# The use of antibiotics in cattle livestock in the north Benin, a real factor of the development of bacterial resistance in the cattle and the food chain

Robert Sèmanou Dognon<sup>1,2</sup>, Nicolas Antoine-Moussiaux<sup>3</sup>, Pascal Gustin<sup>4</sup>, Nassim Moula<sup>3</sup>, Marie-Louise Scippo<sup>1</sup>, Issaka Youssao Abdou Karim<sup>2</sup>

<figure><img src="image_53.png" /></figure>

robertdognon@yahoo.fr

## Objective

The aim of this study is to inventory different antibiotics used in cattle livestock in north Benin and assess risk practices that could be the cause of both food chain contamination by antibiotic residues and selection of antibiotic-resistant bacteria in animals and humans.

## Methods

This survey was conducted from September to November 2015 in the departments of Borgou and Alibori located in north Benin. The process of "snowball sampling" was used to choose 98 cattle farmers in the two best cattle breeding Commons of each department. The first responders breeders were chosen by the publics veterinaries which used like "keys informants". Semi-structured interviews were conducted following the themes: farmer status, breeding system, antibiotics and use practices. Descriptive statistics were performed with Excel software while multiple correspondence analysis (MCA) and hierarchical classification analysis (HCA) were performed with R (version 3.2.5) to establish a typology of cattle breeders following theirs practices.

## Results

Seventy-one percent of the interviewed farmers were "Fulani" and most of them were uneducated (97 %). The breeding was the main activity of 72 % of them. Cattle herds were composed by the breed "Borgou" (76,4 %) and the breed "Zebu Peul" (16 %) ; some herds were composed by both these two breeds (7,6 %). Antibiotics groups used in cattle breeding were tetracyclines, beta-lactams, sulfonamides, aminoglycosides and macrolides by respectively 100, 88, 56, 44 and 35 % of the interviewed farmers. These pharmaceuticals were purchased in local market (58 %) and veterinary pharmacy (39 %). They were used by these farmers against bacterial diseases (respiratory, podal, mastitis, omphalitis and neonatal enteritis diseases) and skin diseases (nodules, alopecia, etc.). Further, only 49 % of farmers seek veterinary services to treat animals and 93 % of them did not respect the withdrawal time of each antibiotic before eating or selling the foods from treated animals. Using the Multiple Correspondence Analysis, farmers were classified in three groups: high-risk, medium and low risk group.

## Conclusion

Antibiotics are used by one hundred percent of the interviewed farmers and tetracyclines and beta-lactams were the most used antibiotics in this study area. Antibiotics as used to treat all kind of symptoms, including diseases not caused by bacteria (i.e. skin diseases). These practices suggest a high risk of contamination of bovine milk and meat with antibiotics residues, as well as selection of antibiotic-resistant bacteria, and consequently adverse health effects on consumers. These practices could be explained by lack of supervision and control of the animal production chain in this region and in Benin in general.

**Keywords:** Survey ; cattle farmers ; antibiotics ; bacterial resistance ; Benin

<footnote n="1">¹ Department of Food Sciences, Laboratory of Food Analysis, Faculty of Veterinary Medicine, Fundamental and Applied Research for Animals & Health (FARAH), Veterinary Public Health, University of Liège (ULg) - Belgium</footnote>

<footnote n="2">² Department of Animal Production and Health, Laboratory of Animal Biotechnology and Meat Technology, Polytechnic School of Abomey-Calavi, University of Abomey-Calavi (UAC) - Benin</footnote>

<footnote n="3">³ Tropical Veterinary Institute, Fundamental and Applied Research for Animals & Health (FARAH), Sustainable Animal Production, Faculty of Veterinary Medicine, University of Liege (ULg) - Belgium</footnote>

<footnote n="4">⁴ Department of Functional Sciences, Unit of Pharmacology, Faculty of Veterinary Medicine, University of Liège (ULg) - Belgium</footnote>
# High prevalence of Antimicrobial resistance among Escherichia coli isolated from day old broiler chicks in Mostaganem province, northwestern Algeria

Qada Benameur <fnref n="1" />, <fnref n="2" />, Meki Boutaiba Benklaouz <fnref n="3" />, Meriem-Hind Benmahdi <fnref n="2" />

benameurkada@hotmail.fr

## Background

The evolution of antimicrobial resistance is a multifaceted issue that is influenced by numerous factors. The overutilisation and inappropriate use of antimicrobials is a critical stimulant in the promotion of antimicrobial resistance. High rates of Antimicrobial resistance have been also observed already before treatment, for a longer period after treatment, or in the absence of treatment.

## Objective

The aim of this study was to evaluate the prevalence of multidrug-resistant *E. coli* isolated from day old broiler chicks that had not been treated with antimicrobials before.

## Methods

In this study, 120 samples of day old broiler chicks were collected from three broiler hatcheries situated in Mostaganem province, Algeria, from January 2012 to April 2014. After isolates identification, antibiotic susceptibility testing was performed by disk-diffusion method on Mueller-Hinton agar. The isolates were tested against a panel of 16 antimicrobials commonly used in veterinary and human medicine. Results were interpreted according to Clinical and Laboratory Standards Institute guidelines

## Results

In total, 142 starins were isolated in this work. We detected a high prevalence of resistance to drugs such as ampicillin, tetracycline, nalidixic acid, enrofloxacin, and trimethoprim-sulfamethoxazol in *E. coli* isolates from untreated day old broiler chicks. All *E. coli* isolates were resistant at least to three antibiotics, and 90% of the isolates were resistant at least to five antibiotics.

## Conclusions

Other factors must therefore play an important role. Interventions minimizing multi-drug resistant bacteria in broilers should focus on preventing horizontal and vertical spread.

**Keywords:** Escherichia coli ; day old broiler chicks ; Antimicrobial resistance ; Algeria

<footnote n="1">¹ Département des sciences infirmières, Faculté des sciences de la nature et de la vie, Université Abd El-Hamid Ibn Badis, Mostaganem, Algeria</footnote>

<footnote n="2">² Laboratoire de recherche santé et production animale, Ecole nationale supérieure vétérinaire d'El-harrach, Algiers, Algeria</footnote>

<footnote n="3">³ Institut des sciences vétérinaires, Université Ibn Khaldoun, Tiaret, Algeria</footnote>
<figure><img src="image_54.png" /></figure>

Association d'Epidémiologie et de Santé Animale

Wildlife diseases
# Keynote lecture

## TB epidemiology in Europe: past, present and future of a multi-host infection

### Christian Gortázar

SaBio research group at IREC, Universidad de Castilla - La Mancha & CSIC, Ciudad Real, Spain.
www.SaBio-IREC.com

Christian Gortazar (San Sebastián, 1967) is Professor at IREC, a multidisciplinary wildlife research institute belonging to CSIC and Universidad de Castilla - La Mancha in Ciudad Real, Spain (http://www.sabio-irec.com/). His research interests include viral, bacterial and parasitic diseases of wildlife, with emphasis on the epidemiology and control of relevant diseases shared with livestock and humans, such as tuberculosis.

<figure><img src="image_55.png" /></figure>

Christian.Gortazar@uclm.es

<figure><img src="image_56.png" /></figure>

The *Mycobacterium tuberculosis* complex (MTC) is a group of multi-host pathogens thriving at the wildlife-livestock interface. The disease, animal tuberculosis (TB), is due to infection with *Mycobacterium bovis* and other closely related members of the MTC, such as *Mycobacterium caprae*. This presentation addresses TB and TB control in Europe in different time periods, underlining epidemiological aspects that are important for understanding infection dynamics and eventually succeeding in disease control.

## Animal tuberculosis in the past

Prior to milk pasteurization and other improvements, zoonotic TB (the disease caused by non-*Mycobacterium tuberculosis* members of the MTC transmitted from animals to humans) was frequent, mainly through raw milk consumption or close contact to infected animals. In Great Britain, in the 1930s, about 40% of all cattle slaughtered in public abattoirs had TB lesions and about 0.5% of all dairy cows produced milk containing tubercle bacilli (Collins and Grange, 1983). Hence, zoonotic TB was historically the main driver of the onset of TB control in cattle (Bezos et al. 2014).

Interestingly, the basis of the current eradication programmes is still a reagent (tuberculin) developed in 19th century by Koch and initially conceived for the cure of the disease (Good and Duignan 2011). An often used synonym for animal TB is “bovine TB”, indicating the historical bias towards cattle as the main and sometimes the only animal host regarded as epidemiologically relevant for TB maintenance. In fact, the main target host of TB (and of TB control) is cattle.

The fight against cattle TB started as early as the 1940’s as voluntary tuberculin-based test and slaughter schemes, and started to become compulsory in the 1950’s, although initially with great variability among European countries (Bezos et al. 2014, Robinson 2015). In France for instance, the bovine TB eradication programme became compulsory throughout the country by 1965. The TB prevalence in French cattle herds decreased from 13% in 1965 to 1.5% in 1980 and then to <0.1% in 2000 (Bekara et al. 2016).

## The present: why is TB important - and are we controlling it?

Nowadays, animal TB control is considered globally important for public health, economics and conservation. It often causes extra-pulmonary disease in humans and is still a major public health concern in developing countries (Dürr et al. 2013). In industrialized countries, the main reason for TB control is economic: cattle TB results in severe losses due to trade restrictions and slaughter compensations for test-positive animals (Amanfu 2006). Finally, TB is also of concern for conservation, since it can be transmitted to endangered predators and since TB-mediated conflicts can affect animal health and conservation strategies in and around protected natural areas (Gortázar et al. 2015).

In Europe, cattle are still the main MTC reservoir for cattle. In Spain, cattle-related factors explain 70% of the TB breakdowns in cattle herds (Guta et al. 2014), although locally the relevance of other factors is larger (LaHue et al. 2016).

In Ireland, the main risk factors for cattle presenting with a confirmed TB lesion at slaughter are cattle-related, too, e.g. previous MTC exposure history, herd movements and herd size. Hence, there is a need to keep on improving test strategies, and it will be most helpful to reconsider the importance of abattoir surveillance (Clegg et al. 2016). A recent review suggests that, “when multiple cost and benefit components are taken into account, efforts to control or eradicate bovine TB may be effective in reducing disease prevalence, economically viable and worth doing” (Caminiti et al. 2016).

However, the total eradication of cattle TB remains unlikely if the role of all hosts is not clear enough for all relevant reservoirs to be targeted at the same time (O'Reilly & Daborn 1995, Gortázar et al. 2015). Regarding TB in Europe, the group of suitable MTC maintenance hosts is broad, and includes (along with cattle) other domestic animals such as pigs, goats and sheep, as well as several wild hosts including the badger (*Meles meles*), the Eurasian wild boar (*Sus scrofa*), the red deer (*Cervus elaphus*) and other members of the subfamily cervinae (Gortázar et al. 2015 and references therein). In this context, MTC is more likely to survive in complex host communities, where a network of hosts facilitates pathogen survival despite control efforts directed towards only one or two of those host species. In addition, recent research evidences that the environment, e.g. surface water, mud and earthworms also contributes to MTC circulation (Santos et al. 2015, Barasona et al. 2016, Barbier et al. 2016). This, along with recent information on the low frequency of direct
inter-species contacts (Cowie et al. 2016), points towards indirect (environment-mediated) contacts between host species as the main means of MTC circulation in natural systems (Barasona et al. 2014).

## An outlook into the future of animal TB control in Europe

Returning to the French example, it is estimated that there are annually less than 1000 MTC infected individual cattle in the country (L. Boschiroli, pers. comm.). However, there are about two million wild boar in France (>500,000 are hunter harvested yearly), and the minimum prevalence of antibodies against MTC is 2.2% (at the most conservative cut-off; Richomme et al. 2013). Hence, there are about 44,000 TB+ wild boar in the country, 44 times more than cattle – and this elucubration does not consider other hosts such as badgers, red deer, pigs, goats and sheep. The reason for giving this example, which could easily be extrapolated to other European countries, is to insist that in the future TB control will need to expand the focus from controlling “bovine TB” towards controlling animal TB.

New tools will probably help in this endeavor. In the epidemiology field, new approaches for studying MTC transmission networks are granting better insights into complex wildlife-livestock-environment systems (e.g. Barasona et al. 2014, Cowie et al. 2016), and whole genome sequencing allows inferring directionality in MTC transmission (e.g. Trewby et al. 2016). Regarding intervention, much effort is being put in fields such as farm biosafety and wildlife vaccination, among others (Gortázar et al. 2015b).

Acknowledgements: Research on TB at SaBio is partly funded by Plan Nacional AGL2014-56305.

## References

* Amanfu W (2006). The situation of tuberculosis and tuberculosis control in animals of economic interest. Tuberculosis 86: 330-335.

* Barasona JA, Latham MC, Acevedo P, Armenteros JA, Latham DM, Gortazar C, Carro F, Soriguer RC, Vicente J (2014). Spatiotemporal interactions between wild boar and cattle: implications for cross-species disease transmission. Veterinary Research 45:122.

* Barasona JA, Torres MJ, Aznar J, Gortázar C, Vicente J (2016). DNA detection reveals Mycobacterium tuberculosis complex shedding routes in its wildlife reservoir the Eurasian wild boar. Transboundary and Emerging Diseases. In press.

* Barbier, E., Chantemesse, B., Rochelet, M., (...), Boschiroli, M.L., Hartmann, A. (2016). Rapid dissemination of M. bovis from cattle dung to soil by the earthworm Lumbricus terrestris. Veterinary Microbiology 186: 1-7.

* Bekara M.E.A., Azizi L., Benet JJ, Durand, B. (2016). Spatial-temporal Variations of Bovine Tuberculosis Incidence in France between 1965 and 2000. Transboundary and Emerging Diseases 63: 101-113.

* Bezos, J., Álvarez, J., Romero, B., de Juan, L., Domínguez, L. (2014). Bovine tuberculosis: Historical perspective. Research in Veterinary Science 97: S3-4.

* Caminiti, A., Pelone, F., La Torre, G., De Giusti, M., Saulle, R., Mannocci, A., Sala, M., Della Marta, U., Scaramozzino, P. (2016). Control and eradication of tuberculosis in cattle: A systematic review of economic evidence. Veterinary Record 179: 70-75.

* Clegg, T.A., Good, M., More, S.J. (2016). Risk factors for cattle presenting with a confirmed bTB lesion at slaughter, from herds with no evidence of within-herd transmission. Preventive Veterinary Medicine 126: 111-120.

* Collins CH, Grange JM (1983). The bovine tubercle bacillus. The Journal of Applied Bacteriology 55: 13-29.

* Cowie CE, Beck BB, Gortazar C, Vicente J, Hutchings MR, Moran, Piran D, White CL (2014) Risk factors for the detected presence of Mycobacterium bovis in cattle in south central Spain. European Journal of Wildlife Research 60(1): 113-123

* Dürr S, Müller B, Alonso S, Hattendorf J, Laisse CJM, van Helden PD, Zinsstag J (2013). Differences in primary sites of infection between zoonotic and human tuberculosis: results from a worldwide systematic review. PLoS Neglected Tropical Diseases 7: e2399.

* Good M, Duignan A (2011). Perspectives on the history of bovine TB and the role of tuberculin in bovine TB eradication. Veterinary Medicine International 2011: 410470.

* Gortazar C, Che-Amat A, O' Brien D (2015). Open Questions and Recent Advances in the Control of a Multi-Host Infectious Disease: Animal Tuberculosis. Mammal Review 45: 160-175.

* Gortazar C, Diez-Delgado I, Barasona JA, Vicente J, De La Fuente J and Boadella M (2015b). The wild side of disease control at the wildlife-livestock-human interface: a review. Front. Vet. Sci. 1:27.

* Guta S, Casal J, Napp S, Saez JL, Garcia-Saenz A, Perez de Val B, Romero B, Alvarez J, Allepuz A (2014). Epidemiological Investigation of Bovine Tuberculosis Herd Breakdowns in Spain 2009/2011. PLoS ONE 9(8): e104383.

* LaHue NP, Vicente J, Acevedo P, Gortázar C, Martínez-López B (2016). Spatially explicit modeling of animal tuberculosis at the wildlife-livestock interface in Ciudad Real province, Spain. Preventive Veterinary Medicine 126: 000-000.

* O'Reilly LM, Daborn CJ (1995). The epidemiology of Mycobacterium bovis infections in animals and man: a review. Tubercle and Lung Disease 76: 1-46.
Richomme C, Boadella M, Courcoul A, Durand B, Drapeau A, Corde Y, Hars J, Payne A, Fediaevsky A, Boschiroli ML (2013). Exposure of Wild Boar to Mycobacterium tuberculosis Complex in France since 2000 Is Consistent with the Distribution of Bovine Tuberculosis Outbreaks in Cattle. PLoS ONE 8(10): e77842.

Robinson, P.A. (2015). A history of bovine tuberculosis eradication policy in Northern Ireland Epidemiology and Infection
15: 1433182-3195.

Santos N, Santos C, Valente T, Gortázar C, Almeida V, Correia-Neves M (2015b). Widespread Environmental Contamination with Mycobacterium tuberculosis Complex Revealed by a Molecular Detection Protocol. PLoS ONE 10(11): e0142079.

Trewby et al. (2016). Use of bacterial whole-genome sequencing to investigate local persistence and spread in bovine tuberculosis. *Epidemics* 14: 26-35.
Selected oral presentations

Genotyping analysis of Brucella melitensis at the wildlife-livestock-human interface in
the Middle East

Anne-Lise Chaber<fnref n="1" />,<fnref n="2" />, Louis Lignereux<fnref n="1" />,<fnref n="3" />, David Fretin<fnref n="4" />, Sanogo Moussa, Claude Saegerman<fnref n="1" />

<figure><img src="image_57.png" /></figure>

alchaber@hotmail.com

Brucella melitensis has been reported in human and livestock in the Middle East but information on genotypes distribution is scarce. This study aimed to collect all accessible genotypes of human and animal isolates of Brucella melitensis in the ME, analyse the distribution of B. melitensis. in this region, and epidemiologically trace back B. melitensis infection in a large wildlife population of Scimitar Horned Oryx (SHO).

The analysis revealed genetic homogeneity among the isolates with a geographical clustering of genotypes confirmed with only a few exceptions by MLVA-15 analysis. An active animal trade between those countries might explain these results. The captive wildlife population of SHO, extinct in the wild, is at threat with 75% of the 900 SHO screened in 2013 seropositive based on a single rose Bengal test. B. melitensis biovar 1 isolated from oryx foetal stomach content had a similar genetic profile to a goat strain isolated in the UAE in 1998. Although animals are the source of infection to humans, available data are mainly drawn from human cases. Animal epidemiological data will be valuable in reducing opportunities for Brucella to jump host species. Brucella is a neglected disease emerging in some rare and endangered wildlife populations expanding the issue from health and economic to conservation perspectives.

Keywords: Brucella melitensi ; wildlife ; livestock ; human interface ; Middle East

<footnote n="1">¹ Faculty of Veterinary Medicine, University of Liège (UREAR-ULg, FARAH)</footnote>

<footnote n="2">² Wildlife Consultant L.L.C, Al Ain.</footnote>

<footnote n="3">³ Environment Agency Abu Dhabi, Abu Dhabi.</footnote>

<footnote n="4">⁴ CODA-CERVA</footnote>
# Occurrence of Cryptosporidium Oocysts in Edible Frogs (Rana Species) Sold for Human Consumption in Hanwa Frog Market Zaria, Kaduna State, Nigeria

Grace Kia¹, Blessing Ukuma, Jerome Jerome Unubi Okpanachi, Mathias Odoba

¹ Department of Veterinary Public Health and Preventive Medicine, Ahmadu Bello University Zaria Kaduna State Nigeria - Nigeria

<figure><img src="image_58.png" /></figure>

gracegracekia@yahoo.com

## Objective

To evaluate the occurrence of *Cryptosporidium* species in edible frogs (*Rana* spp) sold at the Hanwa frog market Zaria, Kaduna State, Nigeria.

