Transboundary and Emerging Diseases

ORIGINAL ARTICLE

Clinical Sentinel Surveillance of Equine West Nile Fever, Spain C. Saegerman1, A. Alba-Casals2, I. Garc
ıa-Bocanegra3, F. Dal Pozzo1 and G. van Galen4 1

2 3

4

Research Unit of Epidemiology and Risk Analysis applied to veterinary science (UREAR-ULg), Fundamental and Applied Research for Animals & Health (FARAH), Faculty of Veterinary Medicine, University of Liege, Liege, Belgium Centre de Recerca en Sanitat Animal (CReSA), UAB-IRTA, Barcelona, Spain
rdoba-Agrifood Excellence International Campus (ceiA3), Co
rdoba, Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de Co Spain Large Animal Clinic, Internal Medicine and Surgery, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

Keywords: West Nile fever; equine; virus; vector-borne disease; clinical epidemiology; data mining Correspondence: C. Saegerman. Research Unit in Epidemiology and Risk Analysis Applied to Veterinary Sciences (UREAR-ULg), Fundamental and Applied Research for Animals & Health (FARAH), Faculty of Veterinary Medicine, University of Liege, Boulevard de Colonster 20, b^ at. B42, B-4000, Liege, Belgium. Tel.: +3243664579; Fax: +3243664261; E-mail: [email protected] Received for publication December 22, 2013 doi:10.1111/tbed.12243

Summary West Nile fever (WNF) is a viral zoonotic infection caused by a mosquito-borne flavivirus of the Flaviviridae family. According to a comparative study, the passive surveillance of horses by equine veterinarians appeared to be the most costeffective system in the European context of WNF. Clinical data issued from a passive epidemiosurveillance network from September 2010 to December 2011 on horses in Spain were statistically compared and used to develop a predictive diagnostic decision tree, both with the aim to improve the early clinical detection of WNF in horses. Although clinical signs were variable in horses affected by WNF, four clinical signs and the month of occurrence were identified as useful indicators to distinguish between WNF-related and WNF-unrelated cases. The signs that pointed out a presumptive diagnosis of WNF in horses were cranial nerves deficits, limb paralysis, photophobia and nasal discharge. Clinical examination of horses with neurological signs that are not vaccinated against WNV could provide important clues for the early clinical detection of WNF and therefore serve as an alert for possible human viral infections. The study of the clinical pattern of WNF in horses is of importance to enhance awareness and better understanding and to optimize surveillance designs for clinical detection of WNF in horses in advance of epidemic activity affecting humans.

Introduction West Nile fever (WNF) is a worldwide viral zoonotic infection caused by a mosquito-borne flavivirus of the Flaviviridae family (Petersen and Roehrig, 2001; Autorino et al., 2002). Current knowledge suggests that there is a low-level and recurrent circulation of West Nile virus (WNV) in Southern Europe. Sporadic and quite unpredictable human and/or equines cases occur (Chevalier et al., 2011), and all favourable conditions appear to be present in a definite place (migratory route of birds, horse and/or human populations, humid area and presence of competent vectors). While overwintering mechanisms cannot be ruled out (Sotelo et al., 2011), modelling suggests that these © 2014 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

mechanisms are not sufficient to explain the observed European WNF outbreaks (Durand et al., 2010). Regular European outbreaks of WNF in horses and/or humans have been reported in France [outbreaks in the Camargue region in 2000, 2003, 2004 (Murgue et al., 2001; Leblond et al., 2007)], Romania [in 1996 and 2010, and several cases in 1997 and 1998 (Tsai et al., 1998; Cernescu et al., 2000; Rabel et al., 2011)], Italy [in 1998 and 2008–2009 (Cantile et al., 2000; Calistri et al., 2010; Monaco et al., 2011)], Russia [in 1999 and 2010 (Platonov et al., 2001; Rabel et al., 2011)], Hungary [in 2008 and 2010 (Kutasi et al., 2011; Rabel et al., 2011)], several cases since 1997 in the Czech Republic (Rabel et al., 2011), Greece [in 2010 and 2012 (Anonymous, 2010; Rabel et al., 2011; Cnops et al., 1

