Virginia Aragon
email: virginia.aragon@cresa.uab.es

Marta Cerdà-Cuéllar

Lorenzo Fraile

Mark Mombarg

Miquel Nofrarías

Alexandre Olvera

Marina Sibila

David Solanes

Joaquim Segalés

Correlation between clinico-pathological outcome and typing of Haemophilus parasuis field strains

Keywords: Glässer's disease, animal model, field strains, Haemophilus parasuis, wild boar

Haemophilus parasuis is the etiologic agent of Glässer's disease in pigs, which is pathologically characterized by serofibrinous polyserositis and arthritis. H. parasuis include virulent and non-virulent strains and confirmation of virulence in H. parasuis is still dependent on experimental reproduction of the disease. Since the variability in virulence is supported by serotyping and genotyping (particularly, multilocus sequence typing [MLST]), we examined the relationship between the classification of 8 field strains by these methods and their capacity to cause disease in snatch-farrowed, colostrum-deprived piglets. The severity of clinical signs and lesions produced by the different strains correlated with the quantity of H. parasuis recovered from the lesions. However, the virulence of the strains in the animal model did not show a total correlation with their serovar or their classification by MLST. More studies are needed to identify a virulence marker that could substitute animal experimentation in H. parasuis. In addition, we reproduced disease in domestic pigs with a strain isolated from the nasal cavity of wild boars. This result indicates the existence of virulent strains of H. parasuis in wild suids, which could produce disease under appropriate circumstances, and suggests a possible source of infection for domestic pigs.

Introduction

Haemophilus parasuis is the etiologic agent of Glässer's disease in pigs, which causes high morbidity and mortality in naive swine populations and is pathologically characterized by serofibrinous to fibrinopurulent polyserositis, arthritis and meningitis [START_REF] Rapp-Gabrielson | Haemophilus parasuis, 9 Edition[END_REF]. H. parasuis strains are heterogeneous and display a diverse degree of virulence. It is also well known that H. parasuis can be isolated from the upper respiratory tract of healthy pigs as part of their normal respiratory microbiota [START_REF] Harris | Incidence of certain microorganisms in nasal cavities of swine in Iowa[END_REF][START_REF] Møller | V factor-dependent members of the family Pasteurellaceae in the porcine upper respiratory tract[END_REF]Olvera et al., 2006aOlvera et al., , 2006b)). Therefore, the differentiation between virulent and commensal strains would improve the diagnosis and control of disease.

Although several studies have identified putative virulence-associated genes, their role in pathogenesis has not been demonstrated [START_REF] Melnikow | Microarray analysis of Haemophilus parasuis gene expression under in vitro growth conditions mimicking the in vivo environment[END_REF][START_REF] Metcalf | Differential expression of Haemophilus parasuis genes in response to iron restriction and cerebrospinal fluid[END_REF][START_REF] Jin | Identification of gene transcribed by Haemophilus parasuis in necrotic porcine lung through the selective capture of transcribed sequences (SCOTS)[END_REF][START_REF] Chen | Understanding Haemophilus parasuis infection in porcine spleen through a transcriptomics approach[END_REF][START_REF] Pina | Trimeric autotransporters of Haemophilus parasuis: generation of an extensive passenger domain repertoire specific for pathogenic strains[END_REF][START_REF] Sack | Identification of novel potential virulence-associated factors in Haemophilus parasuis[END_REF]. Thus, no definite determinant of virulence has been reported so far and the confirmation of the pathogenic potential of H. parasuis isolates still relies on the experimental reproduction of Glässer's disease.

Classically, H. parasuis strains were classified by serotyping [START_REF] Kielstein | Designation of 15 serovars of Haemophilus parasuis on the basis of immunodiffusion using heat-stable antigen extracts[END_REF], but the correlation with virulence is not clear [START_REF] Nielsen | Pathogenicity and immunity studies of Haemophilus parasuis serotypes[END_REF][START_REF] Amano | Pathologic observations of pigs intranasally inoculated with serovar 1, 4 and 5 of Haemophilus parasuis using immunoperoxidase method[END_REF][START_REF] Takahashi | A cross-protection experiment in pigs vaccinated with Haemophilus parasuis serovars 2 and 5 bacterins, and evaluation of a bivalent vaccine under laboratory and field conditions[END_REF][START_REF] Bak | Protection of vaccinated pigs against experimental infections with homologous and heterologous Haemophilus parasuis[END_REF]. On the other hand, sequencing studies revealed two clades of strains in H. parasuis (Olvera et al., 2006a(Olvera et al., , 2006b;;[START_REF] Angen | Development of an improved species specific PCR test for detection of Haemophilus parasuis[END_REF] . In particular, multilocus sequence typing (MLST) showed one cluster associated with systemic disease and a second cluster associated with nasal isolation (Olvera et al., 2006b). This classification was A c c e p t e d M a n u s c r i p t 4 supported by the clinical origin of the strains, but it could not be complemented with data from experimental infections.

Thus, the aim of this study was to analyze the relationship between the severity of disease and the classification of different H. parasuis field strains by serotyping and genotyping. Additionally, we tested the ability of a H. parasuis strain isolated from the nose of a wild boar (Sus scrofa) to produce disease in domestic pigs.

Materials and Methods

Bacterial strains

H. parasuis strains used in this work and their main characteristics are summarized in Table 1. Seven field strains isolated from domestic pigs and one nasal isolate from wild boar were included in the study. Virulent reference strain Nagasaki was also included as positive control.

Animals

All procedures involving animals were approved by the Ethical and Animal Welfare Committee from the Universitat Autònoma de Barcelona and followed EU normative (Council Directive 86/609/EEC). To avoid antibody interference, snatch-farrowed and colostrum-deprived piglets were used for the infection [START_REF] Blanco | Comparison between Haemophilus parasuis infection in colostrumsdeprived and sow-reared piglets[END_REF]). The animal model was tested in a preliminary experiment with 5 animals and a field strain.

Piglets used in this study came from a farm with a standard health status. Briefly, sows were seropositive against porcine reproductive and respiratory virus (PRRSV) and swine influenza, and seronegative against Aujeszky's disease virus.

Inoculation

Bacterial suspensions for inoculation were made in PBS from overnight cultures of H. parasuis on chocolate agar plates. Suspensions were adjusted to O.D. of 0.2 at 660 nm to give a bacterial concentration of approximately 10 8 CFU/ml. The real number of bacteria in the suspensions was confirmed by serial dilution and plating on chocolate agar (Table 1).

At day 40 of age, groups of 5-8 piglets were intranasally inoculated with 1.5 ml (0.75 ml per nostril) of the corresponding bacterial suspension using a plastic syringe. The groups were balanced according to weight.

Clinical evaluation

Animals were individually examined for the 6-7 days of the trial and clinical signs were recorded daily. Fever, lethargy, and mortality were expected after experimental infection with H. parasuis. Animals showing signs of suffering before the end of the experiment were euthanized by an intravenous sodium pentobarbital overdose (200 mg/kg, Dolethal, Vetoquinol SA). Surviving piglets were euthanized at 6-7 days post-inoculation, with an intravenous overdose of the mentioned product.

Mortality associated to H. parasuis infection was confirmed by post-mortem examination and bacterial isolation from the lesions (see below).

Body weight was measured daily and average daily weight gain for the whole period was calculated. After inoculation, rectal temperature was also measured daily.

Pathological examinations

A c c e p t e d M a n u s c r i p t 7 All pigs were necropsied for evaluation of gross lesions. Special attention was drawn to potential features attributable to H. parasuis infection, such as ascites, hydrothorax, and presence of fibrin in serosal surfaces, including meninges and joints. Since evidence of meningeal damage is poorly visible grossly, samples of brain (cerebellum and pons) of all studied pigs were taken, fixed by immersion in 10% buffered formalin, and routinely processed for histopathology. Severity of microscopic lesions (meningitis) was scored from 0 (no lesion) to 3 (severe meningitis).