## Methods

*Rana* spp of frogs (n=117), sourced from the wild in 8 different locations were collected between February and April, 2016 from the frog central collection, sales and processing point at Hanwa in Zaria, Kaduna state. The intestinal contents from the frogs were examined by staining flotation and sedimentation smears with modified Ziehl-Neelsen stains followed by microscopy and micrometry of the oocysts.

## Results

Overall, 35.9% of frogs sampled from the Hanwa frog market were positive for *Cryptosporidium* oocysts. There were more *Cryptosporidium* oocysts detected by sedimentation test (28.2%) than flotation test (23.9%). Although there was no significant statistical association between sex of frogs and oocyst detection (χ2 =0.5349, P>0.05); also, no correlation between the weights of frogs and the sizes of the *Cryptosporidium* oocyst detected (r= 0.0109, P>0.05), nevertheless, female frogs (40%) and frogs within the weight range 170-219g were more infected with *Cryptosporidium* (66.7%). Oocysts size ranging between 6.10µm -7.00µm, had the highest frequency of 10 (23.8%). By size 28.2% of the oocysts detected suggested infection with *C. parvum* and *C. maleagridis*.

## Conclusion

This is the first report of *Cryptosporidium* spp occurrence in frogs (*Rana* spp) intended for human consumption which may constitute a health risk for humans especially the immunocompromised individuals. There is therefore need for public education to prevent the possibility of transmission of zoonoses.

**Keywords:** *Cryptosporidium* ; Oocysts ; Edible frogs ; Rana species ; Zoonotic potential
# Occurrence of the new pathogenic variant of rabbit haemorrhagic disease virus (RHDV2) in wild populations of rabbits in Southern Belgium.

Rosario Volpe<fnref n="1" />, Christophe Lesenfants<fnref n="1" />, Julien Paternostre<fnref n="1" />, Thomas Fett<fnref n="1" />, Nadège Tchuenkam Kamdem<fnref n="1" />, Dominique Cassart<fnref n="2" />, Annick Linden<fnref n="1" />

r.volpe@ulg.ac.be

Rabbit haemorrhagic disease (RHD) is a highly infectious and fatal disease of the European rabbit (*Oryctolagus cuniculus*), responsible for important economic losses in the rabbit industry. The aetiological agent of the disease is a RNA virus (RHDV, *Lagovirus, Caliciviridae*) first detected in China in 1984. Currently RHDV is endemic in most parts of Europe, Asia and North Africa. Phylogenetic analyses of RHDV strains have identified 3 distinct groups : the classic RHDV, the variant RHDVa and RHDV2. This latter has been detected in France for the first time in 2010 in domestic and wild rabbits (Le Gall-Reculé G et al., 2013) and since then has spread throughout Europe, replacing the circulating RHDV/RHDVa strains in most european countries. RHDV2 has already been detected in Belgium in rabbitries (Marlier D et al., 2014). Here, we report for the first time the presence of RHDV2 in wild rabbits in Southern Belgium.

In november 2015, the Surveillance Network of Wildlife Diseases received seven dead wild rabbits for necropsy. The discovery of 7 fresh carcasses found at the same time in a same area (Hainaut province) emphasised the infectious or intoxication hypothesis as cause of death. *Postmortem* examinations were performed at the Faculty of Veterinary Medicine (FMV) of the University of Liege according to a systematic protocol based on gross lesions, histopathological and targeted microbiological analysis. For necropsy, each rabbit (1) was weighted and age was determined by the presence/absence of the distal ulna protuberance, (2) stomach was investigated to exclude poison, (3) spleen was systematically driven into Yersinia CIN culture media for detection of *Yersinia pseudotuberculosis*, (4) lungs and livers were systematically (a) packaged into 10% formaldehyde solution for histopathology analysis (Service of Pathology, FVM) and (b) frozen at -20°C for RHDV analysis (Scanelis Laboratory, Toulouse, France) and finally (6) feces were gathered for parasitology (Service of Parasitology, FVM).

At necropsy, animals (5 adults: 3 males/2 females and 2 juveniles: 1 male/1 female) were in good condition. No hematomas or broken bones were detected, only one displayed clues of diarrhoea. Examinations of the carcasses showed congestion of lungs/kidneys and livers were macroscopically normal. No foreign body or suspicious particles was seen in the stomachs, only one rabbit was hardly infested by tapeworms in the gut. Histopathological examination revealed haemorragic lung lesions in one animal while 5 of them presented severe necrotic hepatitis, sometimes associated with peri-angiocholitis. Only one animal presented an abnormal high rate of coccidia in feces. Samples of livers were sent to Scanelis Laboratory for RHDV RT-qPCR diagnostic. The results were positive for the new variant RHDV2 in 5 out of the 7 rabbit livers. All the samples were negative for the classic RHDV.

To determine if RHDV2 was already present before 2015 in wild rabbits in the region, we tested a series of livers that had been collected in 2013 and 2014 for a retrospective study. Among the 25 rabbit livers checked, 12 presented necrotic hepatitis and were sent for analysis. Ten were confirmed positive by RT-qPCR for RHDV2.

In conclusion, this is the first report which confirms the presence of RHDV2 in wild populations of rabbits in Southern Belgium. Additional data are needed to strengthen the epidemiological picture and to determine how RHDV2 is spread in other provinces in Southern Belgium.

**Keywords:** rabbit ; calicivirus ; RHDV2 ; hepatitis ; liver

<footnote n="1">¹ Surveillance Network of Wildlife Diseases in Southern Belgium, Faculty of Veterinary Medicine, Sart-Tilman B43A, Quartier Vallée II, Avenue de Cureghem 6 University of Liege, B-4000 Liege, Belgium</footnote>

<footnote n="2">² Morphology and Pathology Department, Faculty of Veterinary Medicine, Sart-Tilman B43A, Quartier Vallée II, Avenue de Cureghem 6 University of Liege, B-4000 Liege, Belgium</footnote>
# Validation of Bayesian prevalence estimation with an imperfect diagnostic test

Matthias Flor<fnref n="1" />, Christine Müller-Graf<fnref n="1" />, Matthias Greiner<fnref n="1" />,<fnref n="2" />

<figure><img src="image_59.png" /></figure>

matthias.flor@bfr.bund.de

## Objective

The generic concept of prevalence is applicable to quantify the proportion of any binary trait in a population such as proportion of diseased individuals in an animal population. Major sources of uncertainty of prevalence estimates are related to the study design and sampling issues and are usually described using the concepts of precision (statistical parameter uncertainty of the estimate) and bias. A typical source of (information) bias is diagnostic misclassification.
We aimed at developing and validating a statistical approach for prevalence estimation and characterization of all uncertainties that are associated with the study data and relevant meta-data such as diagnostic method performance characteristics.

## Methods

We developed a user-friendly, universally applicable Bayesian version of a prevalence estimator that accounts for diagnostic misclassification (based on Rogan and Gladen, 1978). Uncertainty of the estimator in our model is naturally expressed as a 95% credible interval of the posterior prevalence distribution. The model requires input data for the (apparent) prevalence estimate (Ap) along with information on the diagnostic sensitivity (Se) and specificity (Sp) that are available from validation studies of the test or instrument and a prior estimate for the true prevalence.
We validated the model on simulated data sets and compared the bias of the point estimator with the Rogan-Gladen estimate and the (frequentist) coverage of the credible interval with conventional confidence intervals such as Blaker's or Sterne's exact confidence limits and the newly developed method by Lang and Reiczigel (2014).

## Results

Bias distributions of the Bayesian prevalence estimator and the Rogan-Gladen estimate are comparable when applied across the entire simulated data sets. However, for a subset of data sets in which the Rogan-Gladen estimate is negative or larger than one, the Bayesian estimator is generally less biased.

Coverage of Bayesian credible intervals and of Lang-Reiczigel intervals are in good accordance with the nominal value of 95%. This is in stark contrast to conventional confidence intervals which exhibit coverage much lower than 95%, and even more so when the Rogan-Gladen estimate is negative or larger than one.

## Conclusion

Prevalence estimations can easily be adjusted for diagnostic misclassification if the diagnostic performance (sensitivity and specificity) of the test or instrument has been characterized. Furthermore, the use of a Bayesian model is a flexible approach for quantifying the combined uncertainties of all model parameters which can be informed by empirical data or expert opinion.

In a validation study on simulated data sets, Bayesian estimates of the true prevalence and the inherent uncertainty proved superior to traditional frequentist methods, exhibiting less bias than the Rogan-Gladen estimate and better coverage than conventional methods (with the exception of Lang-Reicczigel confidence intervals).

## References

Rogan, Walter J., and Gladen, Beth (1978). Estimating prevalence from the results of a screening test. American Journal of Epidemiology 107: 71-76.

Lang, Zsolt, and Reiczigel, Jenő (2014). Confidence limits for prevalence of disease adjusted for estimated sensitivity and specificity. Preventive Veterinary Medicine 113: 13-22.

**Keywords:** validation ; uncertainty ; prevalence ; Bayesian model ; diagnostic test

<footnote n="1">¹ Federal Institute for Risk Assessment (BfR) - Max-Dohrn-Str. 8-10, 10589 Berlin - Germany</footnote>

<footnote n="2">² Veterinary University Hannover (TiHo) - Bünteweg 2, 30559 Hannover - Germany</footnote>
<figure><img src="image_60.png" /></figure>

Association d'Epidémiologie et de Santé Animale

Participatory
epidemiology

7th - 9th Sept. 2016 - Liège (Belgium)
Congress 25 years

**Animal epidemiology**
Past, present and future
# Keynote lecture

## We need to talk! The added value of participatory epidemiology

Marisa Peyre (Ph.D.), Clémentine Calba, Alexis Delabouglise, Thi Thanh Pham Hoa, François Roger, Flavie Goutard

CIRAD, AGIRs, 34398 Montpellier Cedex 5

Marisa Peyre is an epidemiologist specialized in the evaluation of surveillance and control programs in animal health. She has been working for CIRAD (French Agricultural Research Institute for Development) since 2006 and is currently based in Vietnam where she carries out researches at the regional level in the field of evaluative epidemiology. She is a professional trainer in participatory epidemiology and has been using this approach to improve animal health management strategies in South East Asia and in Europe.

<figure><img src="image_61.png" /></figure>

peyre@cirad.fr

<figure><img src="image_62.png" /></figure>

## Lack of communication : a major issue in animal health surveillance performances

In most region of the world farming systems aim to ensure food security but also poorest communities' livelihood. Issues in disease control strategies and husbandry practices can result in disease introduction and endemic situations. Early detection and control of animal diseases through efficient surveillance system is critical to prevent such issue but also emergence and re-emergence of new pathogens from animals. Despite the efforts undertaken by international organisations and national actors, the effectiveness of most surveillance system remains limited especially in low-income countries (Goutard et al., 2015). Weaknesses in surveillance are inherent in most developed countries. Lack of communication between the different actors from local to national levels result in limited coverage and disease underreporting. The implementation of regular and relevant evaluations of surveillance systems is critical to improve their effectiveness and their relevance whilst limiting their cost. Socio-economic factors could not be ignored within the decision making process of household in animal health management (from poor awareness to fear of penalty or stigmatization and therefore distrust in government authorities) (Delabouglise et al., 2015a, 2015b; Goutard et al., 2015). Often farmers do not perceive how being part of surveillance systems could contribute to improving their livelihoods (Goutard et al., 2015). The complex nature of these systems and the variable contexts in which they are implemented call for the development of flexible evaluation tools. Until recently the tool box available to evaluate animal health surveillance system performances did not take into consideration the context in which surveillance was implemented, and rarely considering the socio-economic aspects of surveillance (Calba et al., 2015).

## How to improve communication and participation of actors in animal health surveillance ?

Participatory epidemiology (PE) proved to be of interest in this respect. Participatory Epidemiology (PE) is a flexible, inexpensive, and effective method for the identification and prioritization of issues within communities (Mariner and Paskin, 2000a). This approach is especially aimed at addressing actors' perception on epidemiologic issues. PE methods are flexible enough to address the wide range of issues, including costs and benefits perceived by actors regarding animal health management systems (Catley et al., 2012). The understanding of individual and local community choices regarding animal disease prevention and control is the key factor in efficiency and sustainability of the prevention system at the local and national levels. Several recent initiatives have demonstrated that a combination of participatory methods and modern technologies could help to overcome the constraint of disease surveillance and not only in low income but also in developed countries (Calba et al., 2016; Calba et al., 2014; Delabouglise et al., 2016, 2015b; Pham et al., 2016). A range of participatory methods and tools were used in order to take into consideration the stakeholders' perceptions and expectations regarding the system and to identify and describe of problems and local solutions at grass root level.

PE has been recently used in South East Asia to assess animal health disease priority and to identify local socio-economic factors impairing animal health surveillance system performances. In Cambodia, Village Animal Health Workers (VAHWs) were directly involved in their own evaluation, using participatory methods to define their main functions and set up their own evolution criteria, leading to the development of a standardised method to evaluate VAHWs competences. Innovative approaches have been developed by combining PE with modeling or econometrics techniques (e.g. discrete choice experiment) to generate information on the animal health disease surveillance process, acceptability, non-monetary costs and benefits; these methods have been used in South East Asia but also transposed and adapted under the European context. Tools such as semi-structured interview, ranking and scoring, visualization, direct observation, allow for in depth information gathering on patterns of animal diseases and identification of community problems related to animal health management. Semi-structured interview with open ended questions allow interviewees to feel free to talk about sensitive topics and issues. Probing questions are used to obtain detail information and check for internal consistency, limiting bias and subjectivity of the data. Ranking and scoring are used to provide semi-quantitative data for disease priorisation, which helped to limit the subjective issue of qualitative assessment. Information obtained from interview could be checked or validated by simple observation by the interviewers of the environment and daily activities of the respondent. Visualization techniques (i.e. mapping) are very useful to get an overview of the area and spatial
relationship between communities social relations and movement patterns. Timelines and seasonal calendar are also powerful to describe temporal patterns of diseases in a location. Proportional piling proven to be a very powerful technique that could be applied in a wide range of veterinary issues to quantify disease incidence and disease impact but also to assess the relative importance of different factors identified. PE approaches also come with a cost and one important limit of PE is the sampling method based on key informants and snowball approach rather than on randomized selection. The respondents often have some knowledge on animal health but with their own perception on animal health surveillance and control linked to their specific socio-cultural, economic, or political context. A deep understanding of these issues involving relevant people actors outside the boundaries of animal health field is thus essential. But this approach is not without its drawbacks. Information obtained from PE is usually qualitative or semi-quantitative and often dismissed point of view of quantitative epidemiologist or mis-trusted by decision makers (Catley, 2005; Mariner and Paskin, 2000b). Bias could also come from the interviewer itself, which need to be trained especially to ensure that the interview is open and not leaded. Strong validation of the methods used for PE data collection and analysis is essential to ensure wider use and uptake of PE generated outputs by decision makers. Internationally recognized training in PE is available trough the Participatory Epidemiology Network for Animal and Public health (PENAPH, https://penaph.net/).

## The added value of PE to improve animal health surveillance and control

Participatory tools allow tackling functional attributes of surveillance systems which are difficult to evaluate and could be highly subjective (e.g. sustainability, acceptability). Such approaches also ensure a better acceptability of the evaluation process itself. This method gives priority to dialog aiming to engage decision makers and other stakeholders in a mutual learning process, developing trust and fostering corrective actions. Such tools allow providing context dependent recommendations for the improvement of the current surveillance system by taking into consideration stakeholders' perceptions and expectations regarding the system. PE proved to be effective to highlight the differences in perception of disease priority for surveillance and monitoring between farmers, local and national level veterinarians. PE was also very useful to identify socio-economic factors underlying the farmer's decisions to report or not report the disease and its implication in terms of disease control at national level. This provides important information for policy makers to improve farmers' acceptability and animal disease surveillance and control systems. Such bottom-up specificity, gathering critical information from the local level (bottom) to inform national policy making (top) are more and more recognized as powerful to ensure sustainable and meaningful changes.

## References

Calba, C., Goutard, F.L., Vanholme L., Antoine Moussiaux N., Hendrikx, P., Saegerman, C., 2016. The added-value of using participatory approaches to assess the acceptability of surveillance systems: the case of bovine tuberculosis in Belgium. PLoS ONE 11(7): e0159041. doi:10.1371/journal.pone.0159041

Calba, C., Goutard, F.L., Hoinville, L., Hendrikx, P., Lindberg, A., Saegerman, C., Peyre, M., 2015. Surveillance systems evaluation: a systematic review of the existing approaches. BMC Public Health 15. doi:10.1186/s12889-015-1791-5

Calba, C., Ponsich, A., Nam, S., Collineau, L., Min, S., Thonnat, J., Goutard, F.L., 2014. Development of a participatory tool for the evaluation of Village Animal Health Workers in Cambodia. Acta Trop. 134, 17-28. doi:10.1016/j.actatropica.2014.02.013

Catley, A., 2005. Participatory Epidemiology: A guide for Trainers.

Delabouglise, A., Antoine-Moussiaux, N., Phan, T.D., Dao, D.C., Nguyen, T.T., Truong, B.D., Nguyen, X.N.T., Vu, T.D., Nguyen, K.V., Le, H.T., Salem, G., Peyre, M., 2015a. The Perceived Value of Passive Animal Health Surveillance: The Case of Highly Pathogenic Avian Influenza in Vietnam. Zoonoses Public Health n/a-n/a. doi:10.1111/zph.12212

Delabouglise, A., Antoine-Moussiaux, N., Tatong, D., Chumkaeo, A., Binot, A., Fournié, G., Pilot, E., Phimpraphi, W., Kasemsuwan, S., Paul, M.C., Duboz, R., Salem, G., Peyre, M., 2016. Cultural Practices Shaping Zoonotic Diseases Surveillance: The Case of Highly Pathogenic Avian Influenza and Thailand Native Chicken Farmers. Transbound. Emerg. Dis. doi:10.1111/tbed.12506

Delabouglise, A., Dao, T.H., Truong, D.B., Nguyen, T.T., Nguyen, N.T.X., Duboz, R., Fournié, G., Antoine-Moussiaux, N., Grosbois, V., Vu, D.T., Le, T.H., Nguyen, V.K., Salem, G., Peyre, M., 2015b. When private actors matter: Information-sharing network and surveillance of Highly Pathogenic Avian Influenza in Vietnam. Acta Trop. 147, 38-44. doi:10.1016/j.actatropica.2015.03.025

Goutard, F.L., Binot, A., Duboz, R., Rasamoelina-Andriamanivo, H., Pedrono, M., Holl, D., Peyre, M.I., Cappelle, J., Chevalier, V., Figuié, M., Molia, S., Roger, F.L., 2015. How to reach the poor? Surveillance in low-income countries, lessons from experiences in Cambodia and Madagascar. Prev. Vet. Med. 120, 12-26. doi:10.1016/j.prevetmed.2015.02.014

Mariner, J., Paskin, R., 2000a. FAO Animal Health Manual. Manual on Participatory epidemiology. Rome 2000.

Mariner, J., Paskin, R., 2000b. Manual on Participatory Epidemiology.

Pham, H.T.T., Antoine-Moussiaux, N., Grosbois, V., Moula, N., Truong, B.D., Phan, T.D., Vu, T.D., Trinh, T.Q., Vu, C.C., Rukkwamsuk, T., Peyre, M., 2016. Financial Impacts of Priority Swine Diseases to Pig Farmers in Red River and Mekong River Delta, Vietnam. Transbound. Emerg. Dis. n/a-n/a. doi:10.1111/tbed.12482
# Selected oral presentations

## Review of Participatory Epidemiology practices in Animal Health (1980-2015)

Alberto Allepuz <fnref n="1" />, Katinka De Balogh <fnref n="2" />, Aguanno Ryan <fnref n="2" />, Martin Heilmann <fnref n="2" />, Jordi Casal <fnref n="1" />, Daniel Beltran-Alcrudo <fnref n="2" />

<figure><img src="image_63.png" /></figure>

alberto.allepuz@uab.cat

## Objectives

The objectives of this study were to undertake an inventory of the major applications, geographic regions and diseases covered by Participatory Epidemiology (PE) activities in the field of animal health since 1980, and to discuss with PE practitioners different issues that deserve clarification.

