data, making the use of the simple ZTP model inappropriate. However, including holding size as a covariate did not bring any significant improvement over the simple ZTP model. The ZTNB model proved to be the best model, giving an estimation of 535 (CI 95% 401-796) infected and detectable sheep holdings in 2006, although only 141 were effectively detected, resulting in a holding-level prevalence of 4.4‰ (CI 95% 3.2-6.3) and a sensitivity of holding-level surveillance of 26% (CI 95% 18-35). The main limitation of the present study was the small amount of data collected during the surveillance programme. It was therefore not possible to build complex models that would allow depicting more accurately the epidemiological and detection processes that generate the surveillance data. We discuss the perspectives of capture-recapture count models in the context of animal disease surveillance. © 2012 Elsevier B.V. Source


Bronner A.,Anses Lyon | Morignat E.,Anses Lyon | Henaux V.,Anses Lyon | Madouasse A.,French National Institute for Agricultural Research | And 3 more authors.
PLoS ONE | Year: 2015

Bovine abortion surveillance is essential for human and animal health because it plays an important role in the early warning of several diseases. Due to the limited sensitivity of traditional surveillance systems, there is a growing interest for the development of syndromic surveillance. Our objective was to assess whether, routinely collected, artificial insemination (AI) data could be used, as part of a syndromic surveillance system, to devise an indicator of mid-term abortions in dairy cattle herds in France. A mid-term abortion incidence rate (MAIR) was computed as the ratio of the number of mid-term abortions to the number of female- weeks at risk. A mid-term abortion was defined as a return-to-service (i.e. a new AI) taking place 90 to 180 days after the previous AI. Weekly variations in the MAIR in heifers and parous cows were modeled with a time-dependent Poisson model at the département level (French administrative division) during the period of 2004 to 2010. The usefulness of monitoring this indicator to detect a disease-related increase in mid-term abortions was evaluated using data from the 2007-2008 episode of bluetongue serotype 8 (BT8) in France. An increase in the MAIR was identified in heifers and parous cows in 47% (n = 24) and 71% (n = 39) of the départements. On average, the weekly MAIR among heifers increased by 3.8% (min-max: 0.02-57.9%) when the mean number of BT8 cases that occurred in the previous 8 to 13 weeks increased by one. The weekly MAIR among parous cows increased by 1.4% (0.01-8.5%) when the mean number of BT8 cases occurring in the previous 6 to 12 weeks increased by one. These results underline the potential of the MAIR to identify an increase in mid-term abortions and suggest that it is a good candidate for the implementation of a syndromic surveillance system for bovine abortions. © 2015 Bronner et al. Source


Bronner A.,Anses Lyon | Gay E.,Anses Lyon | Fortane N.,French National Institute for Agricultural Research | Palussiere M.,Anses Lyon | And 3 more authors.
Preventive Veterinary Medicine | Year: 2015

Bovine abortion is the main clinical sign of bovine brucellosis, a disease of which France has been declared officially free since 2005. To ensure the early detection of any brucellosis outbreak, event-driven surveillance relies on the mandatory notification of bovine abortions and the brucellosis testing of aborting cows. However, the under-reporting of abortions appears frequent. Our objectives were to assess the aptitude of the bovine abortion surveillance system to detect each and every bovine abortion and to identify factors influencing the system's effectiveness. We evaluated five attributes defined by the U.S. Centers for Disease Control with a method suited to each attribute: (1) data quality was studied quantitatively and qualitatively, as this factor considerably influences data analysis and results; (2) sensitivity and representativeness were estimated using a unilist capture-recapture approach to quantify the surveillance system's effectiveness; (3) acceptability and simplicity were studied through qualitative interviews of actors in the field, given that the surveillance system relies heavily on abortion notifications by farmers and veterinarians. Our analysis showed that (1) data quality was generally satisfactory even though some errors might be due to actors' lack of awareness of the need to collect accurate data; (2) from 2006 to 2011, the mean annual sensitivity - i.e. the proportion of farmers who reported at least one abortion out of all those who detected such events - was around 34%, but was significantly higher in dairy than beef cattle herds (highlighting a lack of representativeness); (3) overall, the system's low sensitivity was related to its low acceptability and lack of simplicity. This study showed that, in contrast to policy-makers, most farmers and veterinarians perceived the risk of a brucellosis outbreak as negligible. They did not consider sporadic abortions as a suspected case of brucellosis and usually reported abortions only to identify their cause rather than to reject brucellosis. The system proved too complex, especially for beef cattle farmers, as they may fail to detect aborting cows at pasture or have difficulties catching them for sampling. By investigating critical attributes, our evaluation highlighted the surveillance system's strengths and needed improvements. We believe our comprehensive approach can be used to assess other event-driven surveillance systems. In addition, some of our recommendations on increasing the effectiveness of event-driven brucellosis surveillance may be useful in improving the notification rate for suspected cases of other exotic diseases. © 2015 Elsevier B.V. Source


Bronner A.,Anses Lyon | Morignat E.,Anses Lyon | Gay E.,Anses Lyon | Calavas D.,Anses Lyon
Preventive Veterinary Medicine | Year: 2015

The bovine abortion surveillance system in France aims to detect as early as possible any resurgence of bovine brucellosis, a disease of which the country has been declared free since 2005. It relies on the mandatory notification and testing of each aborting cow, but under-reporting is high. This research uses a new and simple approach which considers the calving interval (CI) as a "diagnostic test" to determine optimal cut-off point c and estimate diagnostic performance of the CI to identify aborting cows, and herds with multiple abortions (i.e. three or more aborting cows per calving season). The period between two artificial inseminations (AI) was considered as a "gold standard". During the 2006-2010 calving seasons, the mean optimal CI cut-off point for identifying aborting cows was 691 days for dairy cows and 703 days for beef cows. Depending on the calving season, production type and scale at which c was computed (individual or herd), the average sensitivity of the CI varied from 42.6% to 64.4%; its average specificity from 96.7% to 99.7%; its average positive predictive value from 27.6% to 65.4%; and its average negative predictive value from 98.7% to 99.8%. When applied to the French bovine population as a whole, this indicator identified 2-3% of cows suspected to have aborted, and 10-15% of herds suspected of multiple abortions. The optimal cut-off point and CI performance were consistent over calving seasons. By applying an optimal CI cut-off point to the cattle demographics database, it becomes possible to identify herds with multiple abortions, carry out retrospective investigations to find the cause of these abortions and monitor a posteriori compliance of farmers with their obligation to report abortions for brucellosis surveillance needs. Therefore, the CI could be used as an indicator of abortions to help improve the current mandatory notification surveillance system. © 2015 Elsevier B.V. Source

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