H. parasuis detection

Duplicated swabs for bacterial isolation and DNA extraction were collected at necropsy from nose, thoracic, pericardial and peritoneal cavities, joints and meninges. Samples from pleural, pericardial, peritoneum or joint fluids were taken when fluid accumulation was found. Additionally, when possible, blood and cerebrospinal fluid were also processed for bacterial isolation. H. parasuis recovery was semi-quantified by assigning a score of 3 to samples with confluent growth, 2 to samples yielding isolated colonies (down to 20 colonies), 1 to samples yielding 1 to 19 colonies and 0 to samples yielding no bacterial growth.

Samples for bacterial isolation were processed within 2 h after collection.

Bacterial isolation was performed by plating the swabs on chocolate agar and incubating at 37 o C with 5% CO 2 .

Samples for DNA extraction and subsequent H. parasuis-specific PCR [START_REF] Oliveira | Development of a PCR test to diagnose Haemophilus parasuis infections[END_REF] were stored at -20 o C until used. DNA from selected swabs was H. parasuis recovered from the different animals was processed for ERIC-PCR analysis [START_REF] Oliveira | Characterization of the diversity of Haemophilus parasuis field isolates by use of serotyping and genotyping[END_REF]Olvera et al., 2006a) to confirm recovery of the corresponding inoculated strain.

Typing of H. parasuis by serotyping and multilocus sequence typing (MLST)

Serotyping determination was performed by indirect hemagglutination at the Department of Sanidad Animal of the Veterinary School at the University of Leon (Spain) following a previously published protocol (Del Rio et al., 2003).

MLST analysis of the strains included in this study was already published or performed as previously described (Olvera et al., 2006b). We also deduced in silico the alleles of the two H. parasuis genomes available in the nucleotide database of NCBI (Genbank accession numbers NC_011852 and NZ_ABKM00000000). Results were analyzed by BURST and unweighted pair group method with arithmetic mean (UPGMA) using START2 software [START_REF] Jolley | Sequence type analysis and recombinational tests (START)[END_REF]. Clusters were established by the analysis of the clinical data rather than setting an arbitrary threshold.

Statistical analysis

Experimental groups were compared with ANOVA followed by Tukey-Kramer post hoc test for multiple comparisons of unpaired observations (average daily weight gain and rectal temperature) or using Student´s T test (recovery of H. parasuis at necropsy). The significance level was established at 0.05, unless

Results

Preliminary study: reproduction of disease

Initially, we performed a preliminary trial to test the animal model (snatchfarrowed and colostrum-deprived piglets) with H. parasuis field strains. In this first trial, we used 5 piglets to intranasally inoculate a bacterial suspension of the systemic isolate H. parasuis 264/99 (7.5 x 10 8 CFU/animal). Two days after inoculation, 3 animals were euthanized because they showed severe clinical signs (prostration, with swollen joints, and respiratory distress). At necropsy, animal 1 had catarrhal-purulent bronchopneumonia, animal 2 had catarrhal-purulent bronchopneumonia and fibrinous polyserositis and animal 3 had fibrinous pericarditis and polyarthritis. H. parasuis was recovered in pure culture from the lesions of all 3 animals. The remaining 2 pigs survived the challenge and were sacrificed at day 3 post-inoculation, although they did not show clinical signs.

One of these animals did not show lesions at necropsy and no H. parasuis was recovered from the samples taken from it. From the second animal, H. parasuis was isolated in low quantity from thorax and joints, although no macroscopic lesions were observed.

Thus, we confirmed that we could reproduce the disease by intranasal inoculation with a field strain using snatch-farrowed, colostrum-deprived piglets.

A c c e p t e d M a n u s c r i p t 10

Animal infection with H. parasuis field strains from domestic pigs

Clinical signs and pathological findings

In the infections, the most prominent result was that none of the field strains was able to produce the hyperacute outcome that was produced by the Nagasaki strain. This outcome could be explained by the slightly higher inoculum used for this strain or by its higher virulence. Table 2 shows the mortality after inoculation of the different strains. Animals inoculated with strain Nagasaki died in 24h with signs of septic shock. Strains PV1-12 and IT29205 produced severe disease in the animals with high mortality, while strains 9904108, CA38-4 and 2725 generated no mortality in the piglets. Strain 373/03A caused the death of one of the 6 animals infected.

These general observations occurred concomitantly with other clinical findings, such as increased rectal temperature (Table 3) and reduced daily weight gain (Fig. 1) in the affected animals. Infection by strains Nagasaki, IT29205 and PV1-12, which produced severe disease, produced a clear reduction in daily weight gain of the piglets (Fig. 1). Following infection, elevated temperature (≥ 41ºC) was a good predictor of the severity of disease and death of individual animals.

Besides, the severity of clinical signs correlated with the gross lesions observed in the animals at necropsy (Table 4). Interestingly, 3 of the 5 animals infected with the Nagasaki strain showed lesions characteristic of Glässer's disease (fibrinous serositis), although they died within 24h after inoculation. All the animals infected with IT29205 or PV1-12 also showed lesions of Glässer's disease. In the surviving PV1-12-infected piglet, lesions were mild. Animals infected with A c c e p t e d M a n u s c r i p t 11 994108 and 2725 showed no or very mild lesions. Strain CA38-4 only produced lesions (arthritis) in 3 of the 7 inoculated animals and strain 373/03A produced severe lesions of fibrinous polyserositis (pleuritis, pericarditis and arthritis) in 1 of the 6 inoculated animals and arthritis in an additional animal. Histopathologically, 2 pigs inoculated with the IT29205 strain had severe fibrino-purulent meningitis; two pigs inoculated with strain PV1-12 and one pig that received the Nagasaki strain showed very mild meningitis with few inflammatory cells. No microscopic brain lesions were observed in the rest of the pigs inoculated with the abovementioned or other strains.

Recovery of H. parasuis from the inoculated animals

Recovery of H. parasuis from the lesions of inoculated pigs with the different strains is presented in Fig. 2. Animals showing severe lesions yielded higher quantity of H. parasuis from their lesions than animal with mild lesions. Thus, bacterial recovery from lesions was higher (Student's T test, P<0.01) in animals infected with strains Nagasaki, PV1-12 and IT29205 than with the rest of strains.

Taking together the data from all groups, the organ that yielded more positive samples was thorax, followed closely by LCR, joints, blood and abdomen.

Pericardium and meninx produced the lowest number of positive samples.

Recovery of H. parasuis from the nose of diseased animals was faint, while it was recovered in high quantities from the nose of animals that remained healthy during the trial. This observation was sustained even with animals inoculated with the same strain but producing different clinical outcomes. As an example, strain 373/03A produced disease in 1 piglet and H. parasuis recovery from the nose of A c c e p t e d M a n u s c r i p t 12 this animal was not possible (although it was detected by specific PCR), while it was abundant from the nose of pigs inoculated with the same strain that remained healthy. Similar results were obtained with strain PV1-12. An exception to this observation was the lack of recovery of strain 2725, which was not detected in any of the inoculated pigs at the end of the trial by bacterial culture or PCR.

By ERIC-PCR, it was confirmed that the H. parasuis recovered from the pigs were effectively the same strain that we inoculated in each animal (data not shown).

Relationship between the severity of disease and the serovar of the inoculated strain

We did not see a direct correlation between the serovar and the virulence of all the strains.