Clinical Surveillance of Equine West Nile Fever

2013)], Spain [in 2010, 2011, 2012 (Garc
ıa-Bocanegra et al., 2011b; Ministerio de Agricultura, Alimentaci
on y Medio Ambiente, 2012)], and some cases of WNF have been reported in Portugal (Barros et al., 2011). In addition, although in absence of disease, increased titres of antibodies have been encountered from human intravenous plasma preparations in Germany and Austria (Rabel et al., 2011), and seropositive horses have been recently identified in Croatia (Madic et al., 2007; Barbi
c et al., 2012) and Serbia (Lupulovic et al., 2011). According to the international guidelines for surveillance, prevention and control of the West Nile virus (Centers for Disease Control and Prevention, 2013), the objective of the WNV surveillance consists of two distinct but complementary activities. Epidemiological surveillance studies WNV human disease to quantify disease burden and identify seasonal, geographic and demographic patterns of human morbidity and mortality. Environmental surveillance monitors local WNV activity in vectors and non-human vertebrate hosts in advance of epidemic activity affecting humans. Horses as non-human vertebrate hosts are particularly sensitive to WNV, and among clinically affected horses, approximately 10% present neurological disorders compared with 1% of humans (Petersen and Roehrig, 2001; Leblond et al., 2007), rendering its detection in equids highly pertinent in a public health perspective. The incubation period for WNV in horses appears to be between 3 and 15 days (Lecollinet et al., 2012). Clinical signs of WNV infection in horses may include fever, ataxia, depression or anxiety, stupor, behavioural changes, paresis or paralysis of one or several limbs, clinical signs of cranial nerve paralysis, teeth grinding, muscle twitching, fasciculation and tremors, convulsions, colic, and intermittent lameness, or death (American Association of Equine Practitioners, 2005). The case-fatality rate for horses exhibiting clinical signs of WNV infection, including both natural death and destroyed on human ground, is wide from 33% in United States of America (American Association of Equine Practitioners, 2005; Leblond et al., 2007) to 82% in Europe (Leblond et al., 2007). Clinical signs of WNF in horses are difficult to distinguish from those of other infectious neurological diseases (Leblond et al., 2007; Porter et al., 2011). Many case reports of WNF exist in the literature, but few case–control studies even though they should be promoted because of their higher rank in the pyramid of evidence. A previous study on equine WNF has recently identified clinical variables that could potentially be helpful for an early recognition of WNF cases. However, this study only found variables that were less represented in the WNF compared with the control group (neurologically diseased horses but free from WNF; van Galen et al., 2013). Clinical variables being more represented in WNF would be more valuable 2

