The Schmallenberg virus epidemic in Europe-2011-2013.

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The Schmallenberg virus epidemic in Europe—2011–2013 Ana Afonso a,∗ , Jose Cortinas Abrahantes a , Franz Conraths b , Anouk Veldhuis c , Armin Elbers d , Helen Roberts e , Yves Van der Stede f,g , Estelle Méroc g , Kristel Gache h , Jane Richardson a a

European Food Safety Authority – V. Carlo Magno 1A, 43126 Parma, Italy Friedrich-Loeffler-Institut, Insel Riems, Germany GD Animal Health Service, PO Box 9, 7400 AA Deventer, The Netherlands d Central Veterinary Institute, part of Wageningen UR, PO Box 65, 8200 AB Lelystad, The Netherlands e Animal Health and Veterinary Laboratories Agency, Defra, Nobel House, 17 Smith Square, London SW1P 3JR, UK f Unit of Co-ordination Veterinary Diagnosis-Epidemiology and Risk Assessment, CODA-CERVA, Groeselenberg 99, 1180 Brussels, Belgium g Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium h GDS France (National Animal Health Farmers’ Organization), 75012 Paris, France b c

a r t i c l e

i n f o

Article history: Received 25 October 2013 Received in revised form 8 February 2014 Accepted 28 February 2014

Keywords: Schmallenberg virus Data collection Spatial and temporal distribution Seroprevalence Impact

a b s t r a c t During the Schmallenberg virus (SBV) epidemic, the European Food Safety Authority (EFSA) collected data on SBV occurrence across Europe in order to provide an assessment of spread and impact. By May 2013, twenty-nine countries were reporting to EFSA and twenty-two countries had reported cases of SBV. The total number of SBV herds reported was 13,846 and the number of SBV laboratory confirmed herds was 8730. The surveillance activities were based on the detection of SBV clinical cases (either adults or newborns). Malformation in newborns was the most commonly reported clinical sign of SBV-infection. All countries were able to provide the date when the first suspicion of SBV in the herd was reported and nineteen could report the location of the herd at a regional level. This allowed the spread of SBV in Europe to be measured both temporally and spatially. The number of SBV confirmed herds started to increase in December 2011 and two peaks were observed in 2012 (February and May). Confirmed herds continued to be reported in 2012 and into 2013. An increase during winter 2012 and spring 2013 was again observed, but the number of confirmed herds was lower than in the previous year. SBV spread rapidly throughout Europe from the initial area of detection. SBV was detected above the latitude of 60◦ North, which exceeds the northern expansion observed during the bluetongue virus serotype 8 epidemic in 2006–2009. The impact of SBV was calculated as ratio of the number of herds with at least one malformed SBV positive foetus and the total number of herds in this region. The 75th percentile of the malformations ratio in the various affected countries for the whole reporting period was below 1% and 3% for cattle and sheep herds, respectively. International data collection on emerging diseases represents a challenge as the nature of available data, data quality and the proportion of reported cases may vary widely between affected countries. Surveillance activities on emerging animal diseases are often structured only for case detection making the estimation of infection/diseases prevalence and the

∗ Corresponding author. Tel.: +39 0521036666; fax: +39 05210360666. E-mail address: [email protected] (A. Afonso). http://dx.doi.org/10.1016/j.prevetmed.2014.02.012 0167-5877/© 2014 Elsevier B.V. All rights reserved.

Please cite this article in press as: Afonso, A., et al., The Schmallenberg virus epidemic in Europe—2011–2013. PREVET (2014), http://dx.doi.org/10.1016/j.prevetmed.2014.02.012

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investigation of risk factors difficult. The impact of the disease must be determined to allow risk managers to take appropriate decisions. Simple within-herd impact indicators suitable for emerging disease outbreaks should be defined that could be measured as part of routine animal health surveillance programmes and allow for rapid and reliable impact assessment of emerging animal health diseases. © 2014 Elsevier B.V. All rights reserved.

1. Introduction The ongoing systematic collection and analysis of animal disease data is the core of an animal disease surveillance system. It should result in relevant intelligence at an appropriate spatial and temporal resolution to support risk managers in taking decisions to prevent and control animal diseases and possible public health implications. Important requirements for existing surveillance systems to ensure preparedness for emerging diseases at European level are: clear and specific case definitions, integration with laboratory services and use of appropriate and validated diagnostic reagents and methods, consistent and robust epidemiological indicators and generic data models to facilitate data transfer and analysis (Richardson et al., 2011). In recent years, the need to perform risk assessments at a European Union (EU) level for animal diseases required the development of ad-hoc data collections on emerging and re-emerging diseases like bluetongue serotype 8 (EFSA, 2007) and Q fever (EFSA, 2010). Such ad-hoc data collections were necessary to estimate disease prevalence, spread or impact. In August 2011, farmers and veterinarians in North Rhine-Westphalia (Germany), the Netherlands and Belgium started to report cases of clinical disease in cattle (Hoffmann et al., 2012; Muskens et al., 2012; Cay et al., 2011). Clinical signs were unspecific and transitory: fever, drop of milk yield for several days and in some cases also diarrhoea. Several disease agents such as bluetongue virus, bovine viral diarrhoea virus, bovine herpes virus-1, malignant catarrhal fever virus foot-and-mouth disease virus and exotic viruses like epizootic hemorrhagic diseases virus, Rift Valley fever virus or bovine ephemeral fever virus were excluded by diagnostic analysis. In November 2011, the German national reference laboratory (FLI) detected genomic sequences of a new Orthobunyavirus; the virus was provisionally named “Schmallenberg virus” (SBV) (Hoffmann et al., 2012). Subsequently, the same virus was detected in samples from malformed lambs and calves in Germany, Belgium and the Netherlands (ProMEd-mail, 2011a, 2011b; Van den Brom et al., 2012). The disease situation was presented by these three countries at the Standing Committee on the Food Chain and Animal Health (SCoFCAH), the EU member states (MS) representation on matters related to Animal Health, in January 2012. The MS and the European Commission (EC) issued a statement on the disease, recognising the need to collect and share information (EC, 2012). In the EU, the Animal Disease Notification System (ADNS) application is used to ensure rapid exchange of information between MS and the EC on outbreaks of notifiable diseases. The diseases which are classified by the