As expected, strain Nagasaki, which is the reference strain from the high virulent serovar 5, produced a hypervirulent outcome in the piglets, confirming previous reports with strains from serovar 5 [START_REF] Kielstein | Designation of 15 serovars of Haemophilus parasuis on the basis of immunodiffusion using heat-stable antigen extracts[END_REF][START_REF] Nielsen | Pathogenicity and immunity studies of Haemophilus parasuis serotypes[END_REF][START_REF] Amano | Pathologic observations of pigs intranasally inoculated with serovar 1, 4 and 5 of Haemophilus parasuis using immunoperoxidase method[END_REF][START_REF] Amano | Pathogenicity of Haemophilus parasuis serovars 4 and 5 in contact-exposed pigs[END_REF][START_REF] De La Fuente | Blood cellular immune response in pigs immunized and challenged with Haemophilus parasuis[END_REF]. Since Nagasaki was the only strain from serovar 5 included in our inoculations, this can explain the higher virulence observed with this strain. We also found agreement with the putative virulence of strains 264/99, IT29205 and PV1-12. These three strains were originally isolated from clinical lesions, belonged respectively to virulent serovars 10, 4 and 15, and were able to reproduce Glässer's disease in our animal model. Conversely, strains 2725 and 9904108, which belonged also to virulent serovars 10 and 4, respectively, did not produce disease. Thus, strains A c c e p t e d M a n u s c r i p t 13 with the same serovar showed different degree of virulence. In addition, strain CA38-4, from virulent serovar 12, did not induce severe disease. Finally, strain 373/03A, which belonged to the non-virulent serovar 7, produced severe disease in 1 piglet.

Relationship between the severity of disease and the classification of the strains by MLST

A total of 204 sequence types (ST) were defined by MLST of 260 strains and, using relaxed BURST criteria (strains sharing 5 identical loci were assigned to the same group), they were assembled in 33 groups, while 102 isolates remained as singletons. Searching for more distant relationships by UPGMA, 3 main clusters were defined as before (supplementary figure). Strains 264/99, IT29205, CA38-4, 373/03A, 2725 and Nagasaki were included in cluster A, which was associated to Glässer's disease production and was constituted mainly by isolates from systemic lesions. Accordingly, strains 264/99, IT29205, 373/03A and Nagasaki were all able to produce disease in the animal model, but the severity of disease differed among strains. Moreover, strains 2725 and CA38-4, from the same virulent cluster, did not produce severe disease. On the other hand, cluster B contained half of the strains from Glässer's disease or pneumonia cases, but it did not show a clear link with virulence. Strain PV1-12 was included in this cluster B and was able to produce disease. Finally, cluster C was composed of strains isolated from the nose of healthy animals. Strain 9904108 was included in this cluster C and, in agreement, it did not produce disease. Thus, the correlation between the MLST classification and the reproduction of disease was not complete.

A c c e p t e d M a n u s c r i p t 14

Animal infection with a H. parasuis strain from wild boar

Noteworthy, strain WB21-4, which was isolated from the nose of a wild boar, was able to produce disease in the animal model used. Disease caused by this strain was found only in 1 piglet, which died from the infection and showed fibrinous multifocal pleuritis and slight ascites (approximately 10 ml) at necropsy (Fig. 1, Table 2, 3 and4). This animal had also mild meningitis, while the rest of the pigs showed no gross or microscopic brain lesions. H. parasuis WB21-4 was isolated in high quantities from thoracic, pericardial and abdominal cavities, as well as from brain, joints and cerebrospinal fluid from this animal (Fig. 2). The quantity of inoculated strain isolated from the nose was very faint in this animal, while it was extremely high (scores of 3) in the animals that remained healthy after inoculation with the same strain.

Strain WB21-4 was classified by MLST in the nasal cluster C, but it was able to produce disease in 1 animal. Serotyping result was more consistent with the clinico-pathological outcome in this strain, since it was classified in the moderately virulent serovar 2.

Discussion

We confirmed that snatch-farrowed colostrum-deprived piglets can be used for the reproduction of Glasser's disease by intranasal inoculation of field strains of H. parasuis. Reproduction of disease was strain-dependent and severity of clinical signs and lesions correlated with the quantity of H. parasuis recovered from the A c c e p t e d M a n u s c r i p t lesions of sick animals. In fact, we found a good correlation between the severity of the lesions and the quantity of H. parasuis recovered from them, independently of the organ affected. Our results indicate that the best sampling site for H. parasuis diagnosis is not specific of serovar, as suggested by others [START_REF] Turni | Comparison of sampling sites and detection methods for Haemophilus parasuis[END_REF], but any organ affected by the infection where lesions are observed.

Although we observed a good agreement between the genetic classification by MLST of Nagasaki, 264/99, IT29205, PV1-12 and 9904108 and the virulence of these strains in the animal model, this was not the case for the other strains.

Besides, we found that serovar was not a good predictor of the virulence of the field strains. Actually, the relationship between serovar and virulence in H. parasuis is not well established, since the virulence of some serovars was determined using only the reference strain of each serovar [START_REF] Kielstein | Designation of 15 serovars of Haemophilus parasuis on the basis of immunodiffusion using heat-stable antigen extracts[END_REF][START_REF] Rapp-Gabrielson | Haemophilus parasuis, 9 Edition[END_REF]. From our results and those of other authors [START_REF] Nielsen | Pathogenicity and immunity studies of Haemophilus parasuis serotypes[END_REF][START_REF] Amano | Pathologic observations of pigs intranasally inoculated with serovar 1, 4 and 5 of Haemophilus parasuis using immunoperoxidase method[END_REF][START_REF] Takahashi | A cross-protection experiment in pigs vaccinated with Haemophilus parasuis serovars 2 and 5 bacterins, and evaluation of a bivalent vaccine under laboratory and field conditions[END_REF][START_REF] Bak | Protection of vaccinated pigs against experimental infections with homologous and heterologous Haemophilus parasuis[END_REF], it is clear that serovar does not determine the virulence and additional factors are probably responsible for virulence in H. parasuis. In agreement, Bouchet et al. [START_REF] Bouchet | Interactions of Haemophilus parasuis and its LOS with Porcine Brain Microvascular Endothelial Cells[END_REF][START_REF] Bouchet | Studies on the interactions of Haemophilus parasuis with porcine epithelial tracheal cells: limited role of LOS in apoptosis and pro-inflammatory cytokine release[END_REF] found only a minor role of LOS (one of the main antigen that determines the serovar in H. parasuis) in invasion or release of cytokines from endothelial and epithelial cells. Although several studies have tried to identify virulence factors by different methods [START_REF] Hill | A search for virulence genes of Haemophilus parasuis using differential display RT-PCR[END_REF][START_REF] Melnikow | Microarray analysis of Haemophilus parasuis gene expression under in vitro growth conditions mimicking the in vivo environment[END_REF][START_REF] Metcalf | Differential expression of Haemophilus parasuis genes in response to iron restriction and cerebrospinal fluid[END_REF][START_REF] Bouchet | Interactions of Haemophilus parasuis and its LOS with Porcine Brain Microvascular Endothelial Cells[END_REF][START_REF] Jin | Identification of gene transcribed by Haemophilus parasuis in necrotic porcine lung through the selective capture of transcribed sequences (SCOTS)[END_REF][START_REF] Sack | Identification of novel potential virulence-associated factors in Haemophilus parasuis[END_REF], virulence factors of H. parasuis are Besides, other aspects, such as the number of in vitro passages of the strains, could affect the virulence status of the strains [START_REF] Olvera | Differences in phagocytosis susceptibility in Haemophilus parasuis strains[END_REF] and, therefore, of the inoculum used for the infections. Thus, strains with the proper genetic potential for full virulence could lose part of the phenotypic characteristics and appear in the animal model as poorly virulent. It is always recommended to use strains with few in vitro passages when studying virulence-related properties. In this study, no information on the number of in vitro passages of strains 264/99, 9904108, IT29205 and 2725 was available, and this could have affected the results of the infection. To emphasize the importance of the inoculum, it is noteworthy that reduction of the Nagasaki inoculum to 7.0 x 10 5 CFU per animal produced no clinical signs or lesions in the piglets (data not shown).