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for the early clinical detection of WNF in horses and could serve as an early alert for viral circulation and the possibility of consecutive human infections and human disease. Therefore, this case–control study will extend the search for clinical detection of WNF in horses. Despite the difficulties of the clinical recognition of WNF in horses by equine veterinarians, according to a recent study, the clinical surveillance appeared to be the most cost-effective system for WNV surveillance in the European context and there is a need for emphasizing its clinical recognition (Chevalier et al., 2011). The objectives of the study are (i) to model the clinical pattern of WNF in horses during a recent outbreak in Spain to improve awareness of the equine practitioners, (ii) to perform a first clinical screening in order to better select the cases that need priority laboratory testing and (iii) to capture the WNV activity in horses to be able to assess the threat to human disease and the need for interventions. Materials and Methods The study was conducted in the Mediterranean region of Andalusia, Spain. In this area, WNF vaccination coverage was negligible and only being performed after the occurrence of the disease within and close to the affected holding. The notification of cases by equine veterinarians (N = 125) was made in accordance with the already existing national surveillance of West Nile disease (Ministerio de Agricultura, Alimentaci
on y Medio ambiente, 2013). By definition, any horse showing neurological signs with or without hyperthermia was considered a WNF suspected case. The analysed data were obtained using a standardized clinical surveillance protocol carried out in Andalusia from September 2010 to December 2011. Clinical suspected cases of WNF were characterized by the onset of acute neurological signs. All these neurologically affected horses were tested for WNV infection by a cELISA. In the event of a positive result, the sample was tested by an IgM ELISA (cELISA; IDEXX IgM WNV Ab, IDEXX Lab, Westbrook, ME, USA). The cELISA detects antibodies against one epitope of the envelope protein of the flaviviruses of the Japanese encephalitis antigenic group, among which WNV. Whereas the IgM ELISA detected specific IgM antibodies against WNV using a West Nile recombinant antigen (WNRA) and comparing the response of the problem sample with a normal cell antigen (NCA). Subsequently and in the event of being positive, the samples were confirmed by micro serum-neutralization test (SNT) against WNV, strain Eg101 (Garc
ıa-Bocanegra et al., 2012). In addition, cerebrospinal fluid and blood samples from suspected animals were also tested to assess the presence of WNV RNA. The samples were analysed by RT-PCR © 2014 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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for detection of flaviviruses and differentiation of WNV lineages 1 and 2 (Jim
enez-Clavero et al., 2006; Sotelo et al., 2009). All analyses were performed by the National WNF Reference Laboratory in Algete, Spain. The neurological cases that tested WNV positive were defined as WNF cases, and those that tested WNV negative represented the control group. Unfortunately, besides the WNV serology, no further diagnostic information was available for the control cases. The data retrieved from the WNF cases and the controls were as follows: animal descriptive characteristics (age, breed and sex), the month of onset of clinical signs and clinical findings (such as the presence of increased rectal temperature >38.5°C, anorexia, depression, abnormal behaviour, cranial nerves deficits, hyperaesthesia, muscle fasciculations and/or spasms, ataxia, hypermetria, paresis, limb paralysis, recumbency, photophobia and nasal discharge) and disease outcome related to survival. To compare groups of horses (WNF cases versus controls and WNF survivors versus non-survivors), several statistical tools were used. Statistical analyses were carried out with STATA/SE Acad. 12 (Stata Corp., College Station, Texas) and Classification and Regression Tree (CART) Analysis (CART 6.0, Salford Systems, San Diego, CA, USA). Regression analyses were used to pre-screen the signs that should be entered into CART. Univariate and multivariate logistic regressions aimed the identification of major clinical signs associated or not with WNF, and negative binomial regression was used to investigate the possible seasonal effect of WNF occurrence declaration. The goodness of fit was assessed through a multivariate logistic regression using the Hosmer–Lemeshow goodness-of-fit test (Petrie and Watson, 2006). CART analysis was developed by Breiman et al. (1984) and Clark and Pregibon (1992) and was evaluated previously in medical science (Clark and Pregibon, 1992; Crichton et al., 1997; Thwaites et al., 2002). Further details and explanations on this CART analysis are available in previous veterinary articles (Saegerman et al., 2004; Speybroeck et al., 2004; Porter et al., 2011; van Galen et al., 2013). Briefly, CART analysis is based on the subdivision of the data set into randomly selected and roughly equal parts, with each ‘part’ contains a similar distribution of data from the populations of interest (i.e. confirmed versus unconfirmed cases). The analysis then uses the first nine parts of the data, constructing the largest possible tree, and uses the remaining 1/10th of the data to obtain initial estimates of the error rate of the selected subtree. The process is repeated, using different combinations of the nine remaining data subsets and a different 1/10th data subset to test the resulting tree. This process is repeated until each 1/10th data subset has been used to test a tree that was grown using a 9/10ths of the data © 2014 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

Clinical Surveillance of Equine West Nile Fever

subset. The results of the ten mini-tests are then combined to calculate error rates for trees of each possible size; these error rates are applied to prune the tree that was grown using the entire data set. The consequence of this complex process is a set of fairly reliable estimates of the independent predictive accuracy of the tree (Saegerman et al., 2011). The CART analysis was performed with presence or absence of WNF as the dependent variable. In this study, two different CART analyses were performed: one including the above-mentioned clinical signs and the period of occurrence of the disease as independent variables (or predictors), and another including only the above-mentioned clinical signs. The receiver-operating characteristic (ROC) curve was used to test the diagnostic usefulness of the four clinical signs more associated with WNF. Two exploratory options were tested. In the first one, the clinical score represents the sum of the clinical signs that were present. In the second one, the weighted clinical score of the four clinical signs that were significantly associated with WNF cases was used. In this last case, the pondered coefficient was the odds ratio obtained for each clinical sign. Results Animal description of horses involved in the clinical surveillance This study included a selection of 42 WNF confirmed cases and 36 control cases. For WNF confirmed cases, the titres of specific SNT antibodies ranged between 1 : 10 and 1 : 640. Among these confirmed cases, the presence of WNV was detected by RT-PCR from blood and cerebrospinal fluid (WNV lineage 1). The animal description of the WNF cases and control horses in Spain is presented in Table 1. For age (Welch test, P-value = 0.48), sex (v2 = 2; 1 df; P-value = 0.16) and breed (Fisher’s test exact; P-value = 0.32), no significant Table 1. The animal description of the West Nile Fever cases and controls in Spain