EU as notifiable are listed in EU legislation (Annex I to Directive 82/894/EEC). Notification implies not just reporting but also the need for control or eradication measures to be put in place. However, the system does not include provisions for collection of information on emerging diseases and an ad hoc data collection was necessary. The European Food Safety Authority (EFSA) was requested by the EC to collect data on SBV occurrence from MS in order to provide an assessment on SBV spread and impact. The EU and each of its MS are members of the World Organization for Animal Health (OIE) and therefore have the obligation to report animal diseases detected in their territory. The large majority of disease reports are on listed diseases. The inclusion of an animal disease to the OIE list follows a detailed procedure: a recommendation by the OIE relevant ad hoc group is submitted for endorsement by the relevant elected specialist commissions before it is presented for final adoption by the World assembly of delegates. The criteria for the inclusion of a disease in the OIE List are described in detail in the OIE code. In brief, they relate to feasibility of diagnosis, characteristics of the disease spread and its impact either on public health, animal health or the environment. Diseases can also be listed as emerging diseases when there is evidence of zoonotic potential, rapid spread or significant morbidity and mortality. An “emerging disease” is – as defined by the OIE – a new infection resulting from the evolution or change of an existing pathogenic agent, a known infection spreading to a new geographical area or population, or a previously unrecognized pathogenic agent or disease diagnosed for the first time and which has a significant impact on animal or public health (OIE, 2013). Listing by the OIE as well as inclusion on the list of notifiable diseases by the EU legislation makes it necessary to establish surveillance measures that allow demonstration of disease freedom, early detection and control measures to avoid the spread or the introduction of the disease. The economic impact of such measures can be high and risk managers need to decide on their value. The OIE was notified of the first and of subsequent cases of SBV detected in various MS of the EU as an emerging disease. However, to make SBV infection a listed disease in accordance with the OIE, demonstrating the spread and impact of the infection is required. The objectives of this study were to describe the European data collection effort regarding the SBV epidemic, present the results of the disease spatial and geographic distribution during 2011–2013 and discuss its possible impact. In addition, the level of under-ascertainment of the surveillance system was assessed in order to improve the accuracy of our estimates.




2. Materials and methods 2.1. Data collection: reporting officers network nomination and organization, data reporting guidelines The notification of SBV in the EU was not compulsory. Neither mechanism nor guidelines were available for a harmonised data collection and reporting of a non-notifiable disease. Harmonised case definitions were agreed between the MS. The information related to suspect and confirmed herds was collected at national level by National Veterinary Competent authorities and reported to EFSA by officially appointed reporting officers. The systems in place for dissemination of information on the case definitions, confirmation of suspect cases, reporting and epidemiological investigation of the outbreaks/cases varied across MS. An online questionnaire was submitted in July 2013 to the network of reporting officers to provide an overview of the current surveillance activities in the different MS. The network of reporting officers was involved in the development of case definitions and reporting guidelines together with EFSA. The reporting officers were provided with access to the EFSA data collection framework (DCF) system and relevant training for its use; they were responsible for reporting by the agreed deadlines and for reviewing the analysis outputs. The network operated by having regular teleconferences, once a week from February to April 2012 and subsequently once a month till the end of 2012. The countries were given the option to either share all their data with other MS or exclusively with EFSA. The SBV data reporting guidelines were proposed in February 2012 (EFSA, 2012a) and updated in September 2012 (EFSA, 2012c) based on the experience gained from the reports submitted in spring 2012. The guidelines provide information on: (i) reporting deadlines, (ii) objectives of the datasets (minimum and extended), (iii) plan of analysis (iv) population and epidemiological units to be considered, (v) case definitions of a suspect and confirmed SBV case at animal and herd/flock level and (vi) definitions for each of the required variables (metadata). 2.2. Case definitions: clinical cases and laboratory confirmation The initial cases of SBV in Europe in 2011 were associated with unspecific clinical signs in adult cattle in the late summer of 2011 and with congenital malformations in newborn animals, mainly lambs, starting from midDecember 2011. At that time various case definitions were being used by different MS (Table 1). For this study, uniform case definitions were used by all countries reporting infections with SBV. Case definitions were adopted at animal level for both adult animals and offspring as well as at herd level and were:

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the following: arthrogryposis, hydranencephaly, ataxia, paralysed limbs, muscle atrophy, joint malformations, torticollis, kyphosis, scoliosis, brachygnatia inferior, behavioural abnormalities and blindness). 2.2.1.2. Confirmed case. Following suspicion, a confirmation of viral infection by RT-qPCR, virus isolation or detection of pre-colostral antibodies. 2.2.2. Adult animals 2.2.2.1. Suspicious case. Ruminants with transient fever (>40 ◦ C), diarrhoea, anorexia and reduced milk production (that is not attributed to a known cause). 2.2.2.2. Confirmed case. Confirmation of viral infection by RT-qPCR, virus isolation or detection of SBV-specific antibodies by ELISA, viral neutralization test (VNT) or indirect immunofluorescence (IFAT). 2.2.3. Herd case definition Any herd with one or more suspect or confirmed cases was considered a case herd. Several diagnostic reagents and methods were available for laboratory confirmation and were included in the definitions and updated as new methods were developed. The samples to be collected and laboratory methods to be used were also included in the guidelines and were the ones recommended by the OIE, 2012. 2.3. SBV case finding dataset A dataset was initially specified for the collection of information required for the assessment of the impact of SBV. This dataset was based upon herd/flock level data currently being collected within the affected MS and designed for case detection. The variables specified in the dataset are described by EFSA, 2012b and an updated version of the dataset was provided later on EFSA, 2012c. Twenty-one of the twenty-six variables in the dataset were mandatory since this was the critical information required in order to assess spread and impact. To ensure that the country level data could be analysed at a European level, controlled terminology was applied to eight of the eleven string variables. The geographical regions were described using the Nomenclature of Territorial Units for Statistics (NUTS) at level 2 or 3 (Regulation, 2003) and animal species according to the coding system used for the EU system for monitoring and reporting of information on zoonoses. Upon submission to the DCF, datasets were automatically tested for compliance with variable names, data type, mandatory variables and controlled terminologies. In a second step, variable checks were made to ensure that reported dates and regions were plausible and that reported numerator variables (numbers) did not exceed denominator variables. 2.4. Data submission and data collection framework

2.2.1. Foetuses and neonates 2.2.1.1. Suspect case. Arthrogryposis hydranencephaly syndrome (AHS) in ruminants (stillbirths, premature births, mummified foetuses, and dysfunctions or deformities of foetuses or neonates with two or more of

The DCF is a secure web portal which supports the submission and validation of datasets submitted to EFSA for use in risk assessment, and is built using Java, Oracle and XML technologies. The web portal is organized into




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Table 1 Case definitions for suspicion of infection with SBV used in the affected Member States in January 2012 (EFSA, 2012a). Adult animal

Offspring

Germany

N/A

Netherlands

Acute diarrhoea, drop in milk production, fever or any other clinical suspicion notified by farmers who ask for exclusion of SBV (as cause of the clinical problems) by diagnostic testing of (blood) samples. Cattle with high temperature, drop in milk production and diarrhoea. N/A

Occurrence of malformations of the arthrogryposis hydranencephaly syndrome (AHS) in calves and lambs. Any malformed calf, goat-kid or lamb.

Belgium United Kingdom

France

N/A

domain specific data collections. The permissions for the SBV area were set at the level of the reporting organisation, so one or more data providers can submit data for an organisation and only users from that organisation can access the data or the data collection administrator (EFSA). The officially nominated reporting officers were registered users. XML Schema Definitions (XSDs) were provided to assist MS performing automated transformations from their data management systems. In addition, an Excel template was provided to assist the MS which prepared their data sets manually. The XSD was mapped to the Excel template to allow the dataset to be exported in XML. Data submissions to the DCF using both XML and Comma Separated Values (CSV) formats were supported. 2.5. Study period The period considered for this study and for which data was collected was from 1 August 2011 till 30 April 2013. In order to investigate disease spread to newly affected herds and occurrence of new cases in previously infected herds, data were collected in two sets corresponding to two different time periods: 1 August 2011–31 July 2012 and 1 August 2012–30 April 2013. 2.6. Data analysis Data analysis was performed with R (R Core Team, 2013), SAS enterprise guide 5.1 (SAS, 2006) and ArcMap 9.3 (ESRI, 1996). The structure of the monitoring programmes in each reporting country was summarised. Temporal analysis was based upon the date when the first suspicion of SBV in the herd was reported. Spatial analysis was