Interestingly, it seemed that the strains that proceeded to invade were not maintained well in the nasal cavities of the piglets. This suggests changes in the bacteria from a "colonizing state" to an "invasive state", which could be modulated by the ability of each animal to control the infection. This phenomenon deserves deeper study since it could have an impact, not only in the basic understanding of the pathogenesis of H. parasuis, but also in the control of the disease.

Finally, Glässer's disease has never been described in wild boar, but a strain isolated from the nose of wild boars was able to reproduce characteristic lesions in A c c e p t e d M a n u s c r i p t one domestic pig. This result indicates the existence of virulent strains in wild boar, which could produce disease under the appropriate conditions (such as intensive farming and early weaning). The possibility of transmission of H. parasuis from wild boar to domestic pigs must be, therefore, taken into account.

In conclusion, snatch-farrowed colostrum-deprived piglets can be used to reproduce Glässer's disease with field strains of H. parasuis by intranasal inoculation. The severity of disease correlated with high mortality, severe lesions and recovery of high quantities of H. parasuis from the lesions. The virulence of the strains in the animal model did not show a total correlation with their serovar or their classification by MLST. Thus, further studies will be needed to find a clear virulence marker, which will eliminate the need of the animal model for testing the virulence of H. parasuis strains. b This strain was isolated from a wild boar. A c c e p t e d M a n u s c r i p t (18,26,19,20,18,1,5) SC19-1 26,19,20,18,1,5) SC15-2 26,19,50,18,1,5) SC20-3 10,19,20,30,1,5) 04-18412 26,19,37,1,1,5) 04-36583 26,19,38,18,1,1) NL0409 16,19,47,27,1,5) GN-256 8,19,20,27,1,5) P2418 34,19,10,1,1,21) AZ1-1 41,19,23,27,1,1) SZ2005-2096 56,19,40,44,1,21) NL5/10-I ST-176 (21,54,19,40,10,1,32) 7211027-2 ST-94 (23,16,19,1,18,1,19) 9904791 16,19,1,15,1,6) 4590 16,6,1,9,1,12) PC3-2P 16,19,20,1,7,1) 06-16188 16,19,20,1,7,1) VC7-1 16,19,20,1,12,1) IT13524-1 16,19,16,1,1,1) HS315-4S 16,19,20,18,13,1) HS315-2S 16,19,20,18,13,1) AZ11-5 16,14,15,15,2,1) 37 16,14,15,15,2,1) CT-175-L 16,14,34,1,13,1) BA60/02 16,4,51,1,2,5) AG8-60-3N 16,5,34,1,2,5) 2620 16,19,23,1,7,5) PT2-3A 27,34,20,1,4,5) PT1-5P 27,34,20,1,4,5) FL3-1 27,19,21,1,4,5) AG36-90-1N 20,1,34,1,1,5) CA36-2 27,4,20,30,1,1) CA34-1 27,4,20,30,1,1) N67-1 25,13,20,1,1,5) 112/02 25,13,20,1,1,5) CA32-1 25,6,20,1,1,5) VC6-2 25,6,20,1,10,5) VC1-3 25,6,20,1,10,5) AG9-60-6N 25,6,25,1,1,5) 19/04 25,6,19,1,1,25,6,19,17,1,25,6,19,17,1,5) 46080 25,6,16,4,12,5) 174 6,6,7,6,1,5) SZ2006-0336 40,8,7,31,12,5) N459/05-1 40,8,20,31,12,5) VB4-2 25,9,13,1,2,1) VB4-1 25,9,13,1,2,1) VS10-7 25,9,13,1,2,1) PO127 33,9,20,1,2,1) SZ2004-2204 55,9,13,1,10,1) SC11-4 ST-106 (29,37,3,13,1,1,1) 23/04 (F8) 12,9,13,1,1,1) VS10-3 48,9,15,1,8,1) 232/04 9,9,39,1,1,5) 05-11621 9,9,45,1,1,1) SZ2005-2724 43,9,1,1,1,6) P555/03 14,12,15,1,1,1) 61/03 9,9,1,18,1,1) SZ2003-4928 2,9,1,18,10,1) IT70407-3 26,9,1,18,10,6) 05-100983 33,9,1,33,7,1) 233/03 ST-7 (2,2,1,2,2,1,1,1,1,1,1,1234567891011122,1,20,1,2,1) 3023 ST-85 (21,2,1,20,1,5,1) 4857 ST-67 (15,2,1,1,16,5,1) PO129 57,1,20,18,15,1) 06/06 53,9,13,4,5,1) SW124 9,9,11,10,5,1) VC6-1 52,14,13,39,5,1) SZ2005-2599 50,33,7,36,5,1) RU15-6P 9,16,13,4,14,1) RU15-1P 9,16,13,4,14,1) RU15-5P 9,16,13,4,14,5) 4959 27,8,22,9,1,1) 2784 27,8,31,9,1,1) 06-22132 40,8,20,9,1,1) H465 8,8,10,9,4,1) 7710 24,8,15,1,1,1) 2757 24,8,20,1,4,1) AG34-60-1N 47,9,16,18,1,1) 05-85710 47,9,24,9,1,21) 05-95971 46,8,24,9,1,21) SZ2005-2821 45,8,24,9,1,21) 05-96327 4,32,24,9,1,31) ND19-4 35,10,13,9,1,22) SW140 ST-30 (5,5,5,6,5,1,1) AG32-60-2N 26,9,16,18 (16,21,13,17,12,1,9) SC12-5 21,13,17,12,1,9) SC12-1 21,13,17,12,1,9) SC11-3 21,13,17,12,1,9) CC12-1 21,13,17,12,1,11) SC14-1 21,13,16,12,1,9) 03-103368 3,19,24,1,2,24) 03-102143 3,19,24,1,2,24) 03-100484 3,19,24,1,2,24) 03-100365 3,19,24,1,2,24) 05-83471 3,19,24,1,2,24) 06-10955 4,2,43,1,2,24) 05-82754 28,19,46,1,2,6) GN-257 23,19,20,1,2,11) 228/04 23,17,13,1,2,11) IT85183-1 51,29,18,1,2,29) 34/03 3,11,10,13,2,8) P462/03 3,21,18,21,2,14) P015/96 3,18,18,1,6,4) AZ1-5 3,2,35,18,1,4) 04-26867 3,2,10,29,1,4) 5D-84-15995 ST-8 (3,3,2,3,1,1,2) 05-5808 28,4,24,19,1,24) 2725 28,20,24,19,2,12) SZ2005-2745 28,4,50,19,2,26) 04-100691 28,4,10,19,2,1) SN10-1 28,28,23,42,2,24) IT101517-1 28,28,23,19,1,28) 04-34220 28,9,5,37,1,24) SH0165 60,4,10,47,2,35

  at the moment of the delivery, immediately dried and umbilical cords were clamped, cut and disinfected with an iodine solution.Piglets were housed in the biosecurity level 3 animal facilities at the Centre de Recerca en Sanitat Animal (CReSA). Temperature was maintained at 28-29ºC from day 0 to 30 and at 24-25ºC from day 30 until the end of the trial. From 8 am to 8 pm, boxes were illuminated, while from 8 pm to 8 am, they were maintained in darkness.Piglets were fed the milk substitutive Patavie Porc (Oriane-Celtilait) supplemented with antibiotics (see below) ad libitum during the first 2 days.Afterwards, animals received Startrite 100 (SCA Ibérica S.A.) mixed with the milk or dry after 10-15 days of age.It was decided to administer antibiotics prophylactically to the piglets in order to reduce the likelihood of appearance of bacterial disease in such a susceptible pig population. Briefly, piglets received 205.000 UI of colistin (1 gr of colimicine®, Laboratios SP Veterinaria, in 1.5 L of milk) during the first week and 1.7 mg of enrofloxacin (Baytril solution oral 0.5%, Bayer Animal Health) per kg body weight/day during the first two weeks, through the milk and by oral bolus administration, respectively. After this period of prophylactic antibiotic treatment, only piglets showing signs of disease (mainly diarrhea) were treated with cephalosporin (Ceftiofur®, Pfizer Animal Health) or amoxicillin (Penimox® Bayer Animal Health) depending on the bacteriological findings and following each summary of product characteristics. In any case, antibiotic treatments were stopped at least 2 weeks before experimental infection.