## Materials and methods

In this study, we combined an inventory of PE activities in the field of animal health classified by major application, geographic region and disease/s covered, together with an email discussion forum with PE practitioners from different regions of the world. The inventory included the search of peer-reviewed papers, master thesis and technical reports, conference proceedings, manuals, training materials and projects. The language used for the search was English. Moreover, focal points at institutions, universities, research groups and non-governmental organizations (NGOs) were contacted. The email discussions were held during a 3-week period (12 to 30 of October 2015), each week discussing a new theme: i) Discussion about PE definitions and examples of its successful application; ii) How to institutionalise PE activities to allow for their use in policy development at various levels and iii) What are the priorities for future PE developments.

## Results

The search resulted in a low number of PE activity results until the year 2000, followed by a considerable increase (especially from 2012). The more common uses of PE activities (excluding manuals and training material) were for 'Surveillance' applications (20%, 39 out of 198), followed by 'Disease survey and prioritization' and 'Evaluation of disease control methods' (16% and 12%, respectively). Most of them targeted multiple diseases (57 out of 207), followed by avian influenza (22 out of 207) and foot and mouth disease (19 out of 207).

Seventy-nine PE practitioners working predominantly in Africa, Asia and Europe (29, 22 and 18 respectively) contributed to the email discussion forum. Issues discussed included: PE definition, the application of PE, its institutionalization for use in policy development, as well as the priorities for future development. One of the most debated issues was the definition of PE, from which we received a total of 58 comments. Based on the proposed modifications to the definition by Catley et al. (2012), we came up with the following modified definition:

> "Participatory epidemiology is the systematic use of approaches and methods that facilitate the empowerment of people to identify and solve their health needs. It should promote the participation of people leading to a shared learning environment that improves the understanding of their risk perception, health risks and options for surveillance, control, and health evaluation in populations. It should be conducted by professionals on equal partnership among all involved in the activity and with mutual respect and trust, ensuring acceptability and a sense of ownership".

## Conclusion

The need to increase the number of PE trained people, together with some methodological developments, exploring avenues to institutionalize PE, and discussing the application in developed countries were points highlighted during the forum and point to the importance of further developing PE as a useful approach for engaging communities in addressing animal and related public health risks.

## References

Catley A, Alders RG, Wood JLN. Participatory epidemiology: approaches, methods, experiences. Vet J. 2012; 191: 151 – 160.

**Keywords:** Participatory epidemiology ; animal health ; veterinary epidemiology

<footnote n="1">¹ Departament de Sanitat i Anatomia Animal, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain</footnote>

<footnote n="2">² Animal Production and Health Division, Food and Agriculture Organization of the United Nations, Vialle delle Terme di Caracalla, 00153 Rome, Italy.</footnote>
# Applying sociological methods to the study of animal diseases: the case of Bovine Tuberculosis in Spain

Giovanna Ciaravino<fnref n="1" />, Sebastian Napp<fnref n="2" />, Alberto Pacios<fnref n="3" />, Irene Mercader<fnref n="4" />, Patricia Ibarra<fnref n="5" />, Ester Casal<fnref n="6" />, Sergi Lopez<fnref n="6" />, Josep Espluga<fnref n="6" />, Jordi Casal<fnref n="1" />, Lourdes Anaya<fnref n="3" />, Alberto Allepuz<fnref n="1" />

<figure><img src="image_64.png" /></figure>

giovanna.ciaravino@uab.cat

## Background

Bovine Tuberculosis (bTb) is characterized by a complex interaction between pathogen, hosts and environment and the drivers of its spread are not always well established. The effectiveness of surveillance and control activities are influenced by a range of biological and non-biological factors operating at different levels (EFSA, 2014). The engagement of stakeholders is one of the key factors for the eradication program's success; however, the influence of social factors is often ignored in the control of animal diseases. Perceptions, attitudes and behaviours of farmers and vets, may have a strong influence on the efficacy of the bTb eradication program. The aim of this study was to explore farmers' and vets' opinions and beliefs that might influence attitudes and behaviour in relation to the bTb eradication program.

## Method

The study was carried out in two Spanish autonomous communities, Andalucía and Catalonia, representing high and low prevalence areas respectively. It included three phases: exploratory interviews, qualitative in-depth interviews and a quantitative survey.

1) Exploratory interviews: aimed to identify the major themes to be considered in the next phase. Key people representative of different groups involved in the bTb program (i.e. farmers and vets) were interviewed. The semi-structured interview focused on strong and weak points of the bTb eradication program; reasons for failure to achieve bTb eradication; benefits of being bTb free; future perspectives and proposed changes to the program.

2) Qualitative interviews: aimed to gain more detailed information on the themes resulting from the previous phase. Using a purposive sample, in-depth face-to-face interviews with a thematic guide were conducted, tape-recorded and transcribed by a team of sociologist.

3) Quantitative interviews: aimed to quantify how many people share the same arguments and assess differences in perceptions and opinions between groups (farmers/vets). A telephone survey of our target population (simple random sample) was performed with a structured questionnaire, using a computer assisted telephone interviewing system.

## Results

Exploratory and qualitative interviews were concluded, while the quantitative survey is still ongoing. Low reliability in the diagnostic tests, weak communication and confidence between farmers and official vets, lack of training for farmers and pressure faced by veterinarians due to personal relations with farmers were the main themes emerged from the exploratory interviews. Main results of the qualitative interviews showed that farmers perceive very few benefits of being bTb free and a general feeling of distrust of regulatory bodies (vets/institutions/politician) arose. Quantitative interviews are still ongoing and will enable to quantify the importance of the different social factors that could influence the bTb eradication program's success.

## Conclusions

On the basis of these preliminary results, the complexity of infection dynamics combined with a low level of knowledge on the bTb generates disbelief in the control measures and test results. In addition, the lack of coordination among regional and central institutions gives rise to comparative grievances and demotivation among farmers.

## References

EFSA AHAW Panel (EFSA Panel on Animal Health and Welfare), 2014. Statement on a conceptual framework for bovine tuberculosis. EFSA Journal 2014;12(5):3711, 59 pp.. Available online: www.efsa.europa.eu/efsajournal

**Keywords:** Bovine tuberculosis; Farmer opinion; Vets opinion; Attitude; Perception; eradication program

<footnote n="1">¹ Universitat Autònoma de Barcelona - Departament de Sanitat i Anatomia Animals (UAB) - Spain</footnote>

<footnote n="2">² Centre de Recerca en Sanitat Animal - Institut de Recerca i Tecnologia Agroalimentàries (CReSA - IRTA), Barcelona - Spain</footnote>

<footnote n="3">³ Servicio de Sanidad Animal, Consejería de Agricultura, Pesca y Desarrollo Rural de la Junta de Andalucía, Sevilla - Spain</footnote>

<footnote n="4">⁴ Departament d'Agricultura, Alimentació i Acció Rural de la Generalitat de Catalunya, Barcelona - Spain</footnote>

<footnote n="5">⁵ Asociación Andaluza de Antropología (ASANA), Sevilla - Spain</footnote>

<footnote n="6">⁶ Universitat Autònoma de Barcelona - Departament de Sociologia (IGOP - GEPS - ARAG-UAB), Barcelona - Spain</footnote>
**On the path towards reduced antimicrobial resistance: herd-level quantification of veterinary antimicrobial consumption in Belgian pig herds through the online monitoring tool 'AB Register'**

Wannes Vanderhaeghen<fnref n="1" />, Veerle Piessens<fnref n="1" />, Sharon Lagast<fnref n="2" />, Yvan Dejaegher<fnref n="2" />, Jeroen Dewulf<fnref n="3" />

<figure><img src="image_65.png" /></figure>

wannes.vanderhaeghen@amcra.be

**Objective**

Antimicrobial resistance (AMR) is a major threat in human and veterinary medicine. In the fight against AMR, measuring veterinary antimicrobial use (AMU) at herd-level is key, allowing identification of high and/or irresponsible users. So far, data on AMU in Belgian pig herds has come from studies investigating a limited number of herds. The AB Register is a new, sector-driven online monitoring tool for herd-level AMU covering approx. 80% of the Belgian stock of piglets, finishers and sows. Here, an analysis of the first two years (2014-2015) of data-collection in AB Register is presented.

**Methods**

Use of AB Register is obliged for pig farmers adhering the Certus, CodiPlanPLUS and Colruyt quality schemes, and voluntary for other pig farmers. The analysis included only farms that used AB Register continuously from 1/1/2014 till 31/12/2015.

Data on AMU are collected as registrations of deliveries of antimicrobial products. Registrations are done by the deliverer (the veterinarian, the compound feed producer or the pharmacist) and comprise the product name, product code, quantity delivered (number of kg for premixes, number of packages in other cases), date of delivery, farm code and animal category. Four animal categories can be selected: suckling piglets (SP), weaner piglets (WP), finishers (FI) and sows/bears (S/B). Optionally, the indication for use can be provided.

Herd-level AMU was quantified as treatment days (TD) per 100 animal-days based on the assumed use of the recommended dosage (= Defined Daily Dose Animal, DDDA). DDDA values were determined according to the principles described by Postma et al. 2014. The period at risk was set at 365 days. Standard estimated weights at treatment, used to calculate the kg pig at risk, were those proposed by ESVAC. Numbers of WP, FI and SB at risk were obtained through the Flemish Land Agency. The number of SP was calculated from the number of productive sows.

AMU in the four weight categories was compared with each other and over time based on the median TD within each population of farms keeping a given age category. The relative usage of different active substances was calculated based on total treatment days. For registrations for which an indication for use was provided, the different indications were ranked overall and per age category.

**Results**

The number of farms analysed was 1060 for SP and S/B, 1185 for WP and 2248 for FI. AMU was highest in WP (median TD = 30,33), followed by SP (median TD = 6,81), FI (median TD = 4.72), and S/B (median TD =0.39). The median usage decreased between 2015 and 2014 in all weight categories (SP: -21,6%; WP: -3,4%; FI: -9,1%; S/B: -22%). Extended-spectrum penicillins, tetracyclines and trim-sulfa antimicrobials together accounted for approx. 60% of treatment days. The critically important antimicrobials 3rd/4th generation cephalosporins and fluoroquinolones respectively accounted for approx. 6% and 2,5% of total treatment days and were particularly used in SP and S/B. With almost 60% of registrations providing an indication for use, general illness and respiratory disease were among the most frequently occurring indications in each age category. The combination WP - extended-spectrum penicillins - nervous disease accounted for almost 12% of total treatment days.

**Conclusion**

A gentle decrease in AMU in Belgian pig farming is apparent from our data, leaving room for further improvement. Our results add to the relevance of and point to the level of detail provided by a herd-level data-collection system.

**Keywords:** antimicrobial use, antimicrobial resistance, treatment days, pigs, defined daily dose

<footnote n="1">¹ Centre of expertise on Antimicrobial Consumption and Resistance in Animals (AMCRA) - Belgium</footnote>

<footnote n="2">² Belpork vzw - Belgium</footnote>

<footnote n="3">³ Veterinary epidemiology unit, Department of reproduction, obstetrics and herd health, Faculty of veterinary medicine, Ghent University - Belgium</footnote>
# Improvement of micro-organisms classification methodology into risk groups

**Aline Baldo**<fnref n="1" />, **Sarah Welby**<fnref n="2" />, **Chuong Daï Do Thi**<fnref n="1" />, **Amaya Leunda**<fnref n="1" />, **Philippe Herman**<fnref n="1" />

<figure><img src="image_66.png" /></figure>

wannes.vanderhaeghen@amcra.be

## Objective

Since pathogenic (micro)-organisms present a biological hazard, they have been categorized into risk groups (or classes of risk). The risk groups have been defined by WHO (2004) and many countries. Based on adopted definitions and criteria for risk classification some lists have been published. Belgian legislation defines criteria for the classification of micro-organisms taking into account the maximum risk for exposed immune-competent humans and animals. A common classification list for human and animal pathogen has been established. The Belgian classification system only considers the inherent characteristics of the micro-organism (e.g., invasiveness, virulence, infectious dose etc.), not its use. The aim of this presentation is to propose an improved approach to strengthen the final result obtained for the classification of a given human or animal pathogen.

## Method

An on-line questionnaire (extranet secured platform) for the assessment of a micro-organism based on the criteria described in the Belgian regional decrees has been implemented. This evaluation form contains open-ended questions and multi-choice questions, it also takes into account the level of confidence of the experts in their substantiated answers. The tool has been challenged with already well-described pathogens before being submitted to the panel of experts in order to classify ill-defined or uncategorized pathogens.

## Results

A semi-quantitative statistical approach enabling to take into account diverse experts opinions and providing a weighted score for each criteria has been developed. A meeting organized with the experts will allow to summarize the results and validate the final classification.

## Conclusion

The methodology used for the classification of micro-organisms has been improved. This approach strengthens the final result obtained for the classification of a given pathogen.

## Outcomes

This approach will improve the micro-organisms classification methodology for ill-defined or uncategorized pathogens.

**Keywords:** biosafety; risk assessment

<footnote n="1">¹ Scientific Institute of Public Health (WIV-ISP) - Belgium</footnote>

<footnote n="2">² Veterinary and Agrochemical Research Centre, National Reference Laboratory (CODA-CERVA) - Belgium</footnote>
<figure><img src="image_67.png" /></figure>

Association d'Epidémiologie et de Santé Animale

Epidemiology,
surveillance and
risk analysis

7th - 9th Sept. 2016 - Liège (Belgium)
Congress 25 years

Animal epidemiology
Past, present and future
# Keynote lecture

## Animal epidemiology, surveillance and risk analysis: past, present and future

### Claude Saegerman

UREAR-ULg, FARAH, University of Liege

Claude is a Professor at the University of Liege and is interested in epidemiology and risk analysis applied to veterinary sciences (http://www.dmipfmv.ulg.ac.be/epidemiovet/). Current research is mainly conducted on the development of methods for early clinical detection and understanding dynamics of infection of emerging (vector-borne and/or zoonotic) diseases and rare events, also for prioritizing animal diseases, based on an interdisciplinary approach and use of evidence-based medicine, and evaluation of disease control measures (including cost-benefit analysis).

claude.saegerman@ulg.ac.be

After 25 years of existence of the AESA (Association of Epidemiology and Animal Health), it is a necessity to look both to the past and to the present and give some perspectives for the future in terms of animal epidemiology, surveillance and risk analysis. For each of the three topics, a brief past and current situation is described and some perspectives are given for the future.

## Animal epidemiology

Epidemiology is the study of the occurrence and distribution of health-related events, states, and processes in specified populations. It also includes the study of the determinants that influence these processes, and applying this knowledge to control relevant health problems. Studies include surveillance, observation, screening, hypothesis testing, analytic research, experiments, and prediction (International Epidemiological Association, 2014). Indeed descriptive and analytical epidemiology is well used and disseminated (e.g. Saegerman et al., 2008, 2010 and 2014). However, some epidemiological techniques are of particular interest to deal with new challenges in animal epidemiology. These techniques consist, for example, of: (i) diseases modelling; (ii) forecasting of drivers; (iii) trends analysis of data; and (iv) inclusion of economics and social sciences as well as the environmental/ecological aspects.

**Modelling:** an epidemiological model is usually defined as "a mathematical and/or logical representation of the epidemiology of disease transmission and its associated processes" (Schwabe et al., 1977). These models provide a representation of the transmission dynamics of animal diseases among animals, and/or among groups of animals in time and/or space (Willeberg et al., 2011). The modelling of complex diseases introduction and spread, especially for vector borne diseases (e.g. West Nile fever), and diseases in developing countries due to the limited available data (e.g. foot and mouth disease) as well as evaluating and adapting strategies for animal disease control and prevention (e.g. brucellosis, tuberculosis) merits more attention in the future. Indeed, for example, diseases are often associated with debilitating clinical signs, disorders or production losses in animals and/or humans, which can lead to severe socio-economic repercussions. This explains the high priority that national health authorities and international organizations give in selecting control strategies for the eradication of specific diseases. When a control strategy is selected and implemented, an effective method of evaluating its efficacy is through modelling. For an accurate application of models, an interdisciplinary rather than a multidisciplinary approach is required, with the fewest assumptions possible (Saegerman et al., 2011).

**Forecasting of drivers and trends analysis:** There are many needs for future forecasting of drivers to predict more accurately the occurrence of animal threats (see the keynote from J. Bianchini) and for trends analysis of plethoric available data currently not always analyzed (e.g. Bakker et al., 2016).

**Economics, social sciences and ecological aspects:** The inclusion of economics and social sciences as well as the environmental/ecological aspects are areas that merit also more consideration in animal epidemiology. What are costs and benefit of actions? What are determinants of behavior of stakeholders involved in animal health actions? What are consequences of eradication of an epizootic in the environment (e.g. massive culling for the case of foot and mouth disease). The OIE recommend to include these aspects in all health actions (OIE, 2016; Rushton and Gilbert, 2016).

## Animal surveillance

Several national networks/systems/plans of epidemiological surveillance exist in Member States (MS) of the European Union (e.g. Cardoen et al., 2014a, 2014b). The objectives of surveillance can differ, such as to discovery an emerging disease (e.g. West Nile Fever), to determine the real importance (prevalence, incidence) of disease(s), to estimate the results of control plans and to prioritize the importance among different diseases. The quality of the national networks/systems/plans of epidemiological surveillance has not been frequently evaluated. However, this type of evaluation is strongly recommended. Criteria of interest were proposed by the Center for Disease Control and Prevention

<figure><img src="image_68.png" /></figure>
of Atlanta (CDC Atlanta, 2001; http://www.cdc.gov/mmwr/preview/mmwrhtml/rr5013a1.htm). These criteria for surveillance systems are the following:

* Simplicity: refers to both its structure and ease of operation;

* Flexibility: can adapt to changing information needs or operating conditions with little additional time, personnel, or allocated funds;

* Data quality: reflects the completeness and validity of the data recorded in the public health surveillance system;

* Acceptability: reflects the willingness of persons and organizations to participate in the surveillance system;

* Sensitivity: can be considered on two levels. First, at the level of case reporting, sensitivity refers to the proportion of cases of a disease (or other health-related event) detected by the surveillance system. Second, sensitivity can refer to the ability to detect outbreaks, including the ability to monitor changes in the number of cases over time;

* Positive predictive value: is the proportion of reported cases that actually have the health-related event under surveillance;

* Representativeness: a public health surveillance system that is representative accurately describes the occurrence of a health-related event over time and its distribution in the population by place and unit of interest;

* Timeliness: reflects the speed between steps in a public health surveillance system;

* Stability: refers to the reliability (i.e., the ability to collect, manage, and provide data properly without failure) and availability (the ability to be operational when it is needed) of the veterinary public health surveillance system.

Some operational tools to evaluate a surveillance network exist such as the OASIS method (Hendrikx et al., 2011) and participatory epidemiology (e.g. Calba et al., 2016). These tools should be widely used to ensure the link between objective(s) and the added value of the epidemiological network for the community. Economics and social sciences should be used to enhance the evaluation of the system.