Breed Spanish or Spanish–Arabian Anglo–Arabian French Crossed Sex Female Male Age (year; mean  SD)

WNF cases N = 42

Controls N = 36

65% 0% 4% 31%

55% 12% 3% 30%

53% 47% 8.7  5.2

36% 64% 9.3  4.4

WNF, West Nile fever; N, number of cases.

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differences were found between the WNF cases and the controls. Seasonal effect of occurrence of the West Nile fever The first cases appeared in August and the last in December. In this region, the months September (25/42 cases) and October (12/42 cases) were significantly associated with the WNF cases (negative binomial regression; P-value < 0.01). Major clinical signs presented by horses and survival The overall survival rates in the WNF-affected group and the control group were 52% and 80%, respectively, and they were found to be statistically different. No survivors of the WNF-affected horses suffered from anorexia, hyperaesthesia and paresis. Sixty per cent and forty-two per cent of the WNF-affected and control horses, respectively, had been reported to have an increased rectal temperature. Besides this, the clinical signs of the affected horses were highly variable and included neurological signs from cerebral, cranial nerve and spinal involvement. The univariate analysis of clinical data allowed the identification of four clinical signs that were significantly more associated (i.e. photophobia, affection of cranial nerves, nasal discharge and limb paralysis), and two clinical signs were significantly less associated with WNF disease than to the control group (i.e. anorexia and paresis). In addition, survival is significantly more associated with the control

group than to the WNF horses (Table 2). Decubitus is significantly associated with WNF non-survivors compared with WNF survivors (OR = 0.18; 95% CI: 0.04–0.73). The multivariate analysis of those clinical signs that were significant in the univariate analysis shows that limb paralysis was significantly more associated with WNF disease (OR = 21.2 with 95% CI: 3.7–124; P-value = 0.001). In addition, anorexia (OR = 0.09 with 95% CI: 0.01–0.70; P-value = 0.02) and the disease outcome, that is, survival (OR = 0.08 with 95% CI: 0.01–0.51; P-value = 0.008), were more associated with animals that belonged to the control group. The Hosmer–Lemeshow test showed that the model fit the data well (v2 = 1.87, df = 1, P-value = 0.92). Receiver-operating characteristic curve Considering the clinical signs that were significantly more associated with WNF cases in the univariate analysis, a clinical score of four clinical signs was used to construct a ROC curve (Fig. 1). Two options were investigated: an unweighted and a weighted clinical score by odds ratio. However, there were no significant differences between the two areas under the curves (v2 = 3.37; P-value = 0.07). Clinical decision tree analysis The first CART analysis (considering clinical signs and the period of occurrence of the WNF cases) identified the period between August and November as predictor for WNF

Table 2. Major clinical signs in West Nile Fever cases and control groups WNF cases (N = 42)

Increased rectal temperature (>38.5°C) Anorexia Depression Abnormal behaviour (disorientation) Photophobia Affection of cranial nerves Hyperaesthesia Muscle fasciculations and/or spasms Ataxia Nasal dischargec Paresis Limb paralysis Decubitus Survival

Control group (N = 36)

Presence

Absence

Presence

Absence

OR (95% CI)

25 4 29 28 23 25 2 25 32 25 4 31 15 22

17 38 13 14 19 17 40 17 10 17 38 11 27 20

15 21 23 24 4 13 1 15 32 6 13 9 7 29

21 15 13 12 32 23 35 21 4 30 23 27 29 7

2.06 (0.83–5.09) 0.08 (0.02–0.26)a 1.26 (0.49–3.24) 1.00 (0.39–2.57) 9.68 (2.91–32.28)b 2.60 (1.04–6.51)b 1.75 (0.15–20.14) 2.06 (0.83–5.09) 0.40 (0.11–1.41) 7.35 (2.52–21.47)b 0.19 (0.05–0.64)a 8.45 (3.05–23.47)b 2.30 (0.81–6.50) 0.27 (0.10–0.74)a

