Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study.

The contribution of bacteria in livestock to the global burden of antimicrobial resistance raises concerns worldwide. However, the dynamics of selection and diffusion of antimicrobial resistance in farm animals are not fully understood. Here, we used veal calf fattening farms as a model system, as they are a known reservoir of Extended Spectrum ß-Lactamase-producing Escherichia coli (ESBL-EC). Longitudinal data of ESBL-EC carriage and antimicrobial use (AMU) were collected from three veal calf farms during the entire fattening process. We developed 18 agent-based mechanistic models to assess different hypotheses regarding the main drivers of ESBL-EC dynamics in calves. The models were independently fitted to the longitudinal data using Markov Chain Monte Carlo and the best model was selected. Within-farm transmission between individuals and sporadic events of contamination were found to drive ESBL-EC dynamics on farms. In the absence of AMU, the median carriage duration of ESBL-EC was estimated to be 19.6 days (95% credible interval: [12.7; 33.3]). In the best model, AMU was found to influence ESBL-EC dynamics, by affecting ESBL-EC clearance rather than acquisition. This effect of AMU was estimated to decrease gradually after the end of exposure and to disappear after 62.5 days [50.0; 76.9]. Moreover, using a simulation study, we quantified the efficacy of ESBL-EC mitigation strategies. Decreasing ESBL-EC prevalence by 50% on arrival at the fattening farm reduced prevalence at slaughter age by 33.3%. Completely eliminating the use of selective antibiotics on arrival had a strong effect on average ESBL-EC prevalence (relative reduction of 77.0%), but the effect was mild if this use was only decreased by 50% compared to baseline (relative reduction of 3.3%).

Trends in antimicrobial resistance among Escherichia coli from defined infections in humans and animals.

OBJECTIVES: To characterize and compare resistance trends in clinical Escherichia coli isolates from humans, food-producing animals (poultry, cattle and swine) and pets (dogs and cats). METHODS: Antibiogram results collected between January 2014 and December 2017 by MedQual [the French surveillance network for antimicrobial resistance (AMR) in bacteria isolated from the community] and RESAPATH (the French surveillance network for AMR in bacteria from diseased animals) were analysed, focusing on resistance to antibiotics of common interest to human and veterinary medicine. Resistance dynamics were investigated using generalized additive models. RESULTS: In total, 743 637 antibiograms from humans, 48 170 from food-producing animals and 7750 from pets were analysed. For each antibiotic investigated, the resistance proportions of isolates collected from humans were of the same order of magnitude as those from food-producing animals or pets. However, resistance trends in humans differed from those observed in pets and food-producing animals over the period studied. For example, resistance to third-generation cephalosporins and fluoroquinolones was almost always below 10% for both humans and animals. However, in contrast to the notable decreases in resistance observed in both food-producing animals and pets, resistance in humans decreased only slightly. CONCLUSIONS: Despite several potential biases in the data, the resistance trends remain meaningful. The strength of the parallel is based on similar data collection in humans and animals and on a similar statistical methodology. Resistance dynamics seemed specific to each species, reflecting different antibiotic-use practices. These results advocate applying the efforts already being made to reduce antibiotic use to all sectors and all species, both in human and veterinary medicine.

Co-resistance to Amoxicillin and Tetracycline as an Indicator of Multidrug Resistance in Escherichia coli Isolates From Animals.

OBJECTIVES: To examine the relevance of co-resistance to amoxicillin and tetracycline as an indicator of multidrug resistance (MDR) in animal health. METHODS: Escherichia coli isolates collected between 2012 and 2016 by the French surveillance network for antimicrobial resistance in diseased animals (RESAPATH) were analyzed. The proportions of MDR isolates and the proportions of isolates presenting co-resistance to amoxicillin and tetracycline were calculated for seven animal species (cattle, horse, dog, swine, poultry, duck, and turkey). The degree of agreement between these two proportions was estimated by calculating the kappa value. RESULTS: In total, 55,904 isolates were analyzed. MDR proportions were variable among animal species, ranging from 21.9% [20.2; 23.7] in horses to 56.0% [55.4; 56.7] in cattle. A similar situation was observed for proportions of isolates with co-resistance to amoxicillin and tetracycline, with the highest value for cattle 65.0% [64.3; 65.6]. This co-resistance was also most often associated with resistance to other antibiotics, regardless of the animal species considered. Comparative analysis showed substantial agreement between MDR and this co-resistance, with a kappa value of 0.75, all animal species considered. CONCLUSION: Given the widespread use of penicillins and tetracyclines in animal health, co-resistance to amoxicillin and tetracycline could be an efficient indicator of MDR in E. coli isolates. Based on a specific resistance profile and not an arbitrary number of resistances compared with MDR, this potential indicator is also precise, convenient and suitable for routine use.