Several recent events have prompted the need to develop European networks of epidemiological animal surveillance. A good example is lumpy skin disease that is currently affecting bordering countries of the European Union and where it is difficult to obtain relevant and updated epidemiological data on the true spreading of the disease in real time. Within each MS, a platform of information and exchange could be initiated such as the existing Platform of Animal Health Surveillance in France (http://www.plateforme-esa.fr/). One first action that could be carried out is an inventory of existing epidemiological surveillance systems (networks, systems, plans and other tools). A second action could target a SWOT analysis (Strengths, Weaknesses, Opportunities and Threats) in order to consider a common strategy of action thorough all Member States (harmonization, synergy, rationalization, adaptation to new challenges, assessment and development). These procedures should have a desirable structuring effect and gain in the future more resilience against infectious diseases in Europe.

Lastly, at the European level, a center of animal epidemiological intelligence with veterinary public health perspective could be created. Animal epidemiological intelligence is the process of detecting, verifying, analyzing, assessing, and investigating signals that may represent a threat to animal health (International Epidemiological Association, 2014). The tasks of this center would be the sanitary survey of emerging events, information of MSs on these risks, control of field investigation allowing to identify risks potentially serious for animal and human health, analysis and interpretation of epidemiological surveillance data and to support Member States that require assistance.

## Animal risk analysis

There are two main approaches to risk analysis: the qualitative and the quantitative. In a qualitative risk analysis, the risk level is estimated in qualitative terms; for example, risk of introduction is classified as “negligible” (Dufour et al., 2011). In a quantitative analysis the risk is estimated in quantitative terms e.g. with risk rates, usually expressed as a probability. Both quantitative and qualitative risk analysis can be applied in different fields since they are diverse and extensive. Irrespective of the differences between the two approaches (quantitative versus qualitative), decisions-makers can gain a thorough understanding of disease risk with a risk assessment which results in sensible and realistic recommendations, which if implemented, can lead to a sustainable strengthening of capacities to prevent, control and even to eradicate the disease (e.g. Wieland et al., 2015). As previously noted qualitative risk assessments express the risk in relative qualitative terms and often involve the aggregation of expert opinions. In this case, the methodology for qualitative risk assessment must be rigorous to ensure that the true risk and not the false risk perception is correctly assessed as any decision made can lead to major animal health and economic impacts (Vose, 1997). Additionally, from a methodological point of view, qualitative risk analysis usually lacks reproducibility and accuracy compared to quantitative risk models. Furthermore, quantitative risk assessment allows to model uncertainty by sensitivity analysis in order to determine the relative importance of variation in different inputs on the outputs (e.g. Martinez-Lopez et al., 2014). Quantitative risk analysis however, may be too complex to carry out as it requires more time, resources and accurate data. Indeed, a major and common problem for modelling in general is the lack of strong reliability and accuracy of recorded data (e.g. Allepuz et al., 2015).
There are a lot of challenges for the future in terms of risk analysis. Three examples should be proposed to stimulate future prospects: (i) the global metagenomics are currently accessible and therefore should be integrated as a tool in risk assessment for instance assessing the risk of importing illegal bush meat (Temmam et al., 2016), which is an important threat to biodiversity conservation of several endangered species and may contribute to the emergence and spread of infectious diseases in humans; (ii) Colony collapse disorder in honey bees or EBOLA disease have multiple causes/determinants and therefore the risk needs to be addressed appropriately with more integrated risk analysis taking into account not only pathogens but also other stressors and ecosystems; (iii) new risk assessment methodologies should be developed to meet the challenge of terrorism (Ezell et al., 2010) and (iv) considering the previous element, the inclusion of weight of evidence and uncertainty is of crucial importance to give good decision for action (Anses, 2016).

## References:

Anses. Évaluation du poids des preuves à l'Anses : revue critique de la littérature et recommandations à l'étape d'identification des dangers (rapport d'étape). Juillet 2016, pp. 116 (https://www.anses.fr/fr/system/files/AUTRE2015SA0089Ra.pdf).

Bakker KM, Martinez-Bakker ME, Helm B, Stevenson TJ. Digital epidemiology reveals global childhood disease seasonality and the effects of immunization. Proc Natl Acad Sci USA. 2016; 113(24):6689-6694.

Allepuz A, Stevenson M, Kivaria F, Berkvens D, Casal J, Picado A. 205. Risk factors for foot-and-mouth disease in Tanzania, 2001-2006. *Transbound Emerg Dis.* 2015;62(2):127-136.

Calba C, Goutard FL, Vanholme L, Antoine-Moussiaux N, Hendrikx P, Saegerman C. The Added-Value of Using Participatory Approaches to Assess the Acceptability of Surveillance Systems: The Case of Bovine Tuberculosis in Belgium. *PLoS One* 2016;11(7):e0159041.

Cardoen S., Depoorter P., Hendrikx P., Hooyberghs J., Imberechts H., Dewulf J., Czaplicki G., Van Der Stede Y., Dierick K., Van Den Berg T., Stoop S., Hubaux M., Quoilin S., Saegerman C. La surveillance épidémiologique belge en santé animale. *Partie I : Radioscopie des activités de surveillance épidémiologique en santé animale. Annales de Médecine Vétérinaire* 2014; 158(1):5-21.

Cardoen S., Depoorter P., Hendrikx P., Hooyberghs J., Imberechts H., Dewulf J., Czaplicki G., Van Der Stede Y., Dierick K., Van Den Berg T., Stoop S., Hubaux M., Quoilin S., Saegerman C. Radioscopie de la surveillance des maladies animales infectieuses en Belgique (partie II) : analyse des aspects organisationnels des activités de la surveillance et recommandations. *Annales de Médecine Vétérinaire* 2014; 158(1):22-38.

CDC Atlanta. Updated Guidelines for Evaluating Public Health Surveillance Systems. Recommendations from the Guidelines Working Group, MMWR 2001; 50(RR13):1-35.

Dufour B, Plée L, Moutou F, Boisseleau D, Chartier C, Durand B, Ganière JP, Guillotin J, Lancelot R, Saegerman C, Thébault A, Hattenberger AM, Toma B. A qualitative risk assessment methodology for scientific expert panels. *Rev Sci Tech.* 2011;30(3):673-81.

Ezell BC, Bennett SP, von Winterfeldt D, Sokolowski J, Collins AJ. Probabilistic risk analysis and terrorism risk. *Risk Anal.* 2010;30(4):575-89.

Hendrikx P, Gay E, Chazel M, Moutou F, Danan C, Richomme C, Boue F, Souillard R, Gauchard F, Dufour B. OASIS: an assessment tool of epidemiological surveillance systems in animal health and food safety. *Epidemiol Infect.* 2011;139(10):1486-1496.

International Epidemiological Association. A dictionary of epidemiology. Sixth edition. Edited for the International Epidemiological Association and Miquel Porta, 2014, Oxford Press University, pp. 343.

Martinez-Lopez B, Ivorra B, Fernandez-Carrion E, Perez AM, Medel-Herrero A, Sanchez-Vizcaino F, Gortazar C, Ramos AM, Sanchez-Vizcaino JM. A multi-analysis approach for space-time and economic evaluation of risks related with livestock diseases: the example of FMD in Peru. *Prev Vet Med* 2014; 114(1):47-63.

Rushton J, Gilbert W. The economics of animal health: direct and indirect costs animal disease outbreaks. 84th General Session of the World Assembly, Paris, 22-27 May 2016, doc. 84SG/9, pp. 17.

Saegerman C, Berkvens D, Mellor PS. Bluetongue epidemiology in the European Union. *Emerg Infect Dis.* 2008;14(4):539-544.

Saegerman C, Mellor P, Uyttenhoef A, Hanon JB, Kirschvink N, Haubruge E, Delcroix P, Houtain JY, Pourquier P, Vandenbussche F, Verheyden B, De Clercq K, Czaplicki G. The most likely time and place of introduction of BTV8 into Belgian ruminants. *PLoS One*. 2010; 5(2):e9405.

Saegerman C, Porter SR, Humblet MH. The use of modelling to evaluate and adapt strategies for animal disease control. *Rev. sci. tech. Off. int. Epiz.*, 2011;30(2):555-569.

Saegerman C, Alba-Casals A, García-Bocanegra I, Dal Pozzo F, van Galen G. Clinical Sentinel Surveillance of Equine West Nile Fever, Spain. *Transbound Emerg Dis.* 2016; 63(2):184-193.

Schwabe CW, Riemann H, Franti CE. Epidemiology in veterinary practice. Philadelphia, Lea & Febiger, 1977, pp. 303.
Temmam S, Davoust B, Chaber AL, Lignereux Y, Michelle C, Monteil-Bouchard S, Raoult D, Desnues C. Screening for Viral Pathogens in African Simian Bushmeat Seized at A French Airport. Transbound Emerg Dis. 2016. doi: 10.1111/tbed.12481.

Vose DJ. Risk analysis in relation to the importation and exportation of animal products. Rev Sci Tech. 1997;16(1):17-29.

Wieland B., Batsukh B., Enktuvshin S., Odontsetseg N., Schuppers M. Foot and mouth disease risk assessment in Mongolia-Local expertise to support national policy. *Prev Vet Med.* 2015;120(1):115-123.

Willeberg P, Grubbe T, Weber S, Forde-Folle K, Dube C. The World Organisation for Animal Health and epidemiological modelling: background and objectives. Rev Sci Tech. 2011; 30(2):391-405.

World Organization for Animal Health. Sixth Strategic Plan. OIE Bulletin 2016; 1: 4-5.
# Selected oral presentations

**How does pooling of serum or blood samples from young calves permanently infected with BDV-V affect the detectability of the real time PCR test? A field study in the context of the Belgian BVD eradication program.**

Jean-Baptiste Hanon<fnref n="1" />, Miet De Baere<fnref n="1" />, Jean-Yves Houtain<fnref n="2" />, Marie-Pierre Michiels<fnref n="2" />, Brigitte Cay<fnref n="1" />

<figure><img src="image_69.png" /></figure>

jb.hanon@yahoo.fr

## Objective

Currently, antigen (Ag) ELISA on ear notch samples is the routine method to detect permanently infected (PI) newborn calves within the Belgian BVD eradication program. The purpose of this study was to evaluate if real time RT-PCR testing of pooled blood or serum samples obtained from young calves (< 40 days) could be used as an alternative method and to measure the risk of not detecting PI calves, due to the possible presence of maternal antibodies reducing the viral load in these samples. Therefore, we estimated the proportion of false negative results when testing pooled serum or blood samples by PCR, taking as reference the Ag ELISA performed on individual earnotch samples. We compared this proportion to the estimated percentage of undetected PI (~3%) reported by other authors (Fux, 2012; Oettl, 2010) when using Ag ELISA on earnotch samples.

## Materials and methods

59 calves, previously detected as PI at birth in the routine BVD screening (August - December 2015), were monitored in this study. Each calf was sampled three times, to cover the period during which the detection of the virus is most critical: between day 10 and 15 after birth, around day 21 and around day 28. A fourth sample was taken at 45-60 days of age, to confirm the PI status. At each time point, full blood, serum and an ear notch sample were collected and tested with a commercial Ag ELISA. Three different PCR methods (one in house and two commercial kits) were performed on each blood and serum sample. Virus neutralization tests (VNT; BVDV-1 and BVDV-2) were performed on each serum. Afterwards, each blood and serum sample was diluted 1/20 (1/8) in blood or serum from a BVDV-free seropositive animal to mimic a pool size of 20 (8) samples and tested by PCR. The proportion (with 95% CI) of (false) negative PCR results obtained with pooled serum and pooled blood samples from the first three visits was estimated. We used a generalized estimating equation model (proc genmod, SAS 9.2.) to take into account the intra-class correlation of results obtained with successive samples from the same animals.

## Results

All 59 PI animals were positive at each of the three visits when tested by Ag ELISA on individual ear notch. Three calves were negative by Ag ELISA for serum samples taken at the first visit and two of them were also negative for corresponding blood samples. PCR on individual blood samples were positive for all animals at all visits but one animal had a negative PCR result with the three PCR methods on serum samples from the first and/or second visit. Most calves were seronegative or had low VNT titers (≤1:60) at all visits but a few animals had high VNT titer (≥ 1:240), generally decreasing with time, probably linked to maternal antibodies. Some of the individual serum and blood samples which were positive but had high Ct values (>35) and high VNT titers (1:120 – 1:640) could not be detected anymore when tested in pools and these pools results were considered as false negative. The proportion of false negative results with pooled samples, taking as reference the Ag ELISA method on individual earnotch was estimated to be between 1.13 and 2.26 %, depending on the sample matrix, the pool size, and the PCR method used.

## Conclusion

A small percentage of PI calves, detected at birth by Ag ELISA on earnotch samples would not be detected when tested by PCR on pooled serum or blood samples taken during the first weeks after birth. However, it has been previously shown that a similar proportion of false negative results also occur with the Ag ELISA method on earnotch.

**Keywords:** BVD ; PI ; earnotch ; pooling ; PCR ; ELISA

<footnote n="1">¹ Veterinary and Agrochemical Research Centre, National Reference Laboratory (CODA-CERVA) - Belgium</footnote>

<footnote n="2">² Association Régionale de Santé et d'Identification Animales (ARSIA) - Allée des Artisans 2 5590 Ciney - Belgium</footnote>
# Approach towards benchmarking surveillance: bovine tuberculosis in Belgium as an exemple

Sarah Welby<fnref n="1" />, David Frétin<fnref n="1" />, Virginie Roupie<fnref n="1" />, Yves Van Der Stede<fnref n="1" />, Claude Saegerman<fnref n="2" />

<figure><img src="image_70.png" /></figure>

Sarah.Welby@coda-cerva.be

## Introduction

Despite eradication and control measures, bovine tuberculosis (bTB) remains a constant threat to EU Member States. For EU Member States with an officially free status, such as in Belgium, one of the main concerns is to maintain this free-status and to detect as early as possible new breakdowns. The aim of this study was to evaluate the efficacy of the surveillance system for bTB by estimating and comparing the number of true and false positive reactors that can be expected given a pre-defined design prevalence and the diagnostic tests characteristics (Se and Sp), with the observed number of reactors during purchase (single intradermal skin testing) and slaughterhouse surveillance (inspection).

## Material & Methods

A stochastic iteration model was performed to compute the expected positive reactors (true positive + false positive) in the tested cattle population during purchase and at slaughterhouse. The output (true positive + false positive reactors) was modeled as function of different input parameters, such as test characteristics (sensitivity and specificity) of the intradermal skin test at purchase and visual inspection in the slaughterhouse (EFSA, 2012), the cattle population (excluding fattening calves) proportion sampled and tested (national cattle identification and registration system (SANITEL)), the minimum expected herd design prevalence (Directive 64/432/CEE), different simulated animal level prevalence. Distributions were used for the input parameters to take into account a range of possible values and providing in such a way an output distribution reflecting the uncertainty and variability of the diagnostic tests. Stochastic simulations were carried out with 10 000 iterations per simulation in Modelrisk 3.0.

## Results

Given the test characteristics, design prevalence, cattle population proportion tested, the mean (and respective minimum, maximum values) expected for a simulated animal prevalence of 0.01% was 1.3127% (0.0271-3.5120) false positives during purchase testing and 0.0011% (0.0006-0.0012) suspicious lesions. The true bTB suspicious lesions and positive reactions at purchase was negligible given the low expected prevalence.

## Discussion

Based on the annual tested and slaughtered cattle (excluding fattening calves) it would mean that between 45 and 180 suspicious lesions should be expected, and between 2 500 and 6000 of all tuberculin tested bovines at purchase should react positively. False positives reactors at tuberculin test could be all the more increased, given the prevalence Mycobacterium avium in Belgium. New questions aroused from this study that would require further investigation such as factors influencing sensitivity and specificity of tuberculosis surveillance. However the output of this study provides useful insight on expected reaction rate and the method developed could be used as a tool for benchmarking surveillance.

**Keywords:** Surveillance Benchmark Tuberculosis

<footnote n="1">¹ Veterinary and Agrochemical Research Centre, National Reference Laboratory (CODA-CERVA) - Belgium</footnote>

<footnote n="2">² Research Unit in Epidemiology and Risk Analysis Applied to Veterinary Sciences (UREAR-ULg), Fundamental and Applied Research for Animal Health (FARAH) center, University of Liege - Belgium</footnote>
# Computer and veterinary sciences: an integrated database for disease surveillance

Simone Rizzo<fnref n="1" />, Laura Bortolotti<fnref n="1" />, Tatiana Breda<fnref n="1" />, Donata Trimarchi<fnref n="1" />, Michele Brichese<fnref n="2" />, Stefano Marangon<fnref n="1" />

<figure><img src="image_71.png" /></figure>

srizzo@izsvenezie.it

## Objective

Livestock information systems are worldwide used by various stakeholders (e.g. farmers, veterinarians), who need data for different purposes (e.g. animal traceability, control of animal health and welfare, management practices, safety of products). Data collection and data sharing among these systems through unanimous protocols and real-time communications can provide new tools for surveillance activities performed by veterinary Services (VSs) and reduce the administrative burdens.

## Methods

The Veneto Region (north-eastern Italy), in over fifteen years, has developed an information system which collects, stores and manage data on livestock holdings, animal movements, control activities performed by VSs, vaccine administrations and laboratory tests performed on animals. The SOAP-http communication protocols have been used to centralize in a single database all the data originated from the different territorial information sources. Thanks to the implementation of web services and the use of standards based on XML, it has been possible to ensure the interoperability between software applications implemented on different hardware platforms (e.g. laboratory management systems, registers of holdings and slaughterhouses). Specific tools of the central database have been implemented in order to manage data generated by disease eradication plans (e.g. bovine tuberculosis and brucellosis, Aujeszky disease). An error-automatic monitoring system ensures the continuous monitoring of the quality of the recorded data. Reports on non-compliances (e.g. farms that are not inspected on a regular basis) and situations of sanitary risk (e.g. batches of animals arriving from areas not free from a disease) are published on a website.

New functions have been added in order to enable farmers to draft the animal transport documents using the information stored in the database. The central database checks that all the veterinary requirements are satisfied depending on the animal health status, origin and destination. If no further laboratory tests or veterinary checks are needed, the veterinary certifications attesting the health status of the animals that move from a farm to another one or to a slaughterhouse are automatically issued.

## Results

The information system is largely employed: the users are more than 1,000; the monthly accesses to the system are around 800,000 and over 90,000 cattle movements, 3,700 swine batches, 3,000 movements of sheep and goats are recorded every month. The central database guarantees that the information is accurate, timely and complete, it allows the animal traceability along the whole production chain and indirectly enhances the control of the health status of the farms. For example in 2015, No. 6,320 bovine herds were checked for maintenance of official tuberculosis free status with over 302,000 tests recorded by the VSs. Over 26,000 analyses for Aujeszky disease were automatically transmitted from the laboratory management system to the central archive and linked to the farm of origin of the samples.

## Conclusion

The integration of information retrieved from different sources reduces work, costs, time and errors due to the manual input of data and improves data quality. This solid and consistent database allows the dematerialization of the transport documents and of the veterinary certifications that can be retrieved from the system.

**Keywords:** surveillance; information system; livestock

<footnote n="1">¹ Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe) - Italy</footnote>

<footnote n="2">² Unità Organizzativa Veterinaria e Sicurezza Alimentare, Regione Veneto - Italy</footnote>
# Seroprevalence and risk factor analysis of small ruminant lentiviruses in Belgian sheep and goats

Rodolphe Michiels<fnref n="1" />, Eva Van Mael<fnref n="2" />, Christian Quinet<fnref n="3" />, Ann Brigitte Cay<fnref n="1" />, Nick De Regge<fnref n="1" />

rodolphe.michiels@coda-cerva.be

## Objective

Visna/Maedi virus (VMV) and caprine arthritis encephalitis virus (CAEV) are members of the group of small ruminant lentiviruses (SRLVs). Both result in progressive and persistent infections in sheep and goats. These closely related retroviruses are responsible for neurological disorders and chronic lesions in lungs, joints and mammary glands. Aside from their impact on the animal welfare and their fatal outcome, SRLVs cause economic losses due to reduced lamb weight, reduced milk production, early culling and restrictions to animal trade. The most important route of transmission is the ingestion of infected colostrum and milk by lambs but the virus can also spread via respiratory secretions when animals are housed intensively for prolonged periods. Since no therapies are available against SRLVs, the control of the disease relates mostly on the early detection of infected animals with diagnostic tools such as agar gel immunodiffusion (AGID) and ELISA. As for several other European countries, the seroprevalence in Belgium for these diseases is unknown. Therefore, we performed a nationwide SRLV survey in the Belgian sheep and goat population.