  Nucleospin® blood kit (Macherey-Nagel) following manufacturer's instructions.

  Analyses were carried out with the NCSS 2004 and PASS 2005 (Kavysville, Utah, USA).

  . Further studies are needed to identify essential virulence factors that will allow a clear differentiation between virulent and nonvirulent strains of H. parasuis.

  authors of this paper has a financial or personal relationship with people or organisations that could inappropriately influence or bias the content of this study.

Fig. 1 .

 1 Figures legends

Fig. 2 .

 2 Fig. 2. Semiquantification of the recovery of H. parasuis from different internal

  Figure1

  Figure 1

Table 1 .

 1 Main characteristics of the Haemophilus parasuis strains used in this study and doses used to inoculate the animals.

	Strain	Serovar	Organ of	Country of	Dose/animal
			isolation	isolation
	Nagasaki a	5	Meninges	Japan	1.0 x 10 9
	264/99	10	Joint	Spain	7.5 x 10 8
	PV1-12	15	Thorax	Spain	3.8 x 10 8
	9904108	4	Unknown lesion	Denmark	3.5 x 10 8
	IT29205	4	Unknown lesion	Italy	2.0 x 10 8
	CA38-4	12	Nasal	Spain	1.3 x 10 8
	373/03A	7	Abdomen	Spain	3.0 x 10 8
	2725	10	Joint	Germany	4.2 x 10 8
	WB21-4 b	2	Nasal	Spain	1.0 x 10 8
	a Virulent reference strain.

Table 1 A

 1

	M a n u s c r i p t
	c c e p t e d

Table 2 .

 2 Mortality caused by intranasal inoculation of different strains of H. parasuis in snatch-farrowed colostrum-deprived piglets. Animals showing no clinical signs were euthanized at the end of the experiment. These are not included in the table.

		Number of
		animals	Number of clinically	Days after challenge until
	Strain	challenged	affected animals	euthanasia a
	Nagasaki	5	5	1, 1, 1, 1, 1
	PV1-12	6	5	2, 3, 3, 3, 3
	9904108	6	0	-
	IT29205	6	6	3, 3, 3, 4, 4, 5
	CA38-4	7	0	-
	373/03A	6	1	5
	2725	6	0	-
	WB21-4	8	1	4
	a

Table 2 A

 2

	M a n u s c r i p t
	c c e p t e d

Table 2 .

 2 Comparison of rectal temperatures (mean±SD) in piglets after intranasal inoculation with different strains of H. parasuis. Rectal temperatures were compared by the Tukey-Kramer Multiple-Comparison Test at the different days. Values with different superscript in a column are significatively different (P< 0.05).

	Average and SD of rectal temperature at

a Table

3

Table 3 .

 3 Lesions found in the animals at necropsy. Results are indicated as the number of animals with the specific lesion out of the total animals in each group.

						Lesions
	Strain	Day of death (mean ±SD)	Animals with no lesions	Fibrinous pleuritis and/or pericarditis	CPBN a	Hydro-pericardium	Fibrinous peritonitis	Serous-arthritis fibrinous	Others
									Cianosis (2/5),
									pulmonar,
	Nagasaki	1±0.0	-	1/5	1/5	-	1/5	2/5	intestinal or
									gall bladder
									oedema (4/5)
	PV1-12	3±2.0	-	3/6	2/6	-	2/6	2/6	Pulmonar oedema (1/5)
	9904108	6 b ±0.0	4/6	1/6 c	-	1/6 c	-	-	-
									Fibrinous
	IT29205	3±0.9	-	3/6	-	4/6	4/6	5/6	meningitis
									(2/6)
	CA38-4	7±0.0	4/7	-	-	-	-	3/7 c	-
	373/03A	6.5±1. 2	4/6	1/6	-	1/6	-	2/6	-
	2725	7±0.0	2/6	1/6 d	-	2/6 d	-	2/6 d	-
	WB21-4	6.8±0. 7	2/8	1/8	-	5/8 d	-	-	-

a Catarrhal-purulent bronchopneumonia b This trial was terminated at day 6 post-inoculation c Very mild lesions d Very mild lesions in two of them

Table 4

 4

Acknowledgements

We acknowledge Nuria Galofré and all the staff from the BSL3 animal facility of CReSA, especially Valentí Rosell and Juan Carlos Prieto, for their work with the animals and other technical support. This work was financed by Fort Dodge Animal Health and grants AGL2004-07349 and AGL2007-60432 from the Ministerio de Educación y Ciencia of Spain.


I M G A Santman-Berends

C J M Bartels

G Van Schaik

J A Stegeman

P Vellema

The increase in seroprevalence of bluetongue virus (BTV) serotype 8 infections and associated risk factors in Dutch dairy herds, in 2007

Keywords: bluetongue virus serotype 8, cattle, prevalence, risk factors, sentinel herds

Bluetongue virus serotype 8 (BTV-8) emerged in the Netherlands in August 2006 for the first time. In the winter of 2006/2007, during the transmission free period, the government decided to establish a sentinel network to monitor the re-emergence of BTV-8 in 2007. Between June and December 2007, a sentinel network of 275 dairy herds with 8,901 A c c e p t e d M a n u s c r i p t factors remained in the final model. Herds in the central and southern region of the

Netherlands had a higher monthly increase in seroprevalence (6.4% (95% CI: 3.1-9.9) and (10.1% (95% CI: 6.2-14.3)), respectively compared to herds in the northern region.

Furthermore, there was a strong association with grazing. The monthly increase in seroprevalence in cattle pastured a few hours per day or throughout the day was 5.6% (95% CI: 1.4-10.2) to 11.4% (95% CI: 6.0-17.3) higher, relative to that for cattle kept indoors. For cattle that grazed outdoors throughout the day and the night, the monthly increase in seroprevalence was 13.6% (95% CI: 7.2-20.8). In addition, an association was found between the monthly increase in seroprevalence and some factors relating to stable design. Keeping the stable doors closed during the day was linked to a higher seroprevalence rate compared to that in stables with the door left open (3.6% (95 CI: 0.3-7.1). Furthermore, a horizontal ventilation opening (>30 cm) along the walls of the stable, and with a wind break curtain, appeared to offer some protection (-3.0% per month (95% CI: -6.0-0.2) as compared to stables that had no or, only a small, ventilation opening (<30 cm). By the second half of 2007, bluetongue had spread over throughout the Netherlands. Our study indicated that there were some management factors that may help limit exposure to BTV-8 and its consequences.

seronegative cows at start, was in place for BTV-8 testing in milk samples. Besides estimates of the monthly BTV-8 within-herd prevalence per region (south, central and north), this sentinel was used to determine BTV-8 associated risk factors. Information on management and housing practices that were hypothesized to be related to the increase in BTV-8 prevalence (risk factors) were used. Complete information on BTV-8 testing and management was obtained for 234 herds. At herd level, the increase in seroprevalence was defined as the total increase in seroprevalence among sentinel cows per herd during the sampling period (in months) divided by the number of sampling months in which the spread of BTV-8 occurred within the particular compartment in which the herd was located. This parameter was used as dependent variable in the linear regression analysis. The final model revealed four risk

Introduction

In August 2006, bluetongue virus serotype 8 (BTV-8) was diagnosed in the Netherlands for the first time (van Wuijkhuise et al., 2006). A few days later, Belgium and Germany also reported cases of BTV-8. This discovery was remarkable because, prior to its unexpected A c c e p t e d M a n u s c r i p t appearance in northern Europe, BTV-8 was known only from Africa, Central America and parts of south-east Asia [START_REF] Mo | Bluetongue virus isolations from vectors and ruminants in Central America and the Caribbean[END_REF][START_REF] Daniels | Regional overview of bluetongue viruses in South-East Asia: viruses, vectors and surveillance[END_REF]Gerdes et al., 2004).