OR, odds ratio; CI, confidence interval. Protective factor, less frequent in WNF than in the control group. b Risk factor, more frequent in WNF than in the control group. c No details available on origin and consistency of the nasal discharge. a

4

© 2014 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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(a)

Clinical Surveillance of Equine West Nile Fever

1

Sensitivity

.75

.5

.25

0 0

.25

.5

.75

1

.75

1

1 - Specificity

(b)

1

Sensitivity

.75

.5

.25

0 0

.25

.5

1 - Specificity Fig. 1. Receiver-operating characteristic (ROC) curve of the unweighted (a) and weighted (b) scores of the 4 putative clinical signs related to the WNF for horses in Spain. (a) Unweighted clinical score [area under curve = 0.85; SE (area) = 0.04]; 0,1,2,3 and 4 = clinical score; (b) weighted clinical score [area under curve = 0.86; SE (area) = 0.04]; dots represent the observed data.

infection in this region, and anorexia and paresis as predictors for absence of WNF (Fig. 2a and Table 3). In addition, the second CART analysis (considering only the clinical signs), revealed three major discriminatory variables as being useful to differentiate WNF from other neurological diseases (i.e. anorexia and paresis as main predictors for absence of WNF, and limb paralysis as predictor variable for WNF infection; Fig. 2b and Table 3). Discussion According to a comparative study, the passive surveillance of horses performed by equine veterinarians appeared to be the most cost-effective surveillance system in the European context of WNF (Chevalier et al., 2011). Although many equine case reports of WNF are described in the literature, there are few case–control studies even though they are at the highest level in the pyramid of evidence. In this study, © 2014 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

we used a standardized clinical data set of WNF-affected and control horses from Spain (Andalusia), with the aim to improve the clinical surveillance of WNF in horses by equine practitioners in advance of epidemic activity affecting humans. In the same way, this study allows to perform a first clinical screening in order to improve case prioritizing for laboratory testing. In Andalusia, alongside the passive surveillance that was described in the current study, also an active surveillance was performed using a random sampling of horses (Garc
ıaBocanegra et al., 2012). In total, 510 horses coming from 348 holdings of wetland areas (considered at higher risk of WNF) were tested from September to December 2010, obtaining an estimated seroprevalence of 7.1%. Moreover, the passive surveillance allowed the detection of 84 equine cases with neurological signs that resulted positive by IgM ELISA. In some of these cases, the circulation of WNV lineage 1 could also be confirmed by RT-PCR. In addition, in this particular geographic area of Spain, the active circulation of WNV was officially reported in 2010 and 2013 (RASVE, 2011). In Andalusia, where WNF vaccination coverage was negligible and only being performed after the occurrence of the disease within and close to the affected holdings, several reports indicate that human WNV disease cases occurred soon after the equine cases were detected (Garc
ıa-Bocanegra et al., 2011b; Jes
us-De La Calle et al., 2012). This confirms the usefulness of surveillance in non-human vertebrate hosts like horses in advance of the epidemic activity affecting humans (Chevalier et al., 2011; Porter et al., 2011). From the results of this current study and in agreement with previous research, specific animal traits such as breed, sex or age did not predispose to WNF (Cantile et al., 2001; Trock et al., 2001; Leblond et al., 2007; Porter et al., 2011). Although the identified signs are not pathognomonic, four clinical signs were suggested to be related to WNF cases in Spain, that is, cranial nerves deficits, limb paralysis, photophobia and nasal discharge. These clinical signs were also frequently observed in horses affected by WNF in Spain in another study (e.g. Garc
ıa-Bocanegra et al., 2012). A clear relation between the most common anatomopathological injuries observed in horses infected naturally by WNV (Cantile et al., 2001) and the clinical signs identified in our study was found. The location of gross lesions of encephalomyelitis in naturally infected horses by WNV occurred mainly in the medulla oblongata and the spinal cord. The presence of cranial nerves deficit and limb paralysis is highly compatible with these locations. Nasal discharge is not a direct neurological sign, but can be a result of dysphagia due to neurological deficits of the cranial nerves (in this case, it would be alimentary nasal discharge). However, very few of the WNF horses of this study were 5