## Methods

We aimed to collect samples from a total of 100 sheep and 100 goat farms all over Belgium. Only farms that did not participate in the voluntary MVV/CAEV control program and had at least 3 goats or 5 sheep were eligible to participate. A stratified sampling approach proportional to the number of goat and sheep holders per province was applied and maximally 7 animals per farm were sampled. All randomly selected sheep and goat owners were contacted by phone and asked to participate to the study. A short questionnaire was submitted to the volunteers to collect information about flock size, animal health condition and age, potential contact with goat or sheep and the housing facilities. All submitted sera were tested in two commercial immunodiffusion kits, the AGID-CAEV p28 kit (Pourquier, France) and the Maeditect kit (Apha Scientific, UK). Animals which were positive in at least one of both tests were considered seropositive.

## Results

Although 100 sheep and goat farmers confirmed their participation, we received samples from only 86 sheep farms (546 samples) and from 74 goat farms (393 samples). Samples were received between November 2015 and May 2016. For sheep, an overall seroprevalence of 9.9% was observed and a between herd seroprevalence of 17.4% was found. The mean within herd seroprevalence at those farms that had at least one positive animal was 51.4%, but varied between 14.3% and 100%. In the goat study, 14.9% of the farms had at least one seropositive animal and the mean within herd seroprevalence was 40.9% with a similar variation as found for sheep. Only 6.4% of all goat samples were found seropositive for SRLVs. Interestingly, risk factor analysis showed that herds of more than 10 goats had significantly higher chance to harbor seropositive animals (Odd ratio: 4.27; CI95% (1.05, 17.37); P-value Fisher's Exact Test= 0.047). No significant risk factors could be identified among other factors analyzed in sheep and goats.

## Conclusion

This study is the first to investigate the SRLV seroprevalence in the sheep and goat population of Belgium. Despite the fact that there is a voluntary control program for SRLVs in Belgium, we observed that SRLV are present on 15% to 20% of non-certified farms. For goats, larger flocks seem to be more prone to harbor SRLV positive animals.

**Keywords:** Seroprevalence ; Visna/Maedi virus ; Caprine arthritis encephalitis virus ; Small ruminant lentivirus ; AGID ; Risk factor ; Belgium

<footnote n="1">¹ Veterinary and Agrochemical Research Centre (CODA/CERVA) - Ukkel - Belgium</footnote>

<footnote n="2">² Dierengezondheidszorg Vlaanderen (DGZ) - Torhout - Belgium</footnote>

<footnote n="3">³ Association Régionale de Santé et d'Identification Animales (ARSIA) - Allée des Artisans 2 5590 Ciney - Belgium</footnote>
# Posters

## Surveillance to declare freedom and/or detect a case? A case study for bovine brucellosis in Belgium

Sarah Welby<fnref n="1" />, David Fretin<fnref n="1" />, Jacques Godfroid, Yves Van Der Stede<fnref n="1" />

<figure><img src="image_72.png" /></figure>

Sarah.Welby@coda-cerva.be

### Introduction

Belgium is officially brucellosis free (OBF) since 2003. Prior to 2009 the surveillance components were the following: i) ABORTION testing for the presence of *Brucella* spp.; ii) IMPORT testing of all cattle imported from officially and non-officially free countries; iii) PURCHASE testing of all traded cattle; iv) TANK MILK testing of all dairy herds; v) CROSS sectional serological screening of 1/3 of cattle herd population during winter. In 2010, in accordance with Directive 64/432/CEE and the National Royal Decree of 6/12/1978, a new surveillance system was installed which targeted cattle groups with a higher risk of being infected by *Brucella* spp. (IMPORTS, PURCHASE and ABORTION). In March 2012, an abortion notification led to the detection of *B. abortus* in a herd located in the province of Namur in Belgium. The aim of this study was to know whether the new surveillance system, despite being efficient enough for proving absence of infection, was effective enough in detecting emerging cases of bovine brucellosis.

### Materials and methods

A case detection model was developed to estimate the expected positive detection rate in each surveillance component in place since 2010 taking into account the fraction of population tested and expected to be infected given the official minimum design prevalence, the positive predictive values of the diagnostic assays used.

### Results

Preliminary findings revealed that ABORTION notification was by far the most effective surveillance component with a mean detection rate of 64% (51%-80%).

### Discussion

One of the main features of the study in 2009 showed that a 30 fold decrease in the total number of samples could be implemented and yet would maintain a 99% confidence level in substantiating freedom of brucellosis. It also clearly indicated that the most important backbone of the surveillance program was to test imported cattle from officially free and non-officially free countries, traded animals, as well as aborting animals in order to substantiate freedom. Regarding the passive surveillance (abortions), an important take-home message was that an increase in the number of cases reported and tested was needed. In addition, to encourage reporting of abortions, it was decided in 2009 to target cross sectional screening in herds where a large number of births occurred and where no abortions were declared and yet expected over the last 2 years. The present study corroborates these findings as it clearly shows the importance of passive surveillance and notification of abortions. Finally, an important finding of this study is that both aims, i.e. freedom of infection as well as case detection, can be combined and yet provide an effective and efficient surveillance system.

**Keywords:** Surveillance freedom case detection

<footnote n="1">¹ Veterinary and Agrochemical Research Centre, National Reference Laboratory (CODA-CERVA) - Belgium</footnote>

<footnote n="2">² Arctic Infection Biology, Department of Arctic and Marine Biology,UiT-The Arctic University of Norway, Tromsø, Norway.</footnote>
# Characterization of bovine brucellosis in Colombia (2006 – 2012)

Liliana Cardenas ¹, Jordi Casal ¹

¹ Departament de Sanitat i Anatomia Animals, Universitat Autònoma de Barcelona (UAB) Facultat de Veterinària. UAB. 08193 Bellaterra, Barcelona - Spain

<figure><img src="image_73.png" /></figure>

zlilianac@yahoo.es

Bovine brucellosis is a disease that causes important economic losses in livestock and with high impact in public health. The disease is endemic in Colombia and it is currently under a control program. This control is based on four procedures applied on bovine and bubaline farms: passive surveillance, test-and-remove, certification of disease free farms and tests for animal movements. The objective of this study was to estimate the evolution of bovine brucellosis in Colombia for a seven years period (2006-2012) using data from the official control. A total of 58 epidemiologic variables were analyzed for each year at department level. Univariate descriptive analysis and Principal Components Analysis (PCA) were performed. The surveillance programs covered 3% of the census in 2006 and this proportion increased to 15% in 2012. The percentage of positive farms and animals averaged respectively 22% and 4.7% in 2006 and 23% and 4.6% in 2012, without any clear pattern of evolution. The region with the highest proportion of positive farms was Orinoquia with a range between 24.6% and 49.6%, and the region with the lowest one was Amazonian with a herd prevalence between 17.9% and 32.7%. No differences were detected between the four control procedures. The mean results along the period for each particular examination procedures were 6.8% for passive surveillance, 5.9% for test-and-remove and 4.4% both in farms tested to become free of disease and test performed before animal movements. The results obtained through a PCA, allowed finding three different clusters: 1.) Geographic areas with low bovine production and low bovine brucellosis surveillance, 2.) Geographic areas with average bovine production and middle ovine brucellosis surveillance, and 3.) Geographic areas with a specialized livestock production applying sanitary measures to control bovine brucellosis. The bovine brucellosis control program in Colombia has had a low impact in the reduction of the disease prevalence in the country during the studied period.

**Keywords:** Surveillance freedom case detection
# Identification of virulotypes and serotypes of enteropathogenic (EPEC) and Shigatoxigenic (STEC) Escherichia coli from healthy cattle at slaughterhouses in Wallonia.

Shino Takaki<fnref n="1" />,<fnref n="2" />, Jean-Noël Duprez<fnref n="1" />, Ibrahim Fakih<fnref n="1" />, Nicolas Korsak<fnref n="3" />, **Damien Thiry**<fnref n="1" />, Jacques Mainil<fnref n="1" />

<figure><img src="image_74.png" /></figure>

gitaka77@yahoo.co.jp

Escherichia coli producing the attachment-effacement (AE) lesion (EPEC) and/or Shiga toxins (STEC) cause enteritis and (bloody) diarrhoea in young calves and in humans, and are also present in the intestines of healthy cattle. Besides the O157:H7 serotype, which is the main serotype causing STEC outbreaks in the world EPEC and STEC can belong to dozens of O serogroups. Of them, 9 have been frequently identified worldwide: O5, O26, O103, O104, O111, O118, O121, O145 and O165.

The aim of this study is to identify the virulotypes and the O serotypes of EPEC and STEC isolated from healthy cattle at slaughterhouses in Wallonia.

A total of 245 faeces (216 Enterobacteriaceae selective broth. The enrichment broths were assayed with an stx1, stx2 (Shiga toxin) and eae (AE lesion) triplex PCR and positive broths were inoculated onto 4 agar media: McConkey's, Chromagar ES, Chromagar ES with tellurite and Chromagar STEC. Up to ten colonies per plate were picked up, sub-cultured and tested by the colony hybridization assay with gene probes targeting the stx1, stx2 and eae genes. The triplex PCR was again performed on all probe-positive isolates. The PCR-positive E. coli were subsequently assayed with two pentaplex PCR targeting the specific genes coding for the ten O serogroups listed above.

Of the 2563 sub-cultured isolates, 744 isolates (29%) from 62 animals (25%) tested positive with the colony hybridization assay. Of them, 687 isolates (92%) from 59 animals were positive with the triplex PCR and the results of both tests were in agreement for 617 isolates (83%). One to 29 isolates per animal were probe- and PCR-positive.

The positive isolates grew on Chromagar STEC (379; 55%), on Chromagar ES with tellurite (189; 28%), on Chromagar ES (62; 9%) or on McConkey's agar (57; 8%).

The most frequent virulotypes were eae+ (EPEC: 372 isolates; 54%), eae+stx1+ (AE_STEC: 119 isolates; 17%) and stx2+ (STEC: 118 isolates; 17%). In some animals different virulotypes were identified. The serogrouping with the two pentaplex PCR is in progress.

AE-STEC, EPEC and STEC are excreted by 25% of the healthy cattle at slaughterhouses in Wallonia and different virulotypes can be excreted by the same animal. Conversely the methodology followed gives no precise idea of the actual level of excretion since the hybridization and PCR were performed after enrichment in selective broth. Therefore multiple isolates belonging to the same virulotype might represent the same clone. Identification of the serogroups and comparison by Pulsed Field Gel Electrophoresis should help to clarify that point. Quantitative (q)PCR is today the best method to quantify bacterial excretion, but is more expensive.

The results of the hybridization and PCR correspond to between 80 and 90%. Though the colony hybridization is still useful for large-scale surveillance it needs radioactive probes for highest sensitivity and is more time-consuming than PCR. Therefore the PCR should be the first routine choice if it can be automatized at large scale.

Further steps are the confirmation of the PCR results of the 70 isolates with different hybridization and PCR results and the identification of the serogroups with the two pentaplex PCR and later with PCR for the other serogroups, to compare them with isolates from young diarrhoeic calves and from humans.

Keywords: Escherichia coli ; bovine ; slaughterhouse ; EPEC ; STEC ; AE_STEC

<footnote n="1">¹ Bacteriology, Department of Infectious and Parasitic Diseases, FVM and FARAH, ULg, Liège</footnote>

<footnote n="2">² Dpt Veterinary Medicine, Faculty of Agriculture, University of Miyazaki, Japan</footnote>

<footnote n="3">³ Food Inspection, Dpt of Food Science, FVM and FARAH centre, ULg, Belgium</footnote>
# Outbreak investigations and molecular characterization of foot-and-mouth disease viruses circulating in Niger

Bachir Souley Kouato¹

¹ University of Liege (ULg) - Belgium

<figure><img src="image_75.png" /></figure>

bskouato@student.ulg.ac.be

In Niger, the epidemiological situation regarding foot-and-mouth disease (FMD) is unclear and the majority of outbreaks are not reported. The objectives of this study were i) to identify current FMDV strains circulating in cattle herds, ii) to identify exposure risk factors associated with FMD seropositive animals and iii) to test the relationship between one FMDV isolate from Niger and reference vaccine strains. Epithelial tissues (n = 25) and sera (n = 202) were collected from cattle in eight districts of the western part of Niger. 142 (70%) out of the 202 tested sera were positive for the presence of antibodies against FMD, using the non-structural protein (NSP) test. Using the Liquid Phase Blocking ELISA (LPBE) test, 125 (88%) of 142 sera tested for antibodies to structural proteins of four FMDV serotypes (A, O, SAT 1 and SAT 2) scored positive for one or more serotypes. The multivariate logistic regression analysis with NSP positive revealed that only the herd composition (presence of both cattle and small ruminants) was significantly associated with FMDV seropositivity (P-value = 0.006). Antigen-ELISA and VP1 coding sequence analysis revealed the presence of FMDV serotype O that were characterised within the O/WEST AFRICA topotype. The antigenic relationship between one of the FMDV isolates from Niger (O/NGR/4/2015) and three reference vaccine strains was determined by the two-dimensional virus neutralization test (2dmVNT), revealing a close antigenic match between the field isolate from Niger and three FMDV serotype O vaccine strains. This study provides an updated knowledge on the epidemiological situation of FMD in Niger and these results highlight the complex nature of the FMD epidemiology in Africa reflected by the transboundary mobility of the virus. Therefore, these findings may help to develop effective control and preventive strategies for the disease in Niger as well as in other countries of West Africa.

Keywords: Foot ; and ; Mouth Disease Virus ; Identification ; Molecular Characterization ; Serology ; Risk factors ; Niger
<figure><img src="image_76.png" /></figure>

Association d'Epidémiologie et de Santé Animale

# Bee diseases
# Keynote lecture

## A sticky mess - understanding the drivers of honey bee losses

**Dennis vanEngelsdorp, Ph.D.**

University of Maryland

Dennis is an Assistant Professor at the University of Maryland and is interested in pollinator health. The focus of his current work involves the application of epidemiological approaches to understanding and (importantly) improving honey bee health. Currently Dennis is the director of the Bee Informed Partnership (BeeInformed.org) which attempts to provide a platform to collect "big data" on the state of health of managed honey bee colonies. Analysis of these data is providing important insights into the role beekeeper management practices and environmental factors (such as landscape pesticides and climate) have on bee health.

<figure><img src="image_77.png" /></figure>

dvane@umd.edu

The European honey bee, *Apis mellifera*, is arguably the most important pollinator of agricultural crops in the world today. The ability to manage this “super organism” in manmade equipment allows for the easy transport of bees over large distances, facilitating the use of honey bees for large scale pollination. Conceivably, commercial pollination is the corner stone of modern US agricultural[1] with honey bees playing a role in producing, both directly and indirectly, 1/3 of calories in a typical western diet. When including the value bees add to the agricultural sector through pollination, honey bees are ranked as the third most important livestock species, after cows and pigs [2].

Large scale production of fruit crops (like blueberries, apples, almonds etc.) require a moveable "pollination force" that are brought into orchards before bloom and then removed immediately after petal drop. Moving bees into and out of systems is critical as, apart from crop bloom periods, there is often little food resources for bees in agricultural environments. Further, pesticide applications on fruit crop would certainly harm colonies left in orchards. Consequently, many of the relatively few commercial beekeepers in the US (~2,000) move their colonies on trucks across the continental US to pollinate a host of crops. For instance, a typical east coast commercial beekeeper would start the year in Florida, move colonies to California almonds for February pollination, then move back to Florida before moving colonies north to pollinate apples in Pennsylvania and New York, then move colonies to Maine to pollinate blueberries, then to Massachusetts to pollinate cranberries, then to New Jersey to pollinate cucumbers and Pennsylvania to pollinate pumpkins, and finally back to Florida to repeat the cycle.

Colony numbers in the United States have declined from a peak of just over 6 million colonies in the 1940's to a low of just over 2 million colonies several years ago[3, 4]. This long term decline has largely been driven by socio-economic factors. Colony numbers generally increase when honey prices are high and then decrease when honey prices are low [5]. However, comparing census counts of colony numbers over time is slightly misleading as loss rates can be high even as colony numbers increase from year to year. This seemingly contradictory occurrence is possible because of the unique ability of beekeepers' to replace lost colonies by splitting surviving colonies and adding a queen to the queenless "split". As a result of the tremendous increase in demand for almond pollination, commercial beekeepers are increasing the number of colonies they take into winter to proactively mitigate these losses. A beekeeper who loses 30% of his colonies every winter, now starts the winter with 30% more colonies then he would have had previously to ensure that he will have enough living colonies to meet his pollination contractual obligations.

The highly mobile nature of US commercial beekeeping in addition to the ability of beekeepers to replace losses quickly and relatively easily make surveillance efforts, as well as the application of epidemiological methods to the resulting data, challenging. Nonetheless, through the Bee Informed Partnership, several national surveillance efforts have been initiated including paper (e.g. annual loss and management surveys) and in-field disease sampling efforts[6-8]. The data generated from these efforts now permit the application of epidemiological methods to help identify leading drivers of colony losses as well as identify strategies to improve bee health[9].

There has been a sustained and growing consensus that the drivers of colony losses in the US are multifactorial and potentially synergistic; these include **disease and parasites** – the most important of which is the Varroa mite and the viruses it vectors, **pesticides** (both those that beekeepers apply to colonies to control mites, and pesticides that farmers apply to field crops and that are brought back to the hive by foraging bees), and **poor nutrition** which has been driven by changing land use and agricultural practices[10]. Here we take the opportunity to examine surveillance data and see how these data help elucidate the putative role each cause has on overall bee health.

## Varroa virus complex

The National Honey Bee Disease Survey, funded by the USDA APHIS, randomly samples operations in participating US states to assess, among other drivers, varroa and varroa-mediated virus prevalence and loads in the US. Startlingly, over half of US beekeeping operations survey had mite levels above commonly recommended threshold levels in the fall – a critical period for colonies as this is the time of year bees prepare to rear the next generation of “winter bees”, a
physiologically different bee that can live several months rather than the 3 to 4 week lifespan of summer forager bees. In part, these high levels of mites are a result of the dramatically changed damage threshold, Twenty years ago, colonies could sustain as many as 20 mites per 100 bees but currently, thresholds are set at 3 mites per 100 bees. This change is almost certainly driven by honey bee viruses that varroa mites are able to vector from sister bee to sister bee. As is predicted by disease evolutionary theory, in the absence of mites these viruses are transmitted vertically and so natural selection favors non-virulent viral form; however, the newly introduced varroa mite facilitates horizontal transmission of viruses and so viruses have been selected for increased virulence, thus lowering the varroa treatment thresholds. Varroa issues are also exacerbated by beekeeping practice. The US beekeeping industry is bimodal [11]. Ninety five percent of beekeepers are considered "backyard" beekeepers (less than 50 colonies), and this group manages about 5% of the nation's colonies. Conversely, commercial beekeepers make up less than 5% of the beekeepers in the US but manage well over 90% of the colonies. Both groups have very different motives and objectives for keeping bees which influences their approaches to bee management. Consistently, US commercial beekeepers lose fewer colonies than backyard beekeepers. In part this difference is driven by the fact that most (>95%) commercial beekeepers have varroa management plans in place, while the plurality of backyard beekeepers do not [12]. Many small scale beekeepers do not treat for varroa with the intention of helping develop mite tolerant bees, believing that by not treating, the susceptible stock will die leaving resistant stock from which they can breed. While a noble ambition, this approach is counterproductive as colonies perishing from mites actually spread their mites to colonies as far as two miles away, and so drive mite pressure up in colonies that may already have been successfully treated. Current efforts in the US are focused on a desire to get more beekeepers to actively manage their varroa populations year round. Messaging such as, "would your dog have fleas? Why would you let your bees die from ticks? It is unethical to not have a treatment plan in place because you damage both your own and your neighbors' colonies" have increased use of varroa management practices by all beekeepers.. While increasing numbers of beekeepers do have varroa management plans in place, progress has been slow and seems to be stagnating suggesting other messaging approaches are needed.