Antimicrobial resistance of Pasteurella multocida isolated from diseased food-producing animals and pets.

Surveillance of Pasteurella multocida resistance in food-producing animals is essential to guide the first-line treatment of respiratory diseases and to limit economic losses. Since Pasteurella are the most common bacteria isolated from dog and cat bites, this surveillance is also needed to guide treatment in humans in case of bites. The aim of this study was to characterize the phenotypic resistance of P. multocida strains isolated from respiratory infections in animals, including both food-producing animals and pets. Data collected between 2012 and 2017 by the French national surveillance network for antimicrobial resistance referred to as RESAPATH were analyzed. The proportions of resistance to antimicrobials of relevance in veterinary and human medicines were estimated for each animal species. For cattle, resistance trends over the period were investigated using non-linear analysis applied to time-series. In total, 5356 P. multocida isolates were analyzed. Proportions of resistance of P. multocida were almost all below 20% over the period, and, more precisely, all resistance proportions were below 10% for rabbits, sheep and dogs. The highest resistance proportions to enrofloxacin were identified for cattle (4.5%) and dogs (5.2%). Despite its frequent use in livestock, resistance to florfenicol was less than 1% in P. multocida strains, regardless of the animal species considered. Time series analyses revealed continuous increases in resistance to tetracycline, tilmicosin, flumequine and fluoroquinolones in P. multocida strains isolated from cattle. These trends contrast with the decrease in use of antibiotics in cattle in France and with the decrease in resistance observed in E. coli isolated from diseased cattle.

Antimicrobial Usages and Antimicrobial Resistance in Commensal Escherichia coli From Veal Calves in France: Evolution During the Fattening Process.

Extended-Spectrum-Cephalosporin (ESC)-resistant Enterobacteriaceae have widely spread in all settings worldwide. In animals, Extended-Spectrum Beta-Lactamase (ESBL) producers have been frequently identified in veal calves. The objectives of this study were to investigate the trends in the ESBL load and antimicrobial resistance (AMR) proportions, and antimicrobial usages (AMU) in veal calves during the fattening process. Ten fattening farms were selected and 50 animals per farm were sampled. AMR was assessed in bacteria from the dominant flora (collected on non-selective MacConckey agar) and in ESBL/AmpC-carrying bacteria from the subdominant flora (selected on ChromID ESBL selective plates) upon arrival and 5-6 months later before slaughter. The number and types of treatments during fattening were also collected. Rates of ESBL-producing E. coli from the subdominant flora significantly decreased in all farms (arrival: 67.7%; departure: 20.4%) whereas rates of multidrug-resistant E. coli from the dominant flora have significantly increased (arrival: 60.2%; departure: 67.2%; p = 0.025). CTX-M-1 was the most frequently identified ESBL enzyme (arrival: 59.3%; departure: 52.0%). The plasmid-mediated mcr-1 gene was also identified occasionally. In parallel, levels of resistances to non-critically important antimicrobials were already high upon arrival but have still further increased over time until slaughter. Our study also highlighted that if only ESBL-producing isolates were monitored, it might have led to a partial (and partly false) picture of AMR rates globally decreasing during the fattening period. The mean number of antimicrobial treatments per calf (NTPC) was 8.75 but no association between AMU and AMR was evidenced. Most ESBL producers were clonally unrelated suggesting multiple sources and not cross-contaminations among calves during transportation. Feeding milk containing antimicrobial residues to veal calves is hypothesized to explain the high ESBL loads in animals at the entrance on farms.