In December 2006, the assumed BTV-8 transmission free period commenced. By this point, outbreaks of BTV-8 had been reported from five European countries: Belgium (695), France (7), Germany (952), Luxemburg (8) and the Netherlands with 460 outbreaks (260 in sheep flocks and 200 in cattle herds) [START_REF] Efsa | Scientific Report of the scientific Panel on Animal Health and Welfare on request from the Commission (EFSA-Q-2006-311) and EFSA Self mandate (EFSA-Q-2007-063) on bluetongue[END_REF].

In the winter of 2006/2007, the European Union enforced a monitoring and surveillance program in all affected countries to detect new infections and to monitor disease status, in the hope of regaining its BTV-8 free status within the shorter term. The Dutch government decided to conduct a program using a network of sentinel dairy herds.

The monthly test results from the sentinel network made it possible to pinpoint the moment of introduction of BTV-8 and to predict the rate at which it would spread. Furthermore, by analyzing, the diagnostic results from the ELISA in milk in combination with the management and housing practices on the sentinel farms, risk factors for BTV-8 at herd level could be determined.

In this study, the spread of BTV-8 across the Netherlands, and its monthly increase in seroprevalence in dairy herds is quantified based on results obtained from the 2007 sentinel network program which has enabled us to identify risk factors down to herd level.

Material and Methods

Study population

A c c e p t e d M a n u s c r i p t

The Netherlands is divided into 20 compartments based on geographic boundaries as proposed in Commission Decision 2005/393/EC (Figure 1). Compartment 1 was divided in two sub-compartments (1a and 1b), because of its large size.

For the sentinel network, a sample size of 150 sentinel cows per compartment was needed to achieve 95% confidence and a precision of 2% (Dutch Ministry of Agriculture, Nature and Food Quality, 2006). It was determined that in each compartment at least 10 randomly selected herds had to be sampled (with at least 15 cows per herd) to obtain the required sample size. Herds were not necessarily completely BTV-8 seronegative, but cows designated for the sentinel program had to be BTV-8 seronegative at moment of selection in May 2007.

Dairy herds included in the program had to have at least 50 cows and had to participate in the dairy herd improvement program of the Cattle Improvement Cooperation (CRV) with test-day intervals monthly.

Thirteen or 14 herds per compartment, with at least 16 BTV-8 seronegative cattle per herd, were selected for sampling.

The 16 BTV-8 seronegative cattle were identified by collecting milk samples taken from 26 lactating cows per selected herd in compartments 1 to 13. In compartments14 to 20, milk samples were taken from all lactating cattle. All the cattle that tested negative were included in the sentinel network. In total, 8,901 initially seronegative cows housed in 275 Dutch dairy herds were selected for the BTV-8 sentinel program in 2007. This method of selection was used because van Schaik et al. (2008) found that seroprevalence rates in compartment 1 to 13 did not exceed 1% between January and June 2007 whereas prevalence rates in compartments 14 to 20 (in the south of the Netherlands) were higher. This selection method increased the likelihood of obtaining at least 16 seronegative cattle per herd for inclusion in the network.

A c c e p t e d M a n u s c r i p t

All cattle that tested negative at first sampling in May 2007 were included in the study. Each month thereafter, and from this selected group, 16 randomly chosen cows were sampled in each herd.

Study period

The first round of monthly testing of sentinel cows was done in June 2007. The BTV-8 epidemic started in the south of the Netherlands and spread to the north. Sampling was halted in September in compartments 10 to 20 and in October in compartments 7 to 9. Because the prevalence of BTV-8 in these compartments was increasing rapidly, rendering further sampling was unnecessary. Initially, the sentinel study would end in October, but at that point a low number of cattle in the northern compartments of the Netherlands had seroconverted and it was decided to follow the herds in these compartments (1-6) up to and including December. Thus, cows located in the south were sampled for four months, those in the central region for four, five or seven months and those in the north for seven months (Figure 1 and2).

For the analyses, the test-results of the sentinel cows in the months in which BTV-8 did not spread on compartment level were excluded because risk-factors could not be determined in case there was no spread of BTV-8. Therefore, observations from sentinel cows located in central or northern compartments in June were excluded and observations from sentinel cows located in compartment 6 in June to August were also excluded.

Data collection and management

The monthly milk samples were tested at the Animal Health Service (GD) for antibodies to BTV-8 using a commercial ELISA (sELISA; ID.VET, Montpellier, France). The result of the A c c e p t e d M a n u s c r i p t ELISA is expressed in a S/P ratio. This ratio quantifies the amount of colouring (extinction) caused by the sample as compared to the amount of colouring (extinction) caused by the standard positive sample (extinction sample/extinction positive control x 100%). When the S/P ratio of the ELISA was >100 the sample was considered BTV-positive; those with an S/P ratio of <100 negative. The diagnostic test used is described in detail by [START_REF] Kramps | Validation of a commercial ELISA for the detection of bluetongue virus (BTV)-specific antibodies in individual milk samples of Dutch dairy cows[END_REF].

Between March and May 2008, among the farmers of the sentinel herds, a short questionnaire was administered by telephone with questions concerning the type of housing and the grazing patterns of their cattle during 2007. All 275 sentinel herd owners were contacted of which 245 (88%) responded. The remaining 30 herds could not be reached by telephone or did not want to cooperate. Answers of the questionnaire were submitted in Net Q [START_REF] Net | Users guide Net Q internet surveys 6.0[END_REF], a program for preparation of questionnaire data. After validation, data from 241 herds remained for analysis. Of these, six herds were only tested once, and in one herd sampling errors were made. These seven herds were excluded from further analysis.

Additional data were obtained on net returm of milk, herd size, and the purchase of cattle in the BTV-8 period (between May and December 2007).

Statistical analysis

Monthly within herd prevalences of the sentinel cows for each sentinel herd were calculated and aggregated at compartmental and regional level. These results were displayed geographically and depict infection levels to BTV-8 in 2007 (Figure 1). Univariate descriptive analyses were performed to obtain means and medians and to compare herd characteristics (i.e. herd size, net return on milk) and the spread of BTV-8 between the regions south, central and north. Median tests (Kruskal-Wallis test: Kruskal and Wallis, 1952) were performed on A c c e p t e d M a n u s c r i p t the parameters that were not normally distributed. A Fisher's Exact test [START_REF] Fisher | On the interpretation of χ 2 from contingency tables, and the calculation of P[END_REF] was used to compare proportions.

For the analysis of the risk factors, for each herd the diagnostic results were aggregated to one outcome variable which was calculated as:

N prev prev MI t t i n 0   Where: MI i =
the mean monthly increase in seroprevalence amongst sentinel cows in each herd (i; i=1 to 234)

Prev tn = the within herd seroprevalence between the sentinel cows in the last month (t n ) in which the herd was sampled Prev t0 = the within herd seroprevalence between the sentinel cows in the first month (t 0 ) in which spread of BTV-8 occurred within the particular compartment in which the herd was located N = the number of months between t 0 and t n

For the risk factor analyses, the outcome variables on herd level, which were based on the diagnostic results, were combined with the results of the questionnaire.

The outcome variable, the monthly increase in seroprevalence of BTV-8 was not normally distributed and a log transformation was used to normalize it. The log monthly increase in First, all variables derived from the questionnaire, and demographic data on the herds, were subjected to univariate analysis. When the P-value was below 0.20, the variable was used in the multivariate model. The multivariate analysis was done using a backward and a forward elimination procedure. After each run, the variable with the highest P-value was excluded from the model until all variables had a P-value <0.05. Confounding was monitored by the change in the coefficient of a variable after removing another variable. If the change of the estimates exceeded 25% or 0.1 when the value of the estimate was between -0.4 and 0.4, the removed variable was considered a potential confounder and was re-entered in the model. In the final model, all possible two-way interactions were tested singly. The residuals of the final model were tested for normality and the r 2 was calculated to measure the proportion of variance explained by the model.