## Pesticides

The role pesticides play in colony mortality has been a hot topic and one that has inflamed passionate political debates. There is little question that pesticides can have large negative effects on bee health [13]. What is less understood is the degree to which real world exposures effect colony health. Surveillance efforts show that more than 80% of samples are contaminated with at least one product and on average contain 3 different products [14]. Levels of individual products rarely are detected at levels that are thought to harm bee health directly. However, products interact synergistically and so in combination their presence can be correlated to poor colony health. Notably, pesticides traditionally deemed bee safe – like fungicides – have measurable negative effects on health, while other insecticides (such as the notorious group of neonicotinoid pesticides) are not detected frequently enough to support claims they are a major driver of colony losses.

## Nutrition

In response to increased commodity prices for corn and soybeans, many millions of previously uncultivated acres of prairie have been plowed under thus reducing the forage available to bees. Poorly fed bees are more susceptible to disease and are more expensive to manage, highlighting the need for comprehensive and multipronged approaches to ensuring bee health.

**In conclusion** it is clear that many different factors affect colony health, and so approaches to improving bee health also need to be multi-factorial. Messages also need to be tailored to different beekeeping groups as both their concerns and likely the drivers of loss differ between small and large beekeeping operations. There is little doubt that varroa are a major challenge for the industry, and without reducing this mites impact, efforts to increase forage or reduce pesticide exposure are unlikely to increase survivorship unless varroa are more consistently controlled.

## References:

1. Pettis, J., D. vanEngelsdorp, and D. Martin, *Migratory beekeeping*, in *Bee Health and Veterinarians*, W. Ritter, Editor. 2014, OIE World Organisation for Animal Health: Paris. p. 51-54.

2. Allsopp, M.H., W.J. de Lange, and R. Veldtman, *Valuing Insect Pollination Services with Cost of Replacement*. PLoS ONE, 2008. **3**(9): p. e3128.

3. NRC, *Status of Pollinators in North America*. 2006, National Academy of Sciences: Washington, D.C. p. 317.

4. Aizen, M.A. and L.D. Harder, *The Global Stock of Domesticated Honey Bees is Growing Slower then Agricultural Demand for Pollination*. Current Biology, 2009. **19**(11): p. 915-918.

5. vanEngelsdorp, D. and M.D. Meixner, *A historical review of managed honey bee populations in Europe and the United States and the factors that may affect them*. Journal of Invertebrate Pathology, 2010. **103**: p. S80-S95.

6. vanEngelsdorp, D., et al., *The Bee Informed Partnership: Using Beekeeper's Real-World Experience to Solve Beekeepers' Real-World Problems*. American Entomologist, 2012. **58**(2): p. 116-118.
7. Traynor, K.S., et al., *Multiyear survey targeting disease incidence in US honey bees*. Apidologie, 2016: p. 1-23.

8. vanEngelsdorp, D., et al., *Honey bee health surveillance*, in *Bee Health and Veterinarians*, W. Ritter, Editor. 2014, OIE World Organisation for Animal Health: Paris. p. 215-222.

9. vanEngelsdorp, D., et al., *Standard epidemiological methods to understand and improve Apis mellifera health*. Journal of Apicultural Research, 2013. **52**(4).

10. Potts, S.G., et al., *Global pollinator declines: trends, impacts and drivers*. Trends in Ecology & Evolution, 2010. **25**(6): p. 345-353.

11. Darerkow, S., P Korb, and F. Hoff, *Structure of U.S. managed pollination industry*. Journal of Economic Entomology, 2009. **102**(3): p. 868-886.

12. Bee Informed, P., *Managment Survey Results*. 2016: www.beeinformed.org.

13. Mullin, C.A., et al., *High Levels of Miticides and Agrochemicals in North American Apiaries: Implications for Honey Bee Health*. Plos One, 2010. **5**(3).

14. vanEngelsdorp, D., et al., *Pesticides in Honey Bee Colonies: four years of US National Honey Bee Disease Survey* reveals real world exposure and associated morbidity. in prep.
# Selected oral presentations

## Development of an original bee health management tool for beekeepers: Bee Best Check

Noëmie El Agrebi<fnref n="1" />, Koen Beeuwsaert, Dirk De Graaf, Claude Saegerman<fnref n="1" />

claude.saegerman@ulg.ac.be

### Objectives:

In Belgium as in many European countries, there has been an increase in honey bee colonies mortality over the past ten years (17% in 2004 to 32,4% in the winter of 2012-2013 for Belgium. The Pan-European epidemiological study on honeybee colony losses, EPILOBEE (2012-2014), shows that Belgium is strongly impacted and has the highest bee mortality rate in Europe. Most scientists agree that there is not a single cause of colony losses but the interaction of different stressors are involved.

As bee health, bee mortality and disease prevention are strongly related to good beekeeping practices, an approach not yet investigated in Belgium. This approach is to study in detail the beekeeping management practices and correlate them with the bee mortality rates. However, to date, there is no comprehensive inventory of beekeeping practices in Belgium which makes it impossible to link the mortality rates to management practices among beekeepers. The existence of a register can help discover deficient beekeeping practices that might be related to bee mortality.

### Methods:

The University of Liège (ULg) in collaboration with the University of Ghent (U-Gent) is working on a national survey: Project Bee Best Check, that aims to check, understand and analyse the beekeeping practices through Belgium. Therefore, data about beekeepers, equipment, bee population and queens, feeding and use of pesticides for apicultural (veterinary) applications across the Belgian territory will be listed and correlate with the bee mortality. The assessment of the beekeeping practices will be done with a face-to-face questionnaire to strive for high response rates, gain in response quality and create the creation of a relationship between scientists and beekeepers. Registers of beekeepers from the federal agency for the safety of the food chain is used for a random sample selection of beekeepers, in every Belgian province. Wax samples will be obtained from the randomized Belgian apiaries and will be analysed in terms of number of pesticides type, frequency and concentrations.

### Results and perspective:

the ongoing project aims, in a short term, to establish a first screening of beekeeping practices. In a medium term, a scoring system will be developed to assess the beekeeping practices in a standardized way and this will be linked to the bee mortality rates. An online system will allow every beekeeper to perform regularly self-assessments of their beekeeping practices and follow their evolution in time based on their bee mortality rates.

Keywords: Bee mortality ; colony losses ; beekeeping management practice

<footnote n="1">¹ Research Unit in Epidemiology and Risk Analysis Applied to Veterinary Sciences (UREAR-ULg), Fundamental and Applied Research for Animal Health (FARAH) center, University of Liege - Belgium</footnote>
# A multidisciplinary and evidence-based methodology applied for prioritizing bee diseases in France

Suzanne BASTIAN<fnref n="1" />,<fnref n="4" />, Florence ETORE<fnref n="2" />, Claude SAEGERMAN<fnref n="3" />,<fnref n="4" />

With the aim of reforming the country's animal health governance, the French government has missioned Anses agency to prioritize biological health hazards in various animal productions, among which the honey bee *Apis mellifera*.

An ad hoc group of independent scientists was coordinated by Anses between 2013 and 2014. The prioritization method (expert knowledge elicitation) was derived from the OIE/Anses multi-criteria assessment approach, in a general framework designed also for other animal species. Prevalence, potential of spread, evolution and socio-economic impacts were different domains of criteria taken into account. Uncertainty of each grade was assessed with a scale from 1 to 3.

The complete assessment grades, uncertainty analysis and prioritization are available online https://www.anses.fr/fr/system/files/SANT2013sa0049-01.pdf. As expected, *Varroa destructor*, the American foulbrood *Paenibacillus larvae* and the small hive beetle stand out as major threats, requiring specific collective measures for the control of virulent infectious and parasitic diseases. The European foulbrood *Melissococcus plutonius* is ranked medium due to its persistence in geographical regions with high densities of hives, so even if the disease is less severe, beekeepers may want to control this hazard for the sake of general biosecurity. The consequences of other hazards are either linked to varroa parasitism or depend on other risk factors to which the hives are exposed, especially when the individual and social immunity is affected e.g. by toxic compounds. Many of the viral hazards were assessed with high uncertainty scale, because of the lack of knowledge on their individual role and intrinsic virulence. Indeed, the asymptomatic infection of hives by several viruses simultaneously is very frequent.

This comprehensive assessment approach is a transparent, adaptable and updatable tool to convey multi-criteria expert knowledge, in support of public decision-making in animal health.

<footnote n="1">¹ UMR 1300 Biologie, Epidémiologie et Analyse de Risque, Institut National de la Recherche Agronomique-LUNAM Université, Oniris, Ecole Nationale Vétérinaire, Agroalimentaire et de l'Alimentation Nantes-Atlantique, Nantes, France</footnote>

<footnote n="2">² Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (Anses), Maisons-Alfort, France</footnote>

<footnote n="3">³ Research Unit of Epidemiology and Risk Analysis applied to veterinary science (UREAR-ULg), Fundamental and Applied Research for Animals & Health (FARAH) Center, Faculty of Veterinary Medicine, University of Liege, Liege, Belgium</footnote>

<footnote n="4">⁴ Members of the Expert Committee in Animal health and animal welfare, Anses, Maisons-Alfort, France</footnote>
# Residues from beeswax: a health risk for the consumer?

Olivier Wilmart

Belgian Food Safety Agency (FASFC) - Boulevard du Jardin Botanique 55 B-1000 Brussels - Belgium

<figure><img src="image_78.png" /></figure>

OLIVIER.WILMART@afsca.be

A risk scenario analysis in regard to chronic exposure of consumers to residues of plant protection products and veterinary drugs through the food consumption of contaminated honey and beeswax was conducted. Eighteen residues were selected. The estimation of this potential chronic exposure was based on a worst-case scenario. This consisted in considering a "maximum concentration level" for each residue, in adding the contribution of honey and beeswax to the theoretical maximum daily intake through other foodstuffs, and in verifying if the acceptable daily intake value was not exceeded. In conclusion, the food consumption of honey and beeswax contaminated with these residues considered separately does not compromise the consumer's (= adult of 60 kg b.w.) health, provided maximum residue limits (MRL's) or proposed action limits set out in this paper are met. Specifically, the "zero tolerance" should be applied as action limit to residues of flumethrin as well in honey as in beeswax.
# Classification of adult cattle diseases in Belgium based on a veterinary and a laboratory survey, years 2013-2015

Véronique Renault<fnref n="1" />, Bert Damiaans<fnref n="2" />, Steven Sarrazin<fnref n="2" />, Jeroen Dewulf<fnref n="2" />, Marie-France Humblet<fnref n="3" />, Claude Saegerman<fnref n="1" />

<figure><img src="image_79.png" /></figure>

vrenault@ulg.ac.be

## Objective

The biosecurity measures and controls in the Belgian cattle industry have been strengthened over the years to improve animal health and the safety and quality of the products. Nevertheless, the level of implementation of those measures remains insufficient due to several perceived constraints (e.g: cost, time and lack of evidence). Biosecurity measures to be applied must be prioritized in accordance with the individual farm conditions and the main diseases affecting cattle. Previous prioritization exercises were neither specific to Belgium nor based on an exhaustive list of diseases. This study aimed at classifying the most important diseases in order to improve the technical guidance of farmers regarding disease control and prevention.

## Materials and methods

A list of 72 cattle diseases with occurrences in Europe was developed based on a literature review. Through an online survey, Belgian rural veterinarians were asked to assign a score to each disease according to their frequency, their evolution from 2013-2015 and their perceived importance (list of the top 5 diseases). A total of 107 veterinarians answered the first two questions and 93 the last one. The results of the survey were used to classify the diseases based on their frequency, trends and importance through an additional weighting system.

Additional criteria were taken into account to correct possible underrating (zoonosis of major public health concern or (re)emerging diseases) and overrating (diseases emphasized in recent scientific literature or existing control programs) by the veterinarians. Therefore, regional laboratory databases and previous disease prioritization exercises were also analyzed. A table was developed to synthesize the importance given to each disease based on the outcomes of the veterinary survey, the previous prioritization exercises and the regional laboratories database. Lastly different selection criteria were applied to identify the most important diseases to consider in regard to biosecurity.

## Results

From the online survey 28 diseases were selected. Among them eight diseases were listed in the top 5, frequents and with increasing occurrence: mastitis, bovine respiratory disease, diarrhea/enteritis, distomatosis, interdigital dermatitis, neosporosis, paratuberculosis and scabies.

Seven additional diseases were identified based on the analysis of the regional laboratory data base and eleven based on previous prioritization exercises (major zoonosis and/or (re)emerging diseases mainly).

A total of 46 diseases out of the 72 were therefore classified as important for biosecurity measures implementation.

## Conclusion

The list of 46 most important diseases obtained through this study is coherent with the Belgian context as all the communicable diseases in Belgium are included with the exception of lumpy skin disease and yersiniosis. Out of the 46 diseases, 24 are non-communicable diseases of major importance in Belgium due to their economic impact and high occurrence. This additional list could guide the decision makers in terms of future control programs as they do represent a major concern for the cattle owners.

The diseases listed as important will be reviewed to identify their related risk factors and appropriate biosecurity measures in order to improve the technical guidance for farmers.

The table obtained represents a practical tool for other users who could easily adjust the selection criteria to their specific objectives and needs.

**Keywords:** Classification ; Cattle ; Diseases ; Belgium ; Survey ; Biosecurity

<footnote n="1">¹ Research Unit in Epidemiology and Risk Analysis Applied to Veterinary Sciences (UREAR-ULg), Fundamental and Applied Research for Animal Health (FARAH) center, University of Liege - Belgium</footnote>

<footnote n="2">² Veterinary Epidemiology Unit Department of Reproduction, Obstetrics and Herd Health Faculty of Veterinary Medicine Ghent University - Belgium</footnote>

<footnote n="3">³ Department for Occupational Safety and Health, Biosafety and Biosecurity Unit, University of Liege, Liege - Belgium</footnote>
<figure><img src="image_80.png" /></figure>

Association d'Epidémiologie et de Santé Animale

# Drivers of diseases emergence

7th - 9th Sept. 2016 - Liège (Belgium)
Congress 25 years

Animal epidemiology
Past, present and future
# Keynote lecture

## Main drivers of emerging and re-emerging infectious diseases: Focus on livestock

Juana Bianchini¹, Claude Saegerman¹

¹ Research Unit in Epidemiology and Risk Analysis applied to veterinary sciences (UREAR-ULg), Center for Fundamental and Applied Research for Animal and Health (FARAH), University of Liège, Belgium

Juana Bianchini (Orebro, Sweden, 1976), is a PhD research student at Epidémiologie et Analyse de Risques Appliquées aux Sciences Vétérinaires, University of Liege, Belgium (http://www.dmipfmv.ulg.ac.be/epidemiovet/). She is a Doctor in Veterinary Medicine (Universidad Santo Tomas, Chile) with a Master's in Veterinary Epidemiology from the EpiCentre, Massey University, New Zealand. She has worked in the past as a Veterinary Epidemiologist in the UK on different projects, and her current research focuses on emerging and reemerging infectious diseases in livestock and the risk of introduction to Belgium.

<figure><img src="image_81.png" /></figure>

juana.bianchini@ulg.ac.be

<figure><img src="image_82.png" /></figure>

Livestock contribute significantly to the livelihoods of hundreds of millions of people worldwide. Thus, diseases affecting livestock can have a range of impacts on food supplies, and trade, but more importantly, can be a major threat to animal and human health globally. Economic and socio-economic threats from livestock diseases come in three broad categories: (i) losses in production, productivity and profitability due to the effects of the disease and cost of treatment; (ii) disruptions of local markets, and international trade arising from the control measures aimed at containing the spread of the disease, such as culling, quarantines, travel and trade bans; and (iii) livelihood threats to the poor (FAO, 2013). At a human level livestock diseases are also crucial as nearly two-thirds of human pathogens are zoonotic and, of greater concern, nearly three-quarters of emerging and re-emerging human diseases are zoonoses (Woolhouse and Gowtage-Sequeria 2005, Taylor et al., 2001).

During the twentieth century, tremendous social and technological changes that are likely to continue or accelerate in the twenty-first century occurred. These changes altered the landscape of infectious diseases that affect both animals and humans. Unsurprisingly, in recent years, several animal disease epidemics have emerged within places where they were previously eradicated or had never been present before. Examples in the European Union (EU) and other industrialized nations are foot-and-mouth disease (FMD) in the United Kingdom (UK) in 2001 and more recently in Japan in 2010, avian influenza (AI) in the Netherlands in 2003, bluetongue (BT) in Northern Europe in 2006, Schmallenberg in Germany in 2011 (Knowles et al., 2001; Elbers et al., 2004; Wilson and Mellor, 2009, Saegerman et al., 2011, Martinelle et al., 2012, Muroga et al., 2012). Each of these epidemics has resulted in devastating consequences in terms of animal health, animal welfare and economic losses. From the human health perspective new zoonoses that have caused high-fatality rate in humans have also appeared such as the viral diseases coronaviruses SARS and MERS-CoV, influenza A (H5N1 and H7N9), Hendra and Nipah virus, Ebola haemorrhagic disease (www.who.int/csr/don/en/), and the West Nile outbreak in France in 2003 affecting both humans and animals (Mailles et al., 2003). Consequently, the effective control of livestock diseases is crucial for agronomic health, safeguarding, securing national and international food supplies, and human health drawing the attention of the sectors of agriculture, regulatory agencies, and government, as well as the general public in order to understand the factors or drivers of this emergence.

## Factors affecting disease emergence, re-emergence

The term emerging disease first was used to describe several new pathogens in humans that surfaced in the early 1980s, the most notable example of which was Acquired Immunodeficiency Syndrome (AIDS). Since then the number of emerging diseases in humans has continued to increase, a trend also observed in animals. Eventually the OIE defined an emerging or re-emerging disease as "a new infection or infestation resulting from the evolution or change of an existing pathogenic agent or known infection or infestation, to a new geographic area or population, or previously unrecognised pathogenic agent or disease diagnosed for the first time and which has significant impact on animal or public health" (OIE, 2014). The term is not restricted to livestock or even mammals and birds as there are other species who also incur emerging diseases such as the honey bee colony collapse disorder or chytridiomycosis, a fungal disease of amphibians. The reason or reasons for the emergence or re-emergence of diseases is a complex set of multifactorial circumstances and their importance varies in function of time. Different models have been developed to better understand the forces of these drivers. Daszack et al. (2000), describe the host-parasite ecological continuum; meaning that most emerging diseases exist within a host and parasite continuum between wildlife, domestic animal and human populations. Few diseases affect exclusively only one group, and the complex relations between host populations set the scene for disease emergence. King (2008), describes the convergence model which conceptualises how factors of emergence converge and alter the animal-human-microbe interface and then produce and transmit infectious disease. Both models show that different conditions or events (the 'drivers') align in such a manner as they modify the equilibrium among and between three species: humans, animals, and the infectious organisms resulting in an emerging disease either in livestock or in the human population or both.
## Intensive Agriculture

The factors that drive livestock disease emergence or re-emergence need to be considered against the backdrop of fundamental and global changes in agriculture. In response to human population growth, income increases and urbanisation, world food and agriculture shifted its main focus from supplying cereals as staples to providing an increasingly protein-rich diet based on livestock and fishery products (FAO, 2013). This led (in industrialised nations mostly) to livestock production systems around the world which had been family centred, sustainable low input, and a relative low efficiency to become intensified; where a large numbers of a single species is often produced under confinement conditions. Much of the farming in the developed world is almost entirely of this intensive type, so that throughout there are fewer farms managing larger number of animals. Nowadays intensive livestock production is increasingly the main supply source of animal-source food, enabling steady, bulk production of milk, meat and eggs of standard quality. Intensification of agriculture is one of the main forces of other livestock disease drivers due to many conditions that arise such as: larger quantities of raw materials and products flow within a country and between countries, deforestation and wildlife contact to have agricultural farming land. In the intensification systems, domestic animals have been genetically selected for a specific production, and as a result, they are less hardy and resistant to a high exposure rate of pathogens (Martin et al., 2011). Furthermore, the high density of animals allows the rapid selection and amplification of pathogens that arise from a virulent ancestor (frequently by subtle mutation). A perfect example was the detection of a new Deltacorona virus (PDCoV) in February 2014 detected in the United States in intensive pig production systems, which was similar to a coronavirus detected in Hong Kong in 2012 (EFSA, 2014). All these factors which arise from intensive agriculture in conjunction with different drivers increase the risk for disease entrance and/or dissemination through livestock populations.