Clinical Surveillance of Equine West Nile Fever

(a)

MONTH (N = 78) 53.8% pos. WNF

< 8, 11 and 12

No

HYPERESTHESIA (N = 28) 85.7% pos. WNF

N = 27 7.4% pos. WNF

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8, 9 and 10

Yes

Yes

No

N=1 100% pos. WNF

NASAL DISCHARGE (N = 10) 94.7% pos. WNF

N=8 12.5% pos. WNF

(b)

No

Yes

N = 31 96.8% pos. WNF

PARALYSIS (N = 53) 71.7% pos. WNF

Yes

N = 13 15.4% pos. WNF

ANOREXIA (N = 78) 53.8% pos. WNF

No

PARESIS (N = 50) 78% pos. WNF

No

ANOREXIA (N = 40) 0% pos. WNF

Yes

Yes

N=2 100% pos. WNF

N=4 25% pos. WNF

No

N = 36 97.2% pos. WNF

Yes

N = 25 16% pos. WNF

ATAXIA (N = 22) 36.4% pos. WNF

No

N=9 66.7% pos. WNF

Fig. 2. Classification and regression tree analysis for clinically affected WNF cases realized with (a) or without (b) considering the period of occurrence. pos. WNF = horse with positive result for detection of IgM antibodies to West Nile virus.

described to be anorexic, which would then be expected. Nasal discharge was not previously reported in WNF disease, while dysphagia was only rarely reported in the first episodes of WNF in France (Camargue), but it was more prevalent in the more recent outbreaks of 2004 (Leblond A., pers. com.). Nasal discharge can also be unrelated to dysphagia and of another consistency, namely serous, 6

mucous or purulent. In infections caused by Japanese encephalitis virus (another flavivirus), mucous nasal discharge was also reported in equine cases (Consultant, 2013). In addition, nasal discharge was recurrently observed in experimental infection of birds or mammals by WNV (Center for Food Security and Public Health, 2013). Detailed data on the origin and consistency of the nasal © 2014 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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Clinical Surveillance of Equine West Nile Fever

Table 3. Power (relative importance) of the different clinical signs (splitters) obtained after classification and regression tree (CART) analysis (maximum relative importance = 100) Predictor variable

Discriminatory power

CART I (Se = 90.5%; Sp = 97.2%) Anorexia Period of occurrence Nasal discharge Limb paralysis Photophobia Paresis Hyperaesthesia

Predictor variable

Discriminatory power

CART II (Se = 85.7%; Sp = 88.9%)

a

b

100 83.40 52.15 48.39 43.80 32.21 22.99

Anorexia Limb paralysis Paresis Ataxia Nasal discharge Photophobia Decubitus Muscle fasciculation and/or spasms Depression Hyperaesthesia

100 98.38 90.25 26.62 25.61 25.61 18.50 11.19 8.72 1.02

Se, sensitivity of the tree; Sp, specificity of the tree. Classification and regression tree analysis for clinically affected WNF cases considering the period of occurrence. b Classification and regression tree analysis for clinically affected WNF cases without considering the period of occurrence. a

discharge are unfortunately lacking in the current study. The origin of the nasal discharge should be reported in more detail during the data collection process in the future. The season was identified as a predictor variable using the regression analysis and the first CART analysis, indicating that the period between August and November should be considered in the presumptive clinical diagnosis in this region. As previously suggested (Porter et al., 2011), this can be explained by the higher activity of WNV transmitting vectors during the summer months, in combination with a relatively short incubation time. Based on ROC curve analysis, the clinical score obtained with the four most strongly related signs of WNF appeared to be efficient to distinguish the WNF case from the control horses. The area under the curve was significantly higher than a similar study previously published (Porter et al., 2011). In addition, following this study, a clinical decision tree with high sensitivity and specificity can be suggested with anorexia, paresis, nasal discharge and paralysis as main discriminatory clinical signs. Especially, the high sensitivity of the clinical decision tree renders its use interesting for veterinary practitioners in the field as a screening test to better select the cases that need priority on laboratory testing. A high clinical suspicion by this decision tree should, however, always be followed by a more precise diagnostic laboratory tests. Its value is more important during the vector season activity than outside this period, as suggested by the two CART options investigated. Moreover, the statistical comparison between survivors and non-survivors allowed identifying decubitus as a key element for poor prognosis. However, this indicator is undoubtedly associated with more severe neurological signs as compared to absence of recumbence. However, some bias can be present, explained by veterinarians choosing © 2014 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