Sheep, goats, cattle: abnormally high rate of stillbirths or abortions, birth defects such as malformations of the joints, hydrocephalus. Arthrogryposis or profound congenital nervous signs (obtundation (“dummy” presentation), blindness or marked paresis/paralysis) in a ruminant neonate or foetus and, in addition, for neonates and foetuses from ruminant dams imported from mainland Europe in 2011, any stillbirth, weakness or disease with nervous signs. Within the known range of SBV cases, cattle, sheep or goat: (i) abortion or malformed newborn (arthrogryposis, shortening of the hamstrings, deformation of the jaw, hydranencephaly torticollis, etc.) or (ii) newborn with neurological disorders (flaccid paralysis, exaggerated movements, irritability, trouble feeding, ataxia, etc.). Outside the known range of SBV cases: second case (or more) of cattle, sheep or goat (i) abortion or malformed newborn, (arthrogryposis, shortening of the hamstrings, deformation of the jaw, hydranencephaly, stiff neck, etc.) or (ii) of newborns with neurological disorders (flaccid paralysis, exaggerated movements, irritability, trouble feeding, ataxia, etc.), occurring in the same farm during a quarter. Suspected case followed by confirmation by RT-qPCR

performed at country level and NUTS region (where available at level 2 or reclassified from level 3 to 2). Data reported using NUTS regions were linked with herd-level population data (Eurostat, 2007). Estimates of distances from previously affected regions to newly affected regions based on the week of first report were made using the distance between centroids of NUTS 2 regions in kilometres in order to establish the potential relationship between time period and spatial spread. Estimates of the distance between centroids formulae are based on the centroids coordinates on a two dimension plane. Considering that the globe is spherical an Equidistant Conic projection system for Europe was used to preserve true-to-scale distances and ensuring balancing shape and minimising area distortion so that the distance between two points could be estimated. For each newly affected region the shortest distance from a previously affected region was estimated using the Euclidean distance formula. In order to estimate the distance spread trend over time, the smallest distance to the following confirmed case in a new NUTS 2 region is calculated. A smoothing technique (Cleveland and Devlin, 1988; Cleveland et al., 1993) is used given that the type of relationship between distance spread and time is not apparent, a LOESS (local regression smoothing procedure) smoothing procedure was followed. Considering an appropriate window span of the data (number of points neighbouring the specific observation representing 60% of the data), regression weights (based on a tri-cube function) for each data point in the span window was calculated. Second, a weighted linear least squares regression is performed (a second order polynomial was used) and the smoothed value is then given by the weighted regression at the predictor value of interest.




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The ratio between the number of confirmed SBVinfected herds reported to DCF and the expected number of SBV-infected herds was calculated for selected regions of Belgium, France and the Netherlands where prevalence estimates were available from surveys based on serological investigation. The exact 95th percentile confidence intervals for the regional (NUTS 2 regions) prevalence, were estimated from the numbers of tested and positive herds per region. The expected number of infected herds per NUTS 2 regions was calculated using the limits of the exact confidence interval multiplied by the number of herds in that region. The AHS case intensity was calculated as an estimate of disease impact. AHS case intensity is the ratio between the number of herds confirmed with observations of AHS cases per NUTS 2 region and the total number of herds per region.

Subsequent investigations of the herd of origin after confirmation of SBV infection in an individual animal were obligatory in 4 out of 19 countries. Testing for SBV infection on foetus submitted for diagnostic of abortion cause was done in 8 countries and laboratory testing for diagnosis of abortion causes was paid by the farmer in 7 of these countries (Table 2). The ratio between the number of confirmed SBVinfected herds reported to DCF and the expected number of SBV-infected herds in regions included in seroprevalence studies made in Belgium, France and the Netherlands is presented in Table 3. In cattle, the lower quartile of the ratio was 0.003–0.004 and the upper quartile was 0.010–0.055. In sheep the lower quartile ratio was between 0.007 and 0.010 and the upper quartile was between 0.038 and 0.240.

3. Results

3.2. Temporal and spatial spread of reported cases

3.1. Surveillance activities

All reporting organisations provided the date when the first suspicion of SBV in the herd was reported and nineteen reporting organisations reported the location of the herd at a regional level (NUTS Level 2 or lower). This allowed the spread of SBV-reported cases in Europe to be measured both temporally and spatially. The time of the first herd report for herds confirmed by direct detection from September 2011 to April 2013 is shown in Fig. 2 for cattle, sheep and goats. According to the data, the first SBV confirmed herds were in cattle: infected adult animals were detected during the first week of September 2011 and later confirmed by direct detection (RT-qPCR). Regarding sheep, the first confirmed SBV flocks were detected not by the detection of adult cases but by clinical cases (AHS in foetus) confirmed by virus direct detection in the last week of November 2011. The number of SBV confirmed herds and AHS cases started to increase in December 2011 and two distinct peaks were subsequently observed. The peak in the last week of February 2012 resulted largely from confirmation in sheep herds and the peak in the first week of May 2012 came from confirmations in cattle. Confirmed herds continued to be reported for the remainder of 2012 and into 2013. An increase during winter 2012 and spring 2013 was again observed, but the number of confirmed herds was lower than in similar periods of the previous year. SBV was first detected in Germany, the Netherlands and Belgium (September to December 2011), followed by Italy, France, Luxembourg and the United Kingdom (January to February 2012), Denmark, Spain (March to June 2012), Ireland, Switzerland, Austria, Czech Republic, Poland, Latvia, Estonia, Sweden, Finland and Slovenia (July to December 2012). The first cases confirmed by direct detection in Norway were reported in 2013, although serological evidence of SBV was obtained in 2012. Hungary and Croatia reported the first confirmed cases in 2013. Spain had only 2 regions with confirmed cases corresponding to a total of 5 herds. France had cases reported for the first time in a new region from January 2012 until December 2012 and UK reports indicated a spread with a North Westerly direction (Fig. 3). The reported data indicates that SBV spread above the latitude of 60◦ North, which exceeds the