## Drivers changing the global disease landscape

1. Expansion of the human population, behaviour. The first and foremost factor contributing to the occurrence of new diseases is the expansion of the human population and the attendant increase in traffic of people, animals, and animal products, bringing all their micro-flora and potential pathogens to new locations. The global human population is expected to increase from approximately 6.5 billion in 2008 to approximately 9.2 billion by 2050 (UNDP 2008). Population growth on such a scale poses enormous challenges for food production in general, as an increased demand for 50 percent more food is expected by 2030, and for livestock in particular, especially in developing countries where increases in household incomes and accompanying urbanisation drives demand for meat and dairy products (Delgado et al., 1999; Jones and Thornton 2009). As Delgado et al. (1999) reported "The livestock revolution that is transforming the sector: A revolution is taking place in global agriculture that has profound implication for human health, livelihoods, and the environment. Population growth, urbanisation, and income growth in developing countries are fuelling a massive increase in demand for food of animal origin". The demand for livestock products is expected to continue growing strongly through the middle of this century driven by population growth, rising affluence and urbanization (FAO 2013). This demand has pushed to further animal intensification systems in developed countries, which may arise more livestock epidemics.

2. Animal species interface. Wildlife species play an increasingly important role in transmission of disease to livestock. The intensification of farming increased settlement of farming in wildlife habitats and farming of wildlife species. With urbanisation also came an increase of diversity of animals kept as pets and also increase of tourism in remote areas. Consequently, this increased contact offers opportunity for potential pathogens to move from one species into another, with subsequent disease and dissemination into the new host population (Blancou et al., 2005). The influenza viruses moving from wild bird populations or perhaps from mammalian reservoirs into poultry are one of the examples. Another example is the Nipah virus outbreak in Malaysia and Singapore in 1998-1999. The virus crossed from wild bats to domestic swine causing an explosive outbreak in high-density swine farms which eventually resulted in widespread exposure of humans and over 250 human cases of encephalitis (Pulliam et al. 2012).

3. Climate change. Climate change impact operates in tandem with the effects of globalisation as a driver of change in disease occurrence, leading to changes in the geographic range and occupancy pattern of disease complexes and pest agents (FAO, 2013). Recent unprecedented climate change is widely predicted to increase the incidence and intensity of vector-borne disease transmission, largely through direct effects of climate on vector biology, abundance and distribution. Climate change in combination with other factors, in particular, international trade led by globalisation, may be responsible for the apparent increase in the incidence of arthropod-borne viral diseases in the eastern Mediterranean basin, which is posing a risk to the template climate zones of Europe. Notorious examples: emergence of bluetongue virus type 8 in Northern Europe 2006 and in central Europe the West Nile virus lineage 1 and 2 in 2004 (Bokonyi et al. 2006, Toussaint et al. 2006). Changes in biodiversity will arguably lead to changes in disease patterns and diseases may bring biodiversity loss.
4. Husbandry and technological changes. With the intensification of agriculture husbandry and technological changes had to follow bringing new diseases. Bovine spongiform encephalopathy is a striking example of how seemingly simple changes in agricultural technology can have far reaching impacts on animal agriculture, human health, and economies. The emergence of antibiotic resistant strains of bacteria was also occurred as they were used as growth promoters (now banned in the European Union) and to decrease the incidence of disease which arise from high density of animals confided in a single place.

5. Globalisation and travel. While globalisation has yielded many benefits for society, it also has created many new challenges, particularly with regard to animal, human, and environmental health. In intensive agriculture, larger quantities of raw materials and products flow within a country and between countries. Today, with free trade and the interconnectedness of economies, the increased movement of live animals and animal products crossing oceans and international boundaries corresponds to an increased risk in the spread of animal and zoonotic diseases (Brown 2004). African swine fever is likely to have been introduced into Georgia via imports of contaminated pig products from Eastern Africa or Madagascar (Rowlands et al., 2008). Since then, the disease has subsequently spread to Eastern Europe and the Baltic countries, most likely through movements of infected wild boars and domestic pigs, and contaminated pig products.

6. War and Terrorism. War is a disruptive force on animal health. It can lead to the breakdown of specific disease control programs or the collapse of the veterinary medical infrastructure itself (Sherman 2010). Conflict also produces refugee populations, and in agricultural societies refugees often flee with their animals, bringing livestock disease to new areas of their own countries or into neighbouring countries. The spectre of bioterrorism adds a new threat more to humans as most of potential bioterrorist agents are zoonotic diseases.

## Conclusions and perspectives

All the diseases drivers are interconnected with each other and in a constant change. Thus, it is clear that livestock infectious diseases are anticipated to continue emerging or re-emerge unless more effective actions are taken to address the variety of underlying causes.

In the past it was thought that with good disease reporting, neighbouring countries could remain free from animal disease, provided that border security in conjunction with quarantine measures were well maintained. For many decades this approach, was an effective defence against the occurrence of transboundary disease of animals. Past and current examples however, have shown these measures are not as reliable and there is a need for a more integrated, transdisciplinary, system-based approach to understand and control disease emergence, their spread and persistence. Thus, early detection remains an important priority and the next frontier for livestock diseases surveillance is to improve the recognition and monitoring of drivers of re-emergence or emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated infection disease risk, thereby triggering targeted active surveillance and interventions (Thurmond 2003, Jebara 2004). An example of what can be used is prioritisation of animal pathogens in order to effectively target the use of resources to manage the risk of outbreak. This type of ranking must take account of the infectious nature, the ease and mode of transmission of the disease, identification, and specific early mitigation or preparedness measures that will positively influence outcomes (Humblet et al., 2012). It is also important to consider that the One Health approach to disease risk management within a holistic framework is rapidly gaining in importance in the international arena, but to succeed major institutional and policy support will be necessary to determine the best use of human and financial resources in the prevention and control of animal infectious diseases (Coker et al. 2011, King et. al., 2004). Within this holistic frame the use of prioritisation of animal pathogens can be useful as this type of method can be applicable across a range of pathogens and be easily updateable from year to year to reflect changing threats (Humblet et al., 2012). Thus, it can help to determine the best use of human and financial resources in the prevention and control of animal infectious diseases.

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Selected oral presentations

Illegal meat trade – a threat to both biodiversity and public health

Anne-Lise Chaber<fnref n="1" />,<fnref n="2" />,<fnref n="3" />, Yves Lignereux<fnref n="4" />, Sarah Temman<fnref n="5" />, Christelle Desnues<fnref n="5" />, Andrew Cunnigham<fnref n="3" />

<figure><img src="image_83.png" /></figure>

alchaber@hotmail.com

Concerns have been raised about the illegal import of bushmeat from Africa into Europe. We highlight that illegal bushmeat traffic is an important threat to biodiversity conservation with CITES species being not only imported for personal consumption but also as part of a lucrative organized trade. Seemingly this trade is also posing health risks to people and livestock that have not been thoroughly assessed yet. After estimating the scale of this international trade, finding around five tons of bushmeat per week smuggled in personal baggage through Paris Roissy-Charles de Gaulle airport, we sampled 18 illegal African bushmeat consignments and tested them for the presence of bacteria. Additionally, five smuggled smoked fish were analysed for polycyclic aromatic hydrocarbons, which are known carcinogens. All bushmeat samples had viable counts of aerobic bacteria above levels considered safe for human consumption. We also identified zoonotic bacterial pathogens in bushmeat and unsafe levels of carcinogens in fish. In addition, African simian bushmeat seized by French customs at Toulouse-Blagnac airport were screened for viral pathogens. Epifluorescence microscopy revealed the presence of virus-like particles in the samples. The illegal importation of meat is a potential risk for the introduction of pathogens into Europe.

**Keywords:** MEAT TRADE, BIODIVERSITY, PUBLIC HEALTH

Recombination (genetic evolution) as driver of new epidemic norovirus strains

Louisa Ludwig<fnref n="1" />, Edmilson De Oliveria-Filho <fnref n="1" />,<fnref n="2" />, Elisabeth Mathijs <fnref n="1" />,<fnref n="3" />, Axel Mauroy<fnref n="1" />, Etienne Thiry<fnref n="1" />

<figure><img src="image_84.png" /></figure>

amauroy@ulg.ac.be

Noroviruses (NoVs) have been detected in both humans and several animal species. In humans, they are now considered as important viral causes of gastroenteritis. Viruses presenting genetic relatedness have been found in feces samples from both diarrheic and non-diarrheic animals of various species. The zoonotic risk associated to animal strains is currently considered low according to phylogenetic evidence from circulating strains and limited results of receptor characterization for strains infecting cattle. However, related data are still lacking, especially regarding receptors for most porcine strains and a few bovine ones. Furthermore, research is hampered by the lack of a robust cell culture system and animal model for human NoVs, as well as for the large majority of animal NoVs (murine NoVs are the exception for which both in vitro and in vivo homologous models are yet available). Recombination has been shown as an important driver of genetic evolution for several viruses. In NoVs, recombination, occurring at the open reading frame (ORF) 1/ORF2-3 junction, usually allows the exchange of non-structural and structural coding regions between co-infecting strains and stimulates the emergence of chimaera harboring fitness and/or antigenic modifications. These chimeras then enter into competition for selection against their parental strains. Recombinant human and animal NoV sequences have mainly been in silico detected; however we recently isolated a recombinant murine NoV (RecMNV), following in vitro co-infection in a murine macrophagic cell line. RecMNV conserved in vivo infectivity. While it was primarily shown to be less fit than parental viruses in vitro, probably due to less-efficient between-genes conversation, regain of fitness for RecMNV was observed after a few replication cycles. This regain of fitness was associated to particular genomic mutations. In humans, recombination has been identified to promote the emergence of new epidemic strains, in particular for those genetically related to the genogroup II genotype 4 (the most prevalent genotype worldwide). In animals, different chimeras have also been identified, in particular in the bovine species for which a recent chimeric strain was detected in Argentina, increasing the genetic and antigenic diversity of the strains circulating in cattle. In conclusion, recombination in NoVs can be considered as a driver of emerging strains, providing new antigenic properties facing the host immune system. Even if these strains can be first disadvantaged in their replication efficacy, regain of fitness can be quickly reached through genetic mutations. The question of the zoonotic risk and its correlate of potential creation of human/animal recombinant strains are still pending and deserve attention.

**Keywords:** norovirus, recombination, genetic evolution

<footnote n="1">¹ Faculty of Veterinary Medicine, University of Liège (UREAR-ULg, FARAH) – Belgium</footnote>

<footnote n="2">² Wildlife Consultant L.L.C, Al Ain. - United Arab Emirates</footnote>

<footnote n="3">³ Institute of Zoology, Zoological Society of London, Regents Park, London – United Kingdom</footnote>

<footnote n="4">⁴ Ecole Nationale Vétérinaire and Museum d'Histoire Naturelle de Toulouse – Museum d'Histoire Naturelle de Toulouse – France</footnote>

<footnote n="5">⁵ CNRS, UMR 7278, Marseille – CNRS : UMR7278 – France</footnote>

<footnote n="1">¹ Veterinary Virology and Animal Viral Diseases, Fundamental and Applied Research for Animals and Health, Faculty of Veterinary Medicine, University of Liège, Belgium - Belgium</footnote>

<footnote n="2">² Department of Virology, Oswaldo Cruz Fundation (Fiocruz), Aggeu Magalhaes Research Center (CPqAM), Recife, Brazil - Brazil</footnote>

<footnote n="3">³ Department of Virology -Molecular Platform, Veterinary Agrochemical Research Centre, 1180 Brussels, Belgium - Belgium</footnote>
# Bayesian assessment of two competitive ELISAs for the detection of bovine viral diarrhoea virus antibodies in bovine sera

Claude Saegerman<fnref n="1" />, Christian Quinet<fnref n="2" />, Guy Czaplicki<fnref n="2" />, Fabiana Dal Pozzo<fnref n="1" />

Infections due to bovine viral diarrhoea virus (BVDV) are endemic in most cattle-producing countries throughout the world. Bovine viral diarrhoea is considered a transboundary disease. The key elements of a BVDV control programme are biosecurity, elimination of persistently infected (PI) animals and surveillance. The aim of this study was to assess the sensitivity (Se) and the specificity (Sp) of two commercial competitive ELISA tests based on selected immunodominant BVDV proteins, respectively the non-structural protein NS3 (p80) and the recombinant envelop glycoprotein E0 (Erns). Both tests were used on individual serum randomly sampled from young bovines in Southern Belgium in order to detect specific BVDV antibodies. Se and Sp were assessed using a Bayesian approach. The Se and Sp were estimated respectively at 97.2% (with 95% credibility interval [Cr I]): 95.1-99.8) and 98.7% (95% Cr I: 96.6-99.9) for the first test and 95.8% (95% Cr I: 91.1-99.7) and 96.1% (95% Cr I: 95.1-97.7) for the second test. The results obtained with the two tests were not significantly different. In addition using both ELISAs, the current BVDV exposure among young bovines in Southern Belgium was estimated at 23.3% (95% Cr I: 20.6-26.2). Combining virological testing of all newborns to detect persistently infected animals with regular serological testing using ELISA tests of young stock would be recommended in the surveillance of BVDV.

**Keywords:** Bovine viral diarrhoea virus, Cattle, Sensitivity, Specificity, Bayesian framework, Assessment, ELISA, diagnosis

# A Bayesian evaluation of four antibody ELISA tests to certify freedom of bovine viral diarrhea infection in unvaccinated cattle

Sophie Roelandt<fnref n="1" />, Jean-Baptiste Hanon<fnref n="1" />, Miet De Baere<fnref n="1" />, Yves Van Der Stede<fnref n="1" />,<fnref n="2" />, Christel Faes³, Ann-Brigitte Cay<fnref n="1" />

In Belgium's BVD control program, commercial antibody ELISA kits will be used to ascertain freedom of disease at herd level based on individual sera from unvaccinated cattle, starting July 2017. Commercial BVDV Ab ELISA kits were previously evaluated, using Belgian field sera from 19 unvaccinated herds (n=1313) and using VNT as gold standard. VNT-seroprevalence was 46.10% (npos=603/1308; 95%CI: 43.41-48.81%). However, there are no "perfect" tests BVDV infection detection in adult/young cattle. Even VNT has a grey zone (19 borderline samples were considered negative), favouring less sensitive ELISA's. Therefore, four tests (Svanova[A] -Idexx[B] -Prionics[C] -Bio-X[D]) were re-evaluated with no gold standard approach. A total of n=1313 available sera from unvaccinated herds were tested with the selected ELISA's and BVDV VNT. Test results were entered in a "4test1population" Bayesian model, including 2-way test dependence parameters and uninformative priors for all parameters (UN). As prior sensitivity analysis, six more prior scenarios were used in the same model: informative priors on test diagnostic accuracy ~previous experience (TEST1-2); informative priors on population prevalence ~SNT results (PREV1-2); all informative priors (TP1-2). All models were estimated using MCMC (2 chains, 10,000 iterations burn-in, results on 50,000 iterations, thinning 10); model diagnostic criteria were satisfactory; Deviance Information Criterion (DIC) indicated little influence of priors on posteriors.
The parameter estimates were comparable for all scenarios and reported from the UN-model (CI:95% credible interval). Diagnostic Sensitivity: TestA: 97.76% (CI:96.08-98.96%) -TestB: 99.86% (CI:99.21-99.99%) -TestC: 99.23% (CI:77.58-99.99%) -TestD: 94.45% (CI:92.13-96.52%); Diagnostic Specificity: TestA: 95.24% (CI:92.50-97.47%) -TestB: 91.31% (CI:88.27-93.95%) -TestC: 95.28% (CI:91.26-98.43%) -TestD: 95.18% (CI:92.21-97.33%); Population Prevalence: 44.98% (CI:42.17-47.88%). The four ELISA's slightly underestimate the population seroprevalence in this model, but the 95%CI includes actual VNT seropositivity (~46%). Additional predictive values and Youden's indexes to investigate diagnostic test performance were calcu-lated within UN model. These parameter estimates were also highly comparable but some were statistically different (Bayesian p-values > 0.05).

Based on predictive values in the study population and biological interpretation of these accuracy parameters, all tests were sufficiently fit for purpose at the herd level, despite expected false negative/positive fractions of 1-5% / 5.5-10% at the individual level. This Bayesian comparative study agreed with gold standard evaluation and demonstrated all four tests under evaluation possessed high accuracy, though testD could increase the cut-off a little to align DSe/DSp with the other tests. Observed statistical differences may not be clinically significant at the herd level. Based on predictive values, all tests are "fit for purpose" for their purpose in the Belgian BVD control program. Clinicians/Laboratories need to take these characteristics into account during individual/herd diagnostics with VNT confirmation for ELISA-seropositive results.

**Keywords:** Bayesian evaluation, BVDV, antibody ELISA, SNT, certification of freedom

<footnote n="1">¹ Research Unit in Epidemiology and Risk Analysis applied to veterinary sciences, Center for Fundamental and Applied Research for Animal and Health (FARAH), University of Liege, Liege (UREAR-ULg, FARAH) - Belgium</footnote>

<footnote n="2">² Association Régionale de Santé et d'Identification Animales (ARSIA) - Allée des Artisans 2 5590 Ciney, Belgium</footnote>

<footnote n="1">¹ Veterinary and Agrochemical Research Centre (CODA-CERVA) - Brussels, Belgium</footnote>

<footnote n="2">² Ghent University (UGent) - Merelbeke, Belgium 3 Hasselt University (UHasselt) - Hasselt, Belgium</footnote>

<footnote>Sophie.Roelandt@coda-cerva.be</footnote>
Posters

# Seasonal variations of micromammal communities and the risk of tick-borne disease in a hedgerow agro-ecosystem

Grégoire Perez <fnref n="1" />,<fnref n="2" />, Alain Butet <fnref n="1" />, Albert Agoulon <fnref n="2" />, Suzanne Bastian <fnref n="1" />,<fnref n="2" />, Olivier Plantard <fnref n="2" />

<figure><img src="image_85.png" /></figure>

perez.gregoire@gmail.com

An increase in the emergence/reemergence of infectious diseases of human and his domestic animals has been observed in recent decades. Most of these diseases are zoonotic and imply often a vector for their transmission. At the same time, land use changes linked to agricultural intensification and/or climate change have modified or will modify the landscapes. The aim of this study was to better understand the mechanisms involved in the maintenance of tick-borne diseases, in order to identify key factors of changes in transmission dynamics. We assessed intrinsic traits of small mammals linked to prevalence of two tick-borne infectious agents of potential public or animal health concern: Anaplasma phagocytophilum and Borrelia burgdorferi s.l., taking into account seasonal and interannual variations. Small mammals were live-trapped using 24 standardized trap-lines in May-June and October 2012 and 2013. 6 plots were located in a large deciduous forest, 6 at forest-meadow ecotones, 6 at woodlot-meadow ecotones, and 6 at hedgerow-meadow ecotones. Those last 18 plots were disseminated either in an agricultural matrix constituted of mixed farming systems or in more intensive crop-oriented farming systems. This sampling scheme represented all the dominant landscapes of the area. Captured animals were euthanized and the infectious tick-borne pathogens were searched for in tissue samples by PCR.