Impact of heat and cold waves on female cattle mortality beyond the effect of extreme temperatures.

Although heat and cold temperatures are known to have an impact on cattle mortality, no study has evidenced and quantified the influence of the prolonged exposure to extreme temperatures beyond the single effect of daily temperatures. We defined a heat (or cold) wave by a continuous variable indicating the number of successive days with temperatures above (or below) a given threshold. For heat wave, the threshold was set to the 95th or 99th percentile of the mean daily temperature distribution and for cold wave to the 1st or 5th percentile. We collected female cattle mortality data by type of production and age classes between 2001 and 2015 for 100 iso-hygro-thermal areas in France. We used time-series analyses to estimate the area-specific heat wave- and cold wave-mortality relationships. Then, we applied meta-analyses to pool area-specific effects at the country level for each definition of heat and cold wave. For each type of production and age classes, our models predicted symmetrical relationships between temperature and mortality, with a temperature range of minimum mortality located approximately between 15 and 20 °CTHI in most categories. Outside that range, relative risks between 1.3 and 2.5 were estimated for extreme cold temperatures and relative risks between 1.1 and 1.5 were estimated for extreme hot temperatures depending on age categories and production type. Our results indicated that a prolonged exposure to high (or low) temperatures caused a significant increase on mortality (up to 40% during heat waves and 23% for cold waves, depending on type of production and age classes), in addition to the effect of extreme temperature alone. This additional mortality risk increased along with the duration and intensity of the exposure. Our results suggest that not discriminating the effect of the prolonged exposure to extreme temperature, may overestimate the effect of temperature alone on mortality.

Why do veterinarians ask for antimicrobial susceptibility testing? A qualitative study exploring determinants and evaluating the impact of antibiotic reduction policy.

For public health reasons, increasing attention has focused on more rational use of antimicrobials in farm animals. Guidance concerning the prescription of antibiotics and antimicrobial susceptibility testing (antibiograms in this case) are beneficial tools to help control the development of antimicrobial resistance. Nevertheless, even though there are already several qualitative studies analysing the determinants of antimicrobial prescription and use in veterinary medicine, little is known about decision-making concerning the use of antibiograms. The aim of this study was to provide a better understanding of veterinarians' motivations and role-players' influence concerning the choice of whether to ask for an antibiogram in the bovine, porcine, poultry and equine sectors in France. We concurrently evaluated the impact of a new French decree (2016) requiring an antibiogram before certain critically important antimicrobial agents can be used in veterinary medicine. Semi-structured interviews with veterinarians were conducted in France. Thematic analysis was used to analyse transcripts. In all, we surveyed 66 veterinarians. Use of antibiograms in veterinary medicine was multifactorial - 46 factors grouped into 11 categories were identified - and differed between animal sectors: use was almost systematic in poultry, frequent in pigs and rare in both the bovine and equine sectors. The decree has not increased the use of antibiograms but has induced a change in prescriptions due to field constraints and the time needed to obtain the results of antibiograms. Respondents see the decree as an aid in promoting responsible and rational use of antibiotics, fostering the use of alternatives. Our findings provide the basis of veterinarians' position regarding antibiogram use and antimicrobial resistance, pointing out levers to facilitate the use of antibiograms in veterinary medicine (for example communication on the benefits of this test and external financial support). Furthermore, the evaluation of the impact of the decree aimed at reducing the use of critically important antibiotic highlights key factors for a successful change in regulations, such as advance planning, precise and adapted communication, and demonstration of the measure's legitimacy. These results will be useful in guiding representative veterinary bodies and regulatory authorities during their decision-making, communication, and policy and regulation choices to combat antimicrobial resistance.

Comparative epidemiology of E. coli resistance to third-generation cephalosporins in diseased food-producing animals.