Surveillance activities varied considerably within Europe. An overview of the surveillance activities in the reporting countries is presented in Table 2. The network of reporting organisations comprised a mix of veterinary organisations, agricultural ministries, research institutes, national animal health institutes, farmers’ organizations and food safety agencies depending on the existing structures within the countries. By May 2013, the network included twenty-six MS, two countries in the European Free Trade Association (EFTA) area and one Accession Country. Twenty reporting organisations were able to submit the minimum dataset via the DCF, predominantly in XML format. All countries where SBV was detected by RTqPCR in tissues from suspect neonates were included in the surveillance programme. Eleven countries also used diagnostic methods in adults in order to detect acute cases of SBV infection. In 2012, indirect ELISA assays became available in seven countries. These ELISA were used to test RT-PCR-negative suspect neonates for the presence of SBVspecific pre-colostral antibodies and fourteen countries started testing adult animals generally as part of serosurveys and serological monitoring programmes. Until May 2013, twenty-two countries had reported cases of SBV and two countries had made a declaration of no detection. The total number of SBV case herds reported to DCF (suspect and confirmed herd cases as in accordance to the case definition) was 13,846 out of which 8730 were SBV confirmed herds. SBV was confirmed in alpacas, bison, cattle, sheep, goats, deer, buffalo and moose and tested, but not confirmed, in horses camels and lamas. Fig. 1 illustrates the number of suspected/confirmed herds per country during the whole reporting period, between 1 August 2011 and 30 April 2013. Eight out of twenty-two countries (36%) reported only cases of SBV confirmed herds. The ratios of confirmed/suspected herds varied considerably between countries that provided this data. The Netherlands was the first MS to impose mandatory notification of malformed calves, lambs and goat kids, from December, 2011 to July, 2012. In July 2013, SBV was notifiable at the national level in Croatia, Germany, and Italy.




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Table 2 Organisations participating in SBV surveillance network, national SBV regulations and detection methods used for confirmation of suspect cases. Country

Austria Belgium Croatia Cyprus Czech Republic Denmark Estonia Finland France

Germany Hungary Ireland Italy Latvia Lithuania Luxembourg Netherlands Norway Poland Portugal Slovenia Spain Sweden Switzerland United Kingdom

Data provider

Austrian Agency for Health and Food Safety Belgian Federal Agency for the Safety of the Food Chain Ministry of Agriculture National Reference Laboratory for Animal Health State Veterinary Administration Czech Republic Danish Ministry of Food, Agriculture and Fisheries Veterinary and Food Board Finnish Food Safety Authority Agence nationale de sécurité sanitaire de l’alimentation, de l’Environnement et du Travail and GDS France Friedrich Loeffler Institut Ministry of Rural Development Dept Agriculture Food and the Marine Ministero della Salute Food and Veterinary Service of the Republic of Latvia State Food and Veterinary Service of the Republic of Lithuania Veterinary Service Administration Food and Consumer Product Safety Authority Netherland Mattilsynet National Veterinary Research institute Direccao Geral de veteinaria Veterinary Administration Subdirección General de Sanidad e Higiene Animal y Trazabilidad Jordbruk verket Federal Veterinary Office Department of Food and Rural Affairs

SBV is a notifiable disease (status in July 2013)

Diagnostic confirmation method used in adult suspect cases Direct detection

Indirect detection

No No

Y N

Y N

Yes No

N NR

N NR

No

N

N

No

N

N

No NA No

Y Y N

Y Y Y

Yes No No Yes NA

Y NR N Y Y

Y Y N Y Y

No

NR

NR

NA Yesa

Y N

N Y

No NA NA No No

N Y NR N Y

N Y NR N Y

No No No

N Y Y

Y Y Y

NA, no answer; NR, no cases reported. a Birth of malformed calves, kids and lambs with the AHS syndrome was notifiable between 20/12/2011 and 6/7/2012.

Northern expansion observed during the bluetongue virus serotype 8 epidemic in 2006–2009. The estimates of the distance of spread from previously affected regions to newly affected regions are provided in Fig. 4. The 25th to 75th quartile range for the spread distance is 73–173 km and the smoothed distance of spread rarely exceeds 200 km. The upper limit of the 95% confidence interval of the mean is 182 km (dotted lines in Fig. 4). Fig. 4 shows, a number of extreme outliers: 1092 km to Etelä-Suomi in Finland, 868 km to Andalucia in Spain,

551 km to Veneto and 496 km to Sardinia in Italy, which might indicate spread by animal movement over long distances. 3.3. Impact assessment A summary of the data available for the assessment of SBV impact is presented in Table 4. The maximum number of AHS cases observed within a herd varied from one in goat flocks, five in cattle herds and 100 in

Table 3 Ratio of confirmed SBV infected reported herds to expected herds (estimates based on selected regions from France, Netherlands, Belgium). Ratio reported/expected Mean

Median

Cattle

Lower bound Mean Upper bound

0.004 0.003 0.003

Lower quartile

0.067 0.019 0.016

0.01 0.008 0.007

0.055 0.012 0.01

Sheep

Lower bound Mean Upper bound

0.01 0.007 0.007

0.195 0.027 0.025

0.057 0.021 0.02

0.24 0.038 0.038

Upper quartile




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Fig. 1. SBV herd cases suspect/confirmed per country in EU reporting countries (1 August 2011–30 April 2013).

sheep flocks. Information on the number of animals in the reported herd (herd size) was available for 31%, 44% and 45% of the cattle, sheep and goat flocks, respectively. It was not possible to calculate the proportion of clini-

cal cases within the confirmed herds. For confirmed herds with AHS signs, 0.34% of the cattle herds reported more than one malformation, while in sheep this proportion was 5.15%.