Results

Descriptive results

Of the 275 sentinel herds that initially entered the Dutch sentinel program, 78 herds were located in the south, 114 in the central region and 83 in the north; respectively, 63, 100 and 71 of these herds, i.e. 85.1% overall, remained for final analysis.

Due to a lower dairy herd density, dairy herds in the southern region (2.0%) were significantly more often included in the sentinel study, than herds in the central (1.1%) or northern (0.9%) part of the Netherlands (Fisher's Exact test, P-value<0.001) (Table 1).

A c c e p t e d M a n u s c r i p t

(Table 1)

The monthly increase in whining herd seroprevalence and herd size differed significantly between regions (Kruskal-Wallis P-value=0.001 and P-value=0.02).

The percentage of herds in which all cattle tested negative in the last test round was not significantly different between regions (Kruskal-Wallis, P-value=0.59) (Table 1). However, we found that in 48% of the herds kept indoors all summer, all cattle tested negative in the last test round, as opposed to 14% for herds maintained outdoors (Kruskal-Wallis P-value<0.0001).

Nevertheless, the percentage of herds in which all cattle tested positive, and the average within-herd prevalence in the last test round, did not significantly differ between regions (Kruskal-Wallis, P-value=0.14 and P-value=0.64, respectively).

In the southern (compartment 15 to 20) and central (compartment 6 to 14) region of the Netherlands, the seroprevalence in the sentinel groups started to increase rapidly from August or September on (Figure 1 and 2) while the rapid increase in the northern region (compartment 1 to 5) of the Netherlands did not commence until October.

(Figure 1)

In compartment 6 (central region), the seroprevalence rate started to increase from September on. However, this increase was slower compared to that of other central compartments, where the seroprevalence rates remained at a low level for several months. The increase in seroprevalence between months where highest in September for the central (mean 44.8%; 95% CI: 37.9-51.7) and southern region (mean 48.2%; 95% CI: 38.2-58.2) (Figure 2). This increase in seroprevalence in September was significantly higher than the increase in seroprevalence in the other months (P-value<0.0001 in the central region and P-value<0.0001 in the southern region). For region north the highest increase in seroprevalence was found in October (mean 20.9%; 95% CI: 15.0-26.9) and November (mean 19.5%; 95% CI: 14.5-24.4) (Figure 2). These increases in seroprevalence were significantly higher compared to the other months (P-value<0.0001 in October and P-value<0.0001 in November, respectively).

Multivariate analyses

Nine of the 13 variables in the univariate analyses remained for multivariate analysis (P-value<0.20) (Table 2). The variables that were excluded based on the results of the univariate analyses, were purchase of cattle (P-value=0.37), stable doors open during the night (P-value=0.87), type of grazing management (rotation grazing, restricted grazing, siesta grazing, restricted grazing, grazing multiple weeks in the same field; P-value=0.99), and type of summer feed (maize, grass, both feeds; P-value=0.63).

(Table 2)

In the final multivariate model, the four factors 'region', 'grazing management between the end of June and October', 'keeping stable doors open during the day' and 'horizontal 3).

(Table 3)

In herds in the central (6.4% (95% CI: 3.1-9.9)) and southern (10.1% (95% CI: 6.2-14.3))

parts of the Netherlands, BTV-8 spread more rapidly amongst cattle than in herds located in the north. Furthermore, it appeared that longer grazing hours were associated with a higher monthly increase in seroprevalence of BTV-8. Cattle that grazed outdoors for only a few hours a day (totaling between 1 to 1500 hours in summer and autumn), grazed outside all day (1501 to 2500 hours) or grazed outside day and night (>2500 hours), showed significantly higher monthly increases in seroprevalence of BTV-8 compared to cattle that remained indoors.

Keeping the stable door closed during the day was associated with a higher monthly increase in seroprevalence when compared to keeping the stable door open (3.6% (95% CI: 0.3-7.1).

In addition, herds with horizontal ventilation openings along the side walls of the stable (>30 cm) in combination with a windbreak curtain, tended to a lower monthly increase in seroprevalence, when compared to herds with no or only small horizontal ventilation openings (<30 cm) (-3.0% (95% CI: -6.0-0.2)). However, large horizontal openings along the side walls, and without windbreak curtain, did not reduce the monthly increase in seroprevalence, when compared to herds in stables with no or with only small horizontal openings.

The final model explained 21% of the variation in the monthly increase in seroprevalence.

The variables in the final model were not significantly correlated amongst each other (Spearmann's correlation test). In the model one two-way interaction term was found to be A c c e p t e d M a n u s c r i p t significant: "grazing management" with "stable doors open at daytime". However, this interaction term did not improve the amount of variance explained by the model nor the fit of the model. In addition, the result did not seem biologically relevant and the interaction was not included in the final model. The residuals of the final multivariate model were normally distributed.

Discussion

The sentinel study was originally developed to establish whether the Netherlands could regain its BTV-8 free status in 2007. In July 2007, the first seronegative cattle in the sentinel herds seroconverted. At that point it became clear that BTV-8 had over wintered and re-emerged.

Subsequent to this the sentinel network was used to determine the spread of BTV-8 across the Netherlands.

Herds in different regions were sampled for different periods. This could have caused some bias in our data. However, within-herd prevalences in the south had increased to very high levels in September and further sampling would probably not provide additional information.

At that point, BTV-8 within-herd prevalences were still very low in some central and northern compartments and for this reason it was decided to continue the testing in those compartments. To correct for the differences in sampling period for herds located in different compartments, the average monthly increase of seroprevalence within herds was determined.

The median monthly increase in seroprevalence significantly differed between regions, with the highest increase in the south (18.8%) and the lowest in the north (7.5%). It is likely that south and limited in the central region. Furthermore, these differences in the increase in the seroprevalence could be due to seasonal differences in the spread of BTV-8. In the south, BTV-8 spread in the summer months during which conditions were favourable and with temperatures high, ranging 15 and 25 degrees Celsius. In the north, BTV-8 started to spread from October to December. However, the conditions for the continued spread of BTV-8 deteriorated during these months due to declining temperatures.

Initially, we suspected that there would be a relationship between the purchase of cattle and the introduction of BTV-8 into a given herd. However, the results of the univariate analyses showed that there was no significant association between the purchase of cattle and increase in seroprevalence. To certify that the purchase (and movement) of cattle was not associated to the spread of BTV-8, we compared purchase of cattle (yes/ no) between June and December 2007 in herds that were BTV-8 positive with purchase of cattle between June and December 2007 in herds that had remained BTV-8 negative throughout the study period. Our data indicated no differences in purchase behavior between owners with herds that became BTV-8 positive and owners with herds that remained BTV-8 negative.

In compartment 6 (central region), the seroprevalence started to increase later than in the other central compartments and remained at a low level for a long time (Figure 1 and 2). The herd owners of only six of the 13 sentinel herds in compartment 6 responded to the questionnaire and so were included in our study. Of these six herds, four were kept stabled throughout the entire grazing season. Thus, the lower seroprevalence in this compartment may be linked by the specific management practices or a lower of herd density.

In the sentinel program, 275 sentinel herds were included; of these, 234 were included in the final model. A fixed number of 13 to 14 herds per compartment were selected for the study.