Categorized by WHO as critically important antibiotics, third-generation cephalosporins (3GCs) are one of the latest therapeutic alternatives to fight severe infectious diseases in humans. Some antibiotics belonging to this class are prescribed to treat food-producing animals in specific pathological contexts. Preserving the effectiveness of 3GCs requires characterization and careful monitoring of 3GCs resistance and the identification and implementation of measures that can limit this antimicrobial resistance (AMR). Here, we characterized the 3GCs resistance in Escherichia coli isolated from diseased animals. Using data collected from broilers, hens, calves, piglets, sows, turkeys and ducks between 2006 and 2016 by the French surveillance network of AMR in pathogenic bacteria of animal origin (called RESAPATH), we investigated the dynamics of resistance to 3GCs. Our non-linear analysis applied to time series showed that the evolution of E. coli resistance to 3GCs is specific to each animal category. From 2006 to 2010, resistance to 3GCs increased for most animal categories. We observed peaks of high-level of resistance for hens (21.5% in 2010) and broilers (26.7% in 2011), whereas trends stayed below 10% for the other animal categories throughout the study period. Resistance later decreased and, since 2014, 3GCs resistance has dropped below 10% for all animal categories. The parallel between trends and measures to limit AMR over the period shed lights on the impact of practices changes, public policies (EcoAntibio Plan) and sector-led initiatives (moratorium in swine sector). Finally, they highlight the usefulness and importance of AMR surveillance networks in animal health, such as RESAPATH.

Antimicrobial resistance in bacteria isolated from mastitis in dairy cattle in France, 2006-2016.

In dairy cattle, mastitis is the most frequent bacterial disease, and the routine use of antibiotics for treatment and prevention can drive antimicrobial resistance (AMR). The aim of our study was to estimate the levels of AMR of the 3 main bacteria isolated from dairy cattle with mastitis in France (Streptococcus uberis, Escherichia coli, and coagulase-positive staphylococci) and to investigate their changes over time. Data collected between 2006 and 2016 by the French surveillance network for AMR in pathogenic bacteria of animal origin (called RESAPATH) were analyzed. The proportions of mono- and multidrug resistance were calculated and the trends were investigated using nonlinear analyses applied to time series. Over the whole period, the lowest proportions of resistance in S. uberis isolates were observed for oxacillin (2.2%) and gentamicin (2.4%) and most resistance levels were below 20%. The trends in resistance showed some significant variation, mainly for S. uberis, but without a common pattern across the various antibiotics examined. For only 2 combinations of bacteria-antibiotic the trend in resistance showed a continuous increase from 2006 to 2016: tetracycline resistance in S. uberis isolates and third-generation cephalosporin resistance in E. coli isolates. In E. coli, the highest proportions of resistance were observed for amoxicillin (28.1%) and tetracycline (23.1%). Resistance to third-generation cephalosporins in E. coli from dairy cattle was almost nil in 2006, but reached 2.4% in December 2016. This increase is particularly concerning because these antibiotics constitute one of the latest therapeutic alternatives to fight severe infectious diseases in humans. Except for penicillin (33.9%), the proportions of resistance in coagulase-positive staphylococci were below 11% during the whole study period. Multidrug resistance (isolates with acquired resistance to at least one antibiotic in 3 or more antibiotic classes) ranged from 2.4% for coagulase-positive staphylococci to 9.9% for S. uberis. These findings can serve as guidelines for practitioners in the choice of the most appropriate antibiotic according to the prevailing epidemiological context. Ultimately, our results contribute to risk assessment of AMR and provide a baseline for setting up and evaluating control measures and designing strategies to limit AMR.

Iso-population partition: An innovative epidemiological approach to mapping and analyzing spatially aggregated data.

In epidemiology, data are often aggregated using administrative boundaries or regular spatial lattices. Iso-population partitioning methods allow the aggregation of small units for which population data are available into larger units that are contiguous, as compact as possible, and have a similar population size. The objective of this paper was to study the influence of three spatial data aggregation approaches on data visualization and data analysis: iso-populated units (IPUs), administrative units, and iso-geometric units. This study was conducted using results and simulations from the brucellosis clinical surveillance system for dairy cattle in France. Our findings indicate that using spatial partitioning methods for generating IPUs enhances the ability to interpret the spatial distribution of epidemiological indicators under study. In addition, it provides information on population density and improves the consistency of the power of statistical tests across units. By defining the target population size per spatial unit, IPUs can be used to control the statistical power of a study. Finally, by adding criteria based on environmental factors to generate spatial units, they can be used to control the variation of exposure to these factors within the units.

Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records.

We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events.

An optimal cut-off point for the calving interval may be used as an indicator of bovine abortions.

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.

Quantifying the influence of ambient temperature on dairy and beef cattle mortality in France from a time-series analysis.

In the context of climate change, the frequency and severity of extreme weather events are expected to increase in temperate regions, and potentially have a severe impact on farmed cattle through production losses or deaths. In this study, we used distributed lag non-linear models to describe and quantify the relationship between a temperature-humidity index (THI) and cattle mortality in 12 areas in France. THI incorporates the effects of both temperature and relative humidity and was already used to quantify the degree of heat stress on dairy cattle because it does reflect physical stress deriving from extreme conditions better than air temperature alone. Relationships between daily THI and mortality were modeled separately for dairy and beef cattle during the 2003-2006 period. Our general approach was to first determine the shape of the THI-mortality relationship in each area by modeling THI with natural cubic splines. We then modeled each relationship assuming a three-piecewise linear function, to estimate the critical cold and heat THI thresholds, for each area, delimiting the thermoneutral zone (i.e. where the risk of death is at its minimum), and the cold and heat effects below and above these thresholds, respectively. Area-specific estimates of the cold or heat effects were then combined in a hierarchical Bayesian model to compute the pooled effects of THI increase or decrease on dairy and beef cattle mortality. A U-shaped relationship, indicating a mortality increase below the cold threshold and above the heat threshold was found in most of the study areas for dairy and beef cattle. The pooled estimate of the mortality risk associated with a 1°C decrease in THI below the cold threshold was 5.0% for dairy cattle [95% posterior interval: 4.4, 5.5] and 4.4% for beef cattle [2.0, 6.5]. The pooled mortality risk associated with a 1°C increase above the hot threshold was estimated to be 5.6% [5.0, 6.2] for dairy and 4.6% [0.9, 8.7] for beef cattle. Knowing the thermoneutral zone and temperature effects outside this zone is of primary interest for farmers because it can help determine when to implement appropriate preventive and mitigation measures.

Devising an indicator to detect mid-term abortions in dairy cattle: a first step towards syndromic surveillance of abortive diseases.

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 departements. 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.

Quantitative and qualitative assessment of the bovine abortion surveillance system in France.

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.

Prevalence of carriage of Shiga toxin-producing Escherichia coli serotypes O157:H7, O26:H11, O103:H2, O111:H8, and O145:H28 among slaughtered adult cattle in France.

The main pathogenic enterohemorrhagic Escherichia coli (EHEC) strains are defined as Shiga toxin (Stx)-producing E. coli (STEC) belonging to one of the following serotypes: O157:H7, O26:H11, O103:H2, O111:H8, and O145:H28. Each of these five serotypes is known to be associated with a specific subtype of the intimin-encoding gene (eae). The objective of this study was to evaluate the prevalence of bovine carriers of these "top five" STEC in the four adult cattle categories slaughtered in France. Fecal samples were collected from 1,318 cattle, including 291 young dairy bulls, 296 young beef bulls, 337 dairy cows, and 394 beef cows. A total of 96 E. coli isolates, including 33 top five STEC and 63 atypical enteropathogenic E. coli (aEPEC) isolates, with the same genetic characteristics as the top five STEC strains except that they lacked an stx gene, were recovered from these samples.O157:H7 was the most frequently isolated STEC serotype. The prevalence of top five STEC (all serotypes included) was 4.5% in young dairy bulls, 2.4% in young beef bulls, 1.8% in dairy cows, and 1.0% in beef cows. It was significantly higher in young dairy bulls (P<0.05) than in the other 3 categories. The basis for these differences between categories remains to be elucidated. Moreover,simultaneous carriage of STEC O26:H11 and STEC O103:H2 was detected in one young dairy bull. Lastly, the prevalence of bovine carriers of the top five STEC, evaluated through a weighted arithmetic mean of the prevalence by categories, was estimated to 1.8% in slaughtered adult cattle in France.