Fig. 2. Number of SBV cases confirmed by direct detection by week of first report with proportion of cattle, sheep and goats.



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Fig. 3. Regions (NUTS2) with at least one SBV herd confirmed by direct detection by period of first report.

Fig. 4. Estimates of distances from affected regions to newly affected regions at NUTS2 level by week of first suspicious report. The median distance between NUTS2 centroids and the upper limit of the 95% confidence interval is represented by the dotted lines. The continuous line represents the smoothed distance.


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A. Afonso et al. / Preventive Veterinary Medicine xxx (2014) xxx–xxx Table 4 Information available for SBV impact assessment. Cattle Confirmed herds Herd size reported Herds with AHS observed Maximum observations of AHS in herd Herds with AHS observed > 1 Herds with acute adults observed Maximum observations of acute adults in herd Herds with acute adults observed > 1

5.281 31% 89%

4. Discussion

Goats 136 45% 91%

Sheep 2.917 44% 93%

5

1

0.34%

0.00%

5.15%

6%

1%

3%

350

12%

9

2

100

50

100%

6%

The data suggests that when an AHS case was reported on a farm, samples were usually taken for laboratory confirmation, but a follow-up visit to record the impact within the herd in terms of number of offspring affected, mortality in offspring, abortions etc. was often not carried out. Therefore, only a between-herd impact assessment was possible with the available data. The between-herd impact was assessed by the AHS case intensity. The 75th percentile of the AHS case intensity was below 1% and 3% with a maximum AHS case intensity of 4 and 7% of the affected cattle and sheep herds, respectively (Fig. 5).

Fig. 5. AHS intensity in cattle and sheep herds in the EU.

The objective of EFSA’s coordinated SBV data collection at a European level was to investigate the spread of the disease and assess its impact in order to support EU risk managers to take decisions on the implementation of control measures and to provide information to trade partners. At the start of the epidemic, surveillance activities were based on case reporting of clinical suspicions to the competent authorities. This type of surveillance is considered passive because the decision to report and submit an animal or a sample is made by the animal owner and/or the veterinarian, and not by the veterinary authority (Hadorn and Stärk, 2008). In general, the sensitivity of passive surveillance systems to detect disease cases is not easy to quantify (Madin, 2011) and is assumed to be biased. The sensitivity is influenced by factors like the probability of infected animals showing clinical signs, disease awareness and the motivation to report (Elbers et al., 2010). All these factors will contribute to under-ascertainment of the infection status of an animal population, showing only “the tip of the iceberg” (Elbers et al., 2002). However, it is a practical solution for early detection of emerging diseases. Several countries have performed seroprevalence studies for SBV which provided a better understanding of SBV infection between-herds or regions and also within-herds for ruminants. Results from serosurveys conducted in the Netherlands (Veldhuis et al., 2013), Belgium (Méroc et al., 2013a, 2013b) and France (Gache et al., 2013) provided estimates of between-herd seroprevalence in NUTS regions, ranging from 8 to 99.99% in cattle, 94.7–98.18% in sheep and 74.7–86.5% in goats. Our study estimated that the number of infected herds in those NUTS regions may be 5–300 times greater than the number of SBV infected confirmed herds reported to the EFSA system (Table 3). It is important to note that these results are based on results obtained in studies in only three countries and that serological results may be difficult to compare with reported cases via passive surveillance. The studies included were very different between them in terms of sampling methods (time of sampling and geographical coverage) as well as diagnostic testing used. Belgium and the Netherlands had a very high between-herd SBV-seroprevalence both in sheep and cattle in all regions studied, while in France (the study was conducted in winter 2011–2012) a great heterogeneity in seroprevalence between areas was observed. One French region was excluded as its ratio was greater than ten (i.e. the number of herds reported to DCF was higher than the one estimated by the seroprevalence study). In this region the number of herds tested was low (8), as well as the observed prevalence (0.125), however this observation demonstrates that these estimations must be treated with caution when applied to other areas of Europe as there could be considerable regional variation. Regional variation is likely to exist due to differences in density of susceptible hosts and vectors and suitability of climatic conditions for the vector. Results of our study showed that the large majority of the SBV cases reported are those resulting from the direct detection of SBV in malformed foetuses which are the most easily recognised clinical picture of the infection.