Because the south of the Netherlands has a lower dairy herd density than the north, the south was slightly overrepresented in our study. Moreover, in the north, fewer farmers responded to A c c e p t e d M a n u s c r i p t the questionnaire, perhaps due to lower BTV-8 morbidity and mortality rates and due to its belated arrival in October 2007 [START_REF] Santman-Berends | The use of national rendering data to estimate the mortality attributed to BTV-8 infection in Dutch dairy herds in 2006 and[END_REF]. Although the sentinel herds were not fully representative of the national situation, we believe nevertheless that the range of management practices, barn types, and risk factors involved, are applicable to all dairy herds in the Netherlands.

It was found that more hours of grazing were related to a higher monthly increase in BTV-8 seroprevalence. Herds maintained indoors stayed significantly more often BTV-8 free (48%) than herds maintained outdoors (14%) and therefore the maintenance of cattle indoors may reduce the spread of infection. [START_REF] Meiswinkel | Stabling and the protection of horses from Culicoides bolitinos (Diptera: Ceratopogondiae), a recently identified vector of African horse sickness[END_REF] found that the ratio outdoors vs.

indoors catches of Culicoides differed per subspecies. However, almost all subspecies were captured outside more often than indoors. In addition, [START_REF] Baylis | Evaluation of housing as a means to protect cattle from Culicoides biting midges, the vectors of bluetongue virus[END_REF] trapped Culicoides indoors and outside the stable in the United Kingdom and they also found lower numbers of trapped Culicoides indoors compared to outdoors (6.5 times less). These findings support our results of grazing as a risk factor. However, [START_REF] Baldet | Indoor activity of Culicoides associated with livestock in the bluetongue virus (BTV) affected region of northern France during autumn 2006[END_REF] found that in France certain species of Culicoides were captured indoors as much as outdoors. Based on the fact that a relatively high proportion of the Culicoides trapped indoors were freshly blood fed, they assumed that these had been actively feeding. [START_REF] Meiswinkel | Endophily in Culicoides associated with BTV-infected cattle in the province of Limburg, south-eastern Netherlands[END_REF] obtained similar results in the Netherlands that included captures in which up to 33% of the Culicoides were freshly blood fed, and which likely had fed inside the stable.

Their conclusions, in part, conflict with our results which, based on the significantly lower BTV-8 seroprevalence rates, indicate Culicoides attack rates to be higher outdoors than indoors. It is important to note that two of the potential BTV vectors in the Netherlands, i.e.

C. dewulfi and C. chiopterus, breed exclusively in the fresh dung of cattle lying in the field outdoors; therefore, if all cattle at a dairy are being maintained indoors it will deprive C.

A c c e p t e d M a n u s c r i p t dewulfi and C. chiopterus of their breeding habitat, leading to a decrease in their population levels, which, in turn, may impact on the dissemination of BTV locally.

We found an association between increase in seroprevalence and some factors relating to stable design. A horizontal air opening of more than 30 cm along the walls of the stable, combined with a windbreak curtain, seemed to be protective against BTV-8 infection; furthermore, keeping the stable doors open was associated with a significantly lower increase in seroprevalence compared to that found at stables where the doors were kept closed. Thus, it would appear that herds housed in stables with many air openings ("fresh stables") showed a lower increase in seroprevalence. It is possible that increased air circulation may inhibit

Culicoides, resulting either in a reduced presence and/ or reduced biting frequency in fresh stables. However, stables with a large (>30 cm) horizontal opening but without windbreak curtain were not associated with a significantly lower increase in seroprevalence compared to that in herds maintained in stables with no or small horizontal openings in the walls.

Windbreak curtains may in some way help to reduce entrance by Culicoides into stables, much as mosquito netting would do. Nevertheless, because of the fairly weak association, further research is required to prove causality.

In the second half of 2007, BTV-8 had spread over all regions in the Netherlands. Our study indicates that there are some management practices such as maintaining the herd indoors and characteristics relating to the stable design that may help limit exposure to BTV-8 and thus lead to a lower increase in BTV-8 prevalence.

  as a dependent variable and a general linear model in SAS 9.1 (SAS, 2006) was used to analyze risk factors related to the monthly increase in seroprevalence.

  the walls of the stable', were significantly associated with the monthly increase in seroprevalence of BTV-8 (Table

  the fraction of BTV-8 infected Culicoides in the southern and central region of the Netherlands was higher at the start of the Culicoides active period in 2007 compared to the fraction of infected Culicoides in the north, because BTV-8 had already spread in 2006 in the A c c e p t e d M a n u s c r i p t

  Common symptoms just a little different and in too many herds.Tijdschr. Diergeneesk. 131,[649][650][651][652][653][654]

Figure 1 .

 1 Figure 1. Mean within-herd BTV-8 prevalence in 234 dairy herds in the Netherlands per compartment per month, from July to December 2007. Horizontal lines demarcate the southern, central and northern regions of the Netherlands: the numbering of the compartments is included in the map of July.

Figure 2 .

 2 Figure 2. Mean within-herd prevalence per month of BTV-8 in the Netherlands in 2007: north (compartments 1-5: sampled June-December), central (shown by use of three separate lines: compartment 6: sampled June-December; compartment 7-9: sampled June-October, and compartments 10-14: sampled June-September) and in the south (compartments 15-20: sampled June-December).

Figure 1 .

 1 Figure 1. Mean within-herd BTV-8 prevalence in 234 dairy herds in the Netherlands per

Figure 1 .

 1 Figure 1. Mean within-herd BTV-8 prevalence in 234 dairy herds in the Netherlands per compartment per month, from July to December 2007. Horizontal lines demarcate the southern, central and northern regions of the Netherlands: the numbering of the compartments is included in the map of July.

Figure 2 .

 2 Figure 2. Mean within-herd prevalence per month of BTV-8 in the Netherlands in 2007: north (compartments 1-5: sampled June-December), central (shown by use of three separate lines: compartment 6: sampled June-December; compartment 7-9: sampled June-October, and compartments 10-14: sampled June-September) and in the south (compartments 15-20: sampled June-December).

a

  Table3. Variables in the final multivariate general linear model on the effect on the monthly increase in seroprevalence between June and December 2007 in the Netherlands and their categories, estimates (transformed from log transformation to real estimates), 95% confidence intervals and significance (P-value) (n=234). Number of hours in the field during the pasturing period were calculated as the number of hours per day times the number of days the cattle were in the field.

Table 1 .

 1 Median and interquartile range (25 th and 75 th percentile) of the dairy herds included in the Dutch BTV-8 sentinel study in 2007 (n=234).

	South	Central	North
	(71 herds)	(100 herds)	(63 herds)
	Median	Median	Median
	(25 th -75 th	(25 th -75 th	(25 th -75 th
	percentile)	percentile)	percentile)

a significantly different from region north b the month in which the cows were sampled for the last time

Table 2 .

 2 Univariate results of all farm management practices and housing variables with a P-value<0.20 in 234 Dutch dairy herds that participated in a testing program to estimate the monthly increase in seroprevalence of BTV-8 between June and September (compartments The total number of hours was calculated as the number of hours per day times the number of days the cattle were in the field.

	16-20), June and October (compartments 7-15) or June and December (compartments 1-6).
	Variable	Category	Frequency Mean monthly	P-value
				increase in	(univariate)
				seroprevalence
				(%)
	Region	North (comp. 1-5)	63	10.3	0.001
		Central (comp. 6-14)	100	16.7
		South (comp. 15-20)	71	18.7
	Herd size	10% smallest herds	23	19.0	0.08
		(less than 50 dairy cows)
		40% smaller herds	92	16.9
		(between 50 and 64 dairy
		cows)
		40% larger herds	96	14.9
		(between 64 and 90 dairy
		cows)
		10% largest herds	23	9.6
		(more than 90 dairy cows)
	Cattle were	Yes	207	16.6	0.003
	grazed in 2007	No	27	8.3

a

Acknowledgements

This study was financially supported by the Dutch Ministry of Agriculture, Nature and Food Quality (LNV). Furthermore, we would like to thank the Dutch dairy farmers who cooperated