Out of the 607 animals tested for both infectious agents, 42 were positive to A. phagocytophilum and 26 were positive to B. burgdorferi s.l.. Significant variation was observed between years, with higher prevalence in the year with low animal abundance. Seasonal variation was also observed, with higher prevalence in autumn of both years. We also found a significant difference in the prevalence in the two dominant species. Wood mice, despite harboring more ticks, had lower prevalence than bank voles. The prevalence of these two tick-borne infectious agents varied in time, possibly in relation to population density. Our results suggest a different implication of host species as infectious disease reservoir or as tick population dynamics amplifier. Long-term changes in small mammal abundance and/or community structure caused by global changes (i.e. climate change and land use changes) can have drastic impact on tick-borne disease transmission. The conduct of long-term studies at the meta-community level (i.e. hosts and vectors) is recommended to anticipate changes in tick-borne diseases transmission and anticipate possible outbreaks.

**Keywords:** tickborne disease, Reservoir, emergence, global change

<footnote n="1">¹ Ecosystèmes, biodiversité, évolution (ECOBIO) - INEE, Université de Rennes 1, CNRS : UMR6553, Observatoire des Sciences de l'Univers de Rennes - Bâtiment 14 - Université de Rennes 1 - Campus de Beaulieu - CS 74205 - 35042 Rennes Cedex - France, France</footnote>

<footnote n="2">² Biologie, Epidémiologie et analyse de risque en Santé Animale (BIOEPAR) - Institut national de la recherche agronomique (INRA) : UMR1300 - ONIRIS : Site de la Chantrerie CS 40706 44307 Nantes cedex 3 Site de la Géraudière CS 82225 44322 Nantes cedex 3, France</footnote>
<figure><img src="image_86.png" /></figure>

Association d'Epidémiologie et de Santé Animale

Zoonoses and
public health

7th - 9th Sept. 2016 - Liège (Belgium)
Congress 25 years

Animal epidemiology
Past, present and future
# Posters

## Rabiës: a still present-day deadly thread

### Geraldine Boseret

Belgian Federal Agency for the Security of the Food Chain (FASFC) - Belgium

<figure><img src="image_87.png" /></figure>

galdine.boseret@afsca.be

Even if European Member States are for the most part free of Rabiës, this zoonose still kills people.

Around 55000 persons dies every year of infection by the Lyssavirus causing rabies.

Most of them are children from underdeveloped or developing countries, such as Morocco, who have been in contact with carriers or infected street dogs or cats.

But the thread presents also another pattern: the illegally smuggled kitten or puppies coming from civilised countries, but not Rabies-free.

Every year, around 200 suspicions of rabies-infected pets are reported in Belgium.

The FAFSC, along with the customs and the vets, is in first line in this fight against a still deadly disease.

Keywords: rabies; zoonosis; illegal; dogs; cats

## Evaluation of immunofluorescence antibody test used for the diagnosis of canine leishmaniasis in the Mediterranean basin: a systematic review and meta-analysis

Amal Adel<sup>1, 2, 3</sup>, Dirk Berkvens<sup>3</sup>, Emmanuel Abatih<sup>3</sup>, Abdelkrim Soukehal<sup>4</sup>, Juana Bianchini<sup>2</sup>, Claude Saegerman<sup>2</sup>

<figure><img src="image_88.png" /></figure>

adelamel2002@yahoo.fr

With an expected sensitivity (Se) of 96% and specificity (Sp) of 98%, the immunofluorescence antibody test (IFAT) is frequently used as a reference test to validate new diagnostic methods and estimate the canine leishmaniasis (CanL) true prevalence in the Mediterranean basin.

To review the diagnostic accuracy of IFAT to diagnose CanL in this area with reference to its Se and Sp and elucidate the potential causes of their variations, a systematic review was conducted (31 studies for the 26-year period). Three IFAT validation methods stood out: the classical contingency table method, methods based on statistical models and those based on experimental studies. A variation in the IFAT Se and Sp values and cut-off values was observed. For the classical validation method based on a meta-analysis, the Se of IFAT was estimated in this area as 89.86% and 31.25% in symptomatic and asymptomatic dogs, respectively. The Sp of IFAT was estimated in non-endemic and endemic areas as 98.12% and 96.57%, respectively.

IFAT can be considered as a good standard test in non-endemic areas for CanL, but its accuracy declines in endemic areas due to the complexity of the disease. Indeed, the accuracy of IFAT is due to the negative results obtained in non-infected dogs from non-endemic areas and to the positive results obtained in sera of symptomatic dogs living in endemic areas. But IFAT results are not unequivocal when it comes to determining CanL infection on asymptomatic dogs living in endemic areas. Statistical methods might be a solution to overcome the lack of gold standard, to better categorize groups of animals investigated, to assess optimal cut-off values and to allow a better estimate of the true prevalence aiming information on preventive/control measures for CanL.

Keywords: canine leishmaniasis; diagnosis; IFAT; dogs; cutoff; systematic review; meta; analysis; Mediterranean

<footnote n="1"><sup>1</sup> Institute of Veterinary Sciences, University Saad Dahlab, Blida, Algeria</footnote>

<footnote n="2"><sup>2</sup> Research Unit in Epidemiology and Risk Analysis applied to veterinary sciences, Center for Fundamental and Applied Research for Animal and Health (FARAH), University of Liege, Liege - Belgium</footnote>

<footnote n="3"><sup>3</sup> Institute of Tropical Medicine Department of Biomedical Sciences (ITM) - Antwerpen - Belgium</footnote>

<footnote n="4"><sup>4</sup> University Hospital of Beni Messous - Algiers - Algeria</footnote>
# Prevalence of bovine brucellosis and risk factors assessment in cattle herds in Mostaganem, northwestern Algeria

Meki Boutaiba Benklaouz <fnref n="1" />, Qada Benameur <fnref n="2" />, Hebib Aggad <fnref n="1" />

<figure><img src="image_89.png" /></figure>

meki1327@yahoo.com

## Background

Brucellosis is a zoonotic disease with economic and public health impact, particularly for human and animal populations within developing countries that relay on livestock production.

## Objective

The present study aimed to estimate the seroprevalence of and risk factors for bovine brucellosis.

## Methods

In total, 2231 cattle of different ages and sexes selected from 291 herds, across the four districts of Mostaganem province, northwestern Algeria, were blood sampled. Rose Bengal Plate Test and complement fixation test were used for detection of antibodies against *Brucella* species.

## Results

From the results 48 cattle (2.15%) were positive by Rose Bengal plate test, while 32(1.43%) were positive with complement fixation test. The infection rate was higher in females than males. Cattle older than 3 years had a higher prevalence rate compared to age groups 2-3 years, and 1-2 years. The prevalence rate was higher in cattle densely populated locations. Purchase of animals without prior diagnosis, lack of awareness and routine milk testing were found as other potential risk factors for transmission of disease.

## Conclusions

This warrants the need of integrated intervention strategies to minimize the spread of the disease in animals and reduce the risk of transmission to humans.

**Keywords:** Brucellosis; cattle herds; risk factors; Mostaganem

<footnote n="1">¹ Institut des sciences vétérinaires, Université Ibn Khaldoun, Tiaret, Algeria</footnote>

<footnote n="2">² Département des sciences infirmières, Faculté des sciences de la nature et de la vie, Université Abd El-Hamid Ibn Badis, Mostaganem, Algeria</footnote>
Authors Index

Aggad

<table><tr><td>Hebib</td><td>97</td></tr></table>

Agnoletti

<table><tr><td>Fabrizio</td><td>26</td></tr></table>

Agurdin

<table><tr><td>Maria</td><td>44</td></tr></table>

Al Dahouk

<table><tr><td>Sascha</td><td>14</td></tr></table>

Allepuz

<table><tr><td>Alberto</td><td>7, 60, 61</td></tr></table>

Amory

<table><tr><td>Hélène</td><td>15</td></tr></table>

Anaya

<table><tr><td>Lourdes</td><td>61</td></tr></table>

Antoine-Moussiaux

<table><tr><td>Nicolas</td><td>47</td></tr></table>

Appoloni

<table><tr><td>Andrea</td><td>9</td></tr></table>

Bakkemo

<table><tr><td>Kathrine</td><td>14</td></tr></table>

Baldo

<table><tr><td>Aline</td><td>63</td></tr></table>

Bardiau

<table><tr><td>Marjorie</td><td>44</td></tr></table>

BASTIAN

<table><tr><td>Suzanne</td><td>82</td></tr></table>

Beeuwsaert

<table><tr><td>Koen</td><td>81</td></tr></table>

Beltran-Alcrudo

<table><tr><td>Daniel</td><td>60</td></tr></table>

Benameur

<table><tr><td>Qada</td><td>48, 97</td></tr></table>

Benmahdi

<table><tr><td>Meriem-Hind</td><td>48</td></tr></table>

Berends

<table><tr><td>Inge</td><td>16</td></tr></table>

Bianchini

<table><tr><td>Juana</td><td>86</td></tr></table>

Bonfanti

<table><tr><td>Lebana</td><td>26</td></tr></table>

Bortolotti

<table><tr><td>Laura</td><td>8, 71</td></tr></table>

Boseret

<table><tr><td>Géraldine</td><td>4, 96</td></tr></table>

Botteldoorn

<table><tr><td>Nadine</td><td>45</td></tr></table>

Boutaiba Benklaouz

<table><tr><td>Meki</td><td>48, 97</td></tr></table>

Breda

<table><tr><td>Tatiana</td><td>71</td></tr></table>

Brichese

<table><tr><td>Michele</td><td>8, 71</td></tr></table>

Brisse

<table><tr><td>Sylvain</td><td>46</td></tr></table>

Brouwer

<table><tr><td>Henriette</td><td>16</td></tr></table>

Brunetta

<table><tr><td>Romina</td><td>26</td></tr></table>

Buniolo

<table><tr><td>Filippo</td><td>26</td></tr></table>

Calba

<table><tr><td>Clémentine</td><td>58</td></tr></table>

Capello

<table><tr><td>Katia</td><td>26</td></tr></table>

Cardenas

<table><tr><td>Liliana</td><td>74</td></tr></table>

Cargnel

<table><tr><td>Mickaël</td><td>10</td></tr></table>

Casal

<table><tr><td>Ester</td><td>61</td></tr><tr><td>Jordi</td><td>7, 60, 61, 74</td></tr></table>

Cassart

<table><tr><td>Dominique</td><td>55</td></tr></table>

Cay

<table><tr><td>Ann-Brigitte</td><td>31, 69, 72</td></tr></table>

Cerri

<table><tr><td>Simona</td><td>15</td></tr></table>

Chaber

<table><tr><td>Anne-Lise</td><td>9, 21, 53, 91</td></tr></table>

Chávez-Larrea

<table><tr><td>María-Augusta</td><td>35, 36</td></tr></table>

Ciaravino

<table><tr><td>Giovanna</td><td>61</td></tr></table>

Claine

<table><tr><td>Francois</td><td>34</td></tr></table>

Cloeckaert

<table><tr><td>Axel</td><td>38</td></tr></table>

Cobianchi

<table><tr><td>Mario</td><td>8</td></tr></table>

Collin

<table><tr><td>Eric</td><td>32</td></tr></table>

Coupeau

<table><tr><td>Damien</td><td>34</td></tr></table>

Cunnigham

<table><tr><td>Andrew</td><td>91</td></tr></table>

Czaplicki

<table><tr><td>Guy</td><td>6, 17, 31</td></tr></table>

Daï Do Thi

<table><tr><td>Chuong</td><td>63</td></tr></table>

Dal Pozzo

<table><tr><td>Fabiana</td><td>6</td></tr></table>

Damiaans

<table><tr><td>Bert</td><td>23, 24, 84</td></tr></table>

De Baere

<table><tr><td>Miet</td><td>69</td></tr></table>

De Balogh

<table><tr><td>Katinka</td><td>60</td></tr></table>

De Graaf

<table><tr><td>Dirk</td><td>81</td></tr></table>

De Graef

<table><tr><td>Evelyne</td><td>43</td></tr></table>
**De Oliveria-Filho**
Edmilson .................................................................................. 91

**De Regge**
Nick .................................................................................. 31, 72

**De Rooster**
Hilde .................................................................................. 43

**De Sordi**
Luisa .................................................................................. 46

**De Waele**
Valérie .................................................................................. 15

**Debarbieux**
Laurent .................................................................................. 46

**Delabouglise**
Alexis .................................................................................. 58

**Delooz**
Laurent .................................................................................. 17, 25, 31

**Denis**
Olivier .................................................................................. 44

**Desnues**
Christelle .................................................................................. 91

**Dewulf**
Jeroen .................................................................................. 23, 24, 42, 43, 84

**Dierick**
Katelijk .................................................................................. 45

**Dion**
Elise .................................................................................. 25

**Dominguez**
Morgane .................................................................................. 19

**Dorotea**
Tiziano .................................................................................. 26

**Ducheyne**
Els .................................................................................. 30

**Dufour**
Nicolas .................................................................................. 46

**Duprez**
Jean-Noël .................................................................................. 44, 45, 75

**El Agrebi**
Noëmie .................................................................................. 81

**Esplugia**
Josep .................................................................................. 61

**ETORE**
Florence .................................................................................. 82

**Fakih**
Ibrahim .................................................................................. 75

**Fett**
Thomas .................................................................................. 55

**Filippitzi**
Marilena .................................................................................. 42

**Flor**
Matthias .................................................................................. 56

**Fourichon**
Christine .................................................................................. 16

**Fretin**
David .................................................................................. 53, 70, 73

**Gilbert**
Marius .................................................................................. 12

**Godfroid**
Jacques .................................................................................. 14, 73

**González-Martínez**
Zulay .................................................................................. 35

**Gortázar**
Christian .................................................................................. 50

**Goutard**
Flavie .................................................................................. 58

**Grégoire**
Fabien .................................................................................. 6

**Greiner**
Matthias .................................................................................. 56

**Gustin**
Pascal .................................................................................. 47

**Hanon**
Jean-Baptiste .................................................................................. 69

**Heilmann**
Martin .................................................................................. 60

**Hendrickx**
Guy .................................................................................. 15, 30

**HENDRIKX**
Pascal .................................................................................. 2

**Heremans**
Evelien .................................................................................. 23

**Herman**
Philippe .................................................................................. 63

**Houben**
Rachel .................................................................................. 15

**Houtain**
Jean-Yves .................................................................................. 17, 25, 31, 69

**Humblet**
Marie-France .................................................................................. 22, 84

**Ibarra**
Patricia .................................................................................. 61

**Kia**
Grace .................................................................................. 54

**Kirschvink**
Nathalie .................................................................................. 6, 34

**Korsak**
Nicolas .................................................................................. 75

**Lanari**
Manuela .................................................................................. 8

**Larsen**
Anett .................................................................................. 14

**Lesenfants**
Christophe .................................................................................. 55

**Leunda**
Amaya .................................................................................. 63

**Lignereux**
Louis .................................................................................. 9, 53
Yves .................................................................................. 91

**Linden**
Annick .................................................................................. 55

**Lopez**
Sergi .................................................................................. 61

**Ludwig**
Louisa .................................................................................. 91

**Mainil**
Jacques .................................................................................. 44, 45, 46, 75

**Manso-Silvan**
Lucia .................................................................................. 9
**Marangon**
Stefano..................................................................................71

**Martín**
Gerard..................................................................................7

**Mateu**
Enric..................................................................................7

**Mathevet**
Pierre..................................................................................32

**Mathijs**
Elisabeth................................................................................91

**Mauroy1**
Axel..................................................................................91

**Mazzucato**
Matteo..................................................................................26

**Meersschaert**
Carole..................................................................................15

**Mercader**
Irene..................................................................................61

**Michiels**
Marie-Pierre........................................................................25, 69
Rodolphe............................................................................72

**Moula**
Nassim..................................................................................47

**Moussa**
Sanogo..................................................................................53

**Müller-Graf**
Christine............................................................................56

**Munstermann**
S. 19

**Muylaert**
Adeline..................................................................................45

**Muylkens**
Benoît..................................................................................34

**Napp**
Sebastian................................................................................61

**Ngassam-Tchamba**
Cyrille................................................................................44, 45

**Nymo**
Ingebjørg............................................................................14

**Odoba**
Mathias..................................................................................54

**Oudin**
Héloïse..................................................................................22

**Pacios**
Alberto................................................................................61

**Passet**
Virginie................................................................................46

**Paternostre**
Julien..................................................................................55

**Pelletier**
Claire..................................................................................32

**Peroz**
Carole..................................................................................16

**Petit**
Etienne..................................................................................32

**Petitjean**
Thierry..................................................................................31

**Peyraud**
Armelle..................................................................................9

**Peyre**
Marisa..................................................................................58

**Pham Hoa**
Thi Thanh............................................................................58

**Pilar Jiménez De Bagüés**
María..................................................................................14

**Pitel**
Pierre-Hugues........................................................................15

**Quinet**
Christian........................................................................17, 31, 72

**Renault**
Véronique........................................................................84

**Reyna-Bello**
Armando........................................................................35, 36

**Rizzo**
Simone................................................................................8, 71

**Rodrígue-Cabezas**
Andrea..................................................................................35

**Roelandt**
Sophie..................................................................................30

**Roels**
Stefan..................................................................................30

**Roger**
François..................................................................................58

**Ron-Román**
Jorge..................................................................................35, 36

**Roupie**
Virginie..................................................................................70

**Roy**
Christelle..................................................................................32

**Ryan**
Aguanno..................................................................................60

**Saegerman**
Claude ..1, 6, 9, 17, 21, 22, 31, 53, 65, 70, 81, 82, 84, 86

**Sarrazin**
Steven................................................................................23, 24, 42, 43, 84

**Saulmont**
Marc..................................................................................45

**Schlepers**
Marjolijn................................................................................43

**Schmidt-Chanasit**
Jonas..................................................................................28

**Scippo**
Marie-Louise........................................................................47

**Sellal**
Eric..................................................................................32

**Sèmanou Dognon**
Robert..................................................................................47

**Seppola**
Marit..................................................................................14

**Suin**
Vanessa..................................................................................30

**Takaki**
Shino..................................................................................75

**Tana-Hernández**
Leandro..................................................................................36

**Tavares-Marque**
Lucinda..................................................................................35
**Tchuenkam Kamdem**
Nadège..................................................55

**Temman**
Sarah................................................................91

**Thiaucourt**
François................................................................9

**Thiry**
Damien..................................................44, 45, 46, 75
Etienne..................................................91

**Trimarchi**
Donata ....................................................8, 71

**Ukuma**
Blessing..................................................54

**Van Der Stede**
Yves................................................................16, 30, 70, 73

**Van Gucht**
Steven................................................................30

**Van Mael**
Eva ................................................................72

**Van Schaik2**
Gerdien..................................................16

**Vandael**
Femke....................................................43

**Vanrobaeys**
Mia ................................................................45

**Vayssier**
Muriel....................................................32

**Veldhuis**
Anouk....................................................16

**Volpe**
Rosario ..................................................55

**Weber-Vintzel**
W................................................................19

**Welby**
Sarah ..................................................16, 63, 70, 73

**Wever**
Paul ................................................................16

**Wiggers**
Laetitia..................................................34

**Wilmart**
Olivier..................................................83

**Youssao Abdou Karim**
Issaka....................................................47

**Zonderland**
Jean-Luc................................................32