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The specific AHS malformations observed in foetuses as a result of SBV infection are probably linked to infection at particular times of the foetal development. Research with experimental SBV infection of pregnant dams is necessary to determine the susceptible periods of the gestation. For now, research conducted with Akabane virus and other orthobunyaviruses provide the best indication of the most likely vulnerable stage. In pregnant sheep, the gestational period for the occurrence of foetal abnormalities can vary from day 30 to day 36 or 50 for Akabane virus (Hashiguchi et al., 1979; Parsonson et al., 1977). In cattle, the neural and muscular lesions responsible for arthrogryposis are a consequence of infection between day 103 and day 174 of gestation while foetal infection between day 76 and 104 of gestation causes hydrancephaly (Kirkland et al., 1988). Infection occurring outside the relatively narrow risk period would not result in malformations but would induce a protective humoral immune response in the infected dam. Therefore, it is likely that AHS cases are not representative of rates of SBV infection. Testing proficiency could also affect the sensitivity of the surveillance system in place. The testing proficiency is dependent on the development of the infection in the susceptible species, the variability of the virus causing infection and ease of implementation in animal health laboratories. In the early stages of the outbreak, testing was mainly done by RT-qPCR using a test developed by FLI (Hoffmann et al., 2012). The test was made available to all laboratories upon request. The test performance is known to be influenced by other factors such as the tissue sampled (Bilk et al., 2012). Direct virus detection was a particular problem in AHS cases in calves indicating a possible virus clearance by the foetus (De Regge et al., 2012; Van Maanen et al., 2012). Only a small number of herds had reported acute cases in adults (6% for cattle, 1% for goats and 3% for sheep). The clinical signs in adult animals were described as transient and non-specific. Experimental infection studies (Hoffmann et al., 2012; Wernike et al., 2013) showed that clinical signs are not easy to reproduce in adults. Awareness and motivation to report are the two other factors that are likely to affect the surveillance sensitivity and these are even more difficult to quantify. Awareness of the clinical signs in foetuses was probably high between farmers and veterinarians during the first year of the outbreak, since several countries developed awareness campaigns and there was large media coverage of the event both in scientific and mass media. The motivation to report depends on many factors, such as direct impact of the disease, regulatory obligation, compensation schemes, consequences of infection such as direct losses from disease or indirect impact from trade restrictions (Elbers et al., 2010). SBV was never notifiable at EU level and only a limited number of countries made SBV a notifiable disease at national level (Table 2). In the course of the epidemic, SBV was considered endemic in most of the affected countries and the obligation to report the first detection of SBV to the OIE was no longer valid. The economic costs of laboratory confirmation of clinical suspects of SBV in a situation without obligatory notification are often paid by the animal owners and not the veterinary authorities. Since a presumptive diagnosis can be obtained only by the

observation of AHS cases there are probably an additional number of cases not confirmed neither reported. Only cases confirmed by direct detection methods were considered for the temporal analysis (Fig. 2) since serological detection provides no indication on the time of infection. Acute cases confirmed by direct detection in adult animals were observed throughout the reporting period in Germany, indicating virus circulation even during the winter period (EFSA, 2013). The demonstration of vector transmission during the winter period has significant implications for disease control. Measures such as those implemented for bluetongue virus control, where animal movement was allowed during the “vector free period”, would have had a reduced or even no effect on SBV spread. Most cases reported to DCF refer to SBV detection in AHS cases. Assuming for sheep and goats a gestation period of 150 days and the start of the vulnerable stage at day 30 and for cattle a gestation period of 280 days and the start of the vulnerable stage at day 90 (EFSA, 2012a), the infection of the pregnant dams would have occurred several months earlier, during the summer and autumn of 2011 and into 2012. It was during these periods that spread to new regions occurred. However, the pattern of case detection, particularly in sheep, may be a reflection of the lambing season in the countries most affected. Lambing season is in many countries, especially in the North of Europe, concentrated in spring, while cattle reproduction occurs throughout the year in most regions. Unfortunately, data to provide an accurate description of the reproductive patterns in cattle and sheep was not available. New infections were reported after the summer of 2012 till the end of April 2013 in newly affected countries, but also in previously affected countries such as France, Germany, Switzerland and the United Kingdom. No data was available to demonstrate if the same animal could be re-infected or to estimate the probability of detection of new cases in previously infected herds in comparison to naïve herds. This evidence is needed to demonstrate the assumption that SBV infection results in long term immunity and further studies should be carried out to investigate life-long immunity. In spite of the limitations already discussed, i.e. a passive surveillance system based on detection of clinical cases, the data collection at EU level supported an effective spatial and temporal analysis using the first report date of suspicion and regional identification of herd location. Collecting the data at this level of granularity ensured that the resulting dataset could be used during the early phase of the epidemic for predictive models of spread (EFSA, 2012; Wilson et al., in press) but also provided useful indications of the limits and speed of spread. Twenty-two countries reported SBV confirmed herds by spring 2013. The most westerly affected country was Ireland and the most easterly was Finland. Cases were also subsequently reported from Turkey (Yilmaz et al., 2014). In the North, confirmed herds occurred above a latitude of 60◦ North which exceeds the Northern expansion observed during the bluetongue virus serotype 8 epidemic in 2006–2009. Midges of the Obsoletus complex were found as far north as latitude 65◦ North (Ander et al., 2012) and could be responsible for the transmission of SBV.