euthanasia in recumbent horses and not awaiting natural death. Any system of clinical detection that increases awareness of veterinarians in regions at risk (during summer and autumn seasons, located at migratory routes and in humid area favourable to mosquito activity) should be promoted, but some difficulties exist to develop such systems. Quantitative and standardized data on passive surveillance of WNV in horses in Europe are limited to a small number of studies (e.g. Leblond et al., 2007; Porter et al., 2011; van Galen et al., 2013), unfortunately all with limited power. Recent scientific reports of increasing flaviviruses activity during the last decade in the Mediterranean basin underline the importance of passive surveillance of horses in the European Union (e.g. Barros et al., 2011; Chaskopoulou et al., 2011; Garc
ıa-Bocanegra et al., 2011a; Spissu et al., 2013). However, because of the antigenic similarities between flaviviruses like Usutu virus Japanese encephalitis virus among others, each clinical suspected case must be confirmed by the use of SNT reaction against WNV (Shi and Wong, 2003). Usutu virus was commonly found in different European countries in birds (V
azquez et al., 2011a) and horses (Barbic et al., 2013), in mosquitoes (Busquets et al.,2008; Vazquez et al., 2011b), and was also documented in neurologically affected horses in Italy (Macini et al., 2008). In Spain, seropositive birds were found based on positive results of WNV ELISA, but unconfirmed with specific SNT, and therefore, these animals may have been infected with other flaviviruses of the Japanese encephalitis complex (Garc
ıa-Bocanegra et al., 2011a; Alba et al., 2014), especially because both Usutu virus and Bagaza virus have been recently detected in Andalusia (Garc
ıa-Bocanegra et al., 2013; Llorente et al., 2013), while Meaban virus has been recently detected in Medes Islands (Catalonia; Arnal 7

Clinical Surveillance of Equine West Nile Fever

et al., 2014). These flaviviruses species have been detected in birds, ticks and mosquitoes, but not in equines. The passive surveillance is not only very useful to identify WNV, but also to detect other future flavivirus threats in horses. In addition, some reports also suggest possible enzootic WNV circulation in European countries (Garc
ıa-Bocanegra et al., 2011a; Monaco et al., 2011). From our point of view, the experience of the field veterinarians was critical to suspect and declare WNF cases during the WNF outbreak in Spain. Taken into account that this was the first important WNF outbreak in Spain and that clinically affected animals presented non-specific and variable neurological signs, we consider that the importance of the outbreaks was probably underestimated. In this sense, training and motivating veterinarians are two critical factors to increase the efficacy and strength of WNF passive surveillance. Even though, this study demonstrates the possibility and importance of early clinical detection of WNF, subsequent confirmation by serology and viral detection remains undoubtedly necessary and indispensable. European collaboration on animal health surveillance of WNF (e.g. with the use of a European standardized clinical data base) and a stronger link with the human surveillance (ECDC, 2013) are recommended to face this emerging virus. Conclusions One of the major results of this study implies that the need for specimen collection and testing for WNV in horses can be determined following a high suspicion of WNF based on clinical data. This approach would imply an improved detection of WNV and a reduction in the costs. As human WNV disease cases may occur simultaneously with or soon after equine cases in areas with no or negligible vaccination coverage in horses, horses are considered early sentinels. Therefore, data on equine WNV disease may be very useful to assess the risk of human infections and the need for interventions. In addition, this surveillance can be useful for other flaviviruses, which can be a future threat in Europe. Acknowledgements This research was funded by the Junta de Andaluc
ıa/Universidad de C
ordoba, Departament d’Agricultura, Ramaderia, Pesca, Alimentaci
o i Medi Natural/CReSA and UREAR-ULg. Authors thank all of actors of the passive surveillance Spanish network. Conflicts of Interest The authors declare no conflict of interest. 8

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