Assessment of Adhesins as an Indicator of Pathovar-Associated Virulence Factors in Bovine Escherichia coli.

The CS31A, F17, and F5 adhesins are usually targeted by serology-based methods to detect pathogenic Escherichia coli associated with calf enteritis. However, the virulence traits of the selected isolates are still poorly described. Here, from a set of 349 diarrheagenic E. coli isolates from cattle, we demonstrated a 70.8% concordance rate (Cohen's kappa, 0.599) between serology- and PCR-based approaches for the detection of adhesins under field conditions. A 79% to 82.4% correspondence between the two methods was found for fimbrial adhesins, whereas major discrepancies (33%) were observed for CS31A-type antigens. Various F17A variants were found, such as F17Ac (20K) (50%), F17Aa (FY) (18.9%), F17Ab (8.1%), and F17Ad (111K) (5.4%), including a high proportion (17.6%) of new F17A internal combinations (F17Aab, F17Aac, and F17Abc) or untypeable variants. In addition, the highest proportion of pathovar-associated virulence factor (VF) genes was observed among E. coli isolates that produced F5/F41 adhesins. A specific link between the heat-stable toxins related to the enterotoxigenic E. coli (ETEC) pathovar and adhesins was identified. STa was significantly linked to F5/F41 and EAST1 to CS31A adhesins (P < 0.001), respectively, whereas NTEC was associated with F17 adhesin (P = 0.001). Clustering between phylogroups according to the adhesin types was also observed. Also, few Shiga toxin-producing E. coli (STEC) or enteropathogenic E. coli (EPEC) pathovars were identified. Finally, no statistically significant difference was observed in the occurrence of extended-spectrum beta lactamase (ESBL) production according to the adhesins expressed by the isolates (P = 0.09). Altogether, this study gives new insights into the relationship between adhesins, VF, and antimicrobial resistance in calf enteritis and supports the need for further standardization of methodologies for such approaches.

Construction of standardized surveillance indicators for bovine cysticercosis.

Bovine cysticercosis is a zoonotic parasitic disease due to Cysticercus bovis. This study aimed to identify factors that could have an impact on the prevalence of cysticercosis and to use them to build standardized indicators of prevalence. Multivariate logistic regression analyses were performed on data from 4,564,065 cattle (91.3% of the cattle population slaughtered in France in 2010) among which 6491 cattle (0.14%) were found to harbor at least one lesion of cysticercosis (including 611 cattle harboring viable cysts, 0.01%). Two multivariate logistic models were fit to the data using as outcome variables either the presence or absence of viable cysts and the presence or absence of cysts whatever their level of development. Age and sex were identified as the main factors influencing bovine cysticercosis prevalence and were used for the construction of standardized prevalence and standardized cysticercosis rate. To illustrate the use of such indicators, they were calculated for the first and second semester of 2010 and for two different areas in France. The differences between raw prevalence and standardized prevalence highlight the use of standardized indicators for comparisons of prevalence between different areas and time periods as the structure of the slaughtered populations differ considerably from one to another.

Factors associated with offal, partial and whole carcass condemnation in ten French cattle slaughterhouses.

The proportion of cattle with offal, partial or whole carcass condemnation could be a useful indicator for animal health syndromic surveillance purposes. It requires first highlighting the factors associated with condemnation in order to include them in a modeling process. This study aims to identify and quantify these factors. It was based on data from ten French cattle slaughterhouses from 2006 to 2010 (n=1,439,868 cattle). Multivariable multinomial logistic regression analyses were performed. Sex, age and slaughterhouse were the main effects for offal, partial and whole carcass condemnation and have to be taken into account when implementing syndromic surveillance systems based on meat inspection data. The presence of an error in cattle identification was identified as a potential indicator for a higher risk of condemnation and should be explored as a potential factor for risk-based meat inspection.