The frequently observed distances below 200 km and the rarely observed larger distances suggest that there may have been different modes of spread for SBV in Europe. However, these distance estimates should be viewed with caution since they are based on between-centroid measurements. The extreme outliers, (1092 km to Etelä-Suomi in Finland, 868 km to Andalucia in Spain, 551 km to Veneto and 496 km to Sardinia in Italy) may be due to transported cases or failure to detect new infections in the intermediary regions. Similarly, the related Akabane virus, which belongs like SBV to the Simbu serogroup within the orthobunyaviridae, is also known for its fast spread in susceptible populations (St George and Kirkland, 2004). It is clear that the spread distance in the first 12 weeks decreases over time, which could be attributed to awareness, efforts taken to follow closely the epidemic as well as a large number of susceptible animals. On the other hand the later period seems to illustrate a relaxation on surveillance activities, considering the limited impact of the disease or a potential reduction on susceptible animals in the population. When comparing the estimates of distance (Fig. 4) with the cases per week of reporting (Fig. 2, it is interesting to note that spread into new areas occurred most frequently in two specific periods i.e. December 2011–March 2012 and August 2012–January 2013, although new cases were confirmed throughout 2012. These two periods of malformations in newborns occurring in new areas, adjusted for the gestation period in ruminants, correspond with the summer of 2011 and 2012 when vector activity is expected to be at its highest. During the BTV-8 epidemic in 2006–2007 higher number of outbreaks were also observed during and shortly after the vector season (EFSA, 2011). However, it is clear that the second wave of the SBV epidemic (August 2012–January 2013) is much lower compared with the second peak of BTV-8 in 2007. This indicates that the load of the SBV virus may have been different in the vectors or the virus is cleared by the host due to acquired immunity. Furthermore, the prevalence of SBV-infected vectors was significantly lower in 2012 compared to 2011 in the Netherlands, which is most probably due to reduced circulation of the virus (Elbers et al., 2013). Using NUTS classification for spatial location has the advantage of using a standardised system and the capacity to integrate information from other data collections, e.g. agricultural data from EUROSTAT. However, since the classification was designed for the application of regional policies, it is based on human population distribution and does not necessarily reflect farm animal density. The lack of standard geographical classification for reporting animal diseases makes integration of data from different animal health databases complex, constituting a barrier for epidemiological investigations of transboundary disease such as the SBV epidemic as well as assessments of possible control measures. A common spatial location system that is suitable for epidemiological investigations of transboundary diseases should be agreed upon. An important objective of the study was to provide an assessment of the impact of SBV on animal health. Consequence assessment is a part of the OIE risk assessment framework and it is essential for risk estimation

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and decision making for disease management. The impact assessment is generally based on direct consequences on public health or animal health but also indirect consequences to the environment, trade losses or costs related to the surveillance and control of the infectious disease. A preliminary assessment of the risk to public health was done by the European Centre for Disease Prevention and Control (ECDC) in December 2011 estimating a negligible risk of SBV to public health (ECDC, 2011). The initial assessment was further confirmed by results from a survey in the Netherlands and Germany (Reusken et al., 2012; Ducomble et al., 2012). The question was then to assess the infection impact on production animals. No mortality of adult cattle, sheep or goats was associated with SBV infection. Morbidity as a consequence of infection was characterized by mild transitory clinical signs such as fever and diarrhoea and loss of milk production. The data reported to DCF did not allow for an assessment of the disease impact in adult animals. Veldhuis et al. (in press) concluded that SBV had a limited within-herd impact on milk production and reproductive performance in dairy cattle in the Netherlands and the German district of Kleve, and a negligible effect on mortality. AHS cases were the most frequent reason for laboratory investigation of SBV infection. The AHS incidence in the various affected countries during the whole reporting period (August 2011 to 30 April 2013) ranged between 1–4% and 3–7% for respectively cattle and sheep herds. Seventy-five percent of the herds were affected. Only a small proportion of the reported herds had more than one case of AHS confirmed (0.34% for cattle and 5.15% for sheep) and in most countries no follow up was made to herds already confirmed by a previous case. It is likely that the between-herd impact is higher than the estimates of this study. Insufficient data were available to estimate within-herd impact. In order to further estimate the impact of SBV, data regarding the number of AHS cases, cases in adult animals, abortions, live births, pregnant animals, dystocia, stillbirths, return to service and fertility per herd during the reporting period would be required. Furthermore, data regarding domestic ruminants were outdated (last statistics available were from 2007) and information such as the number of animals, the number of female animals, the number of births and annual replacement rates per herd were missing. However, preliminary data of within-herd impact are available for France in bovine herds and sheep flocks (Dominguez et al., 2012). However, it is likely that more than one case per herd has occurred especially in the first year of virus circulation and in sheep flocks where gestation periods are synchronised. The results of the reporting officer’s survey on surveillance activities confirm that the herd of origin of a confirmed animal/foetus case was investigated in only a limited number of countries and no follow up was made to herds already confirmed by a previous case. AHS case intensity can only be considered as an indication of the overall impact of infection. Most likely the lower bound of the impact and the between-herd impact is higher than the estimates of this study.




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5. Conclusions The work developed by EFSA and experts of the member states of the European Union on the development of uniform case definitions and protocols for data submission demonstrated the possibilities of international collaboration in the investigation of an emerging disease. The collated data allowed for the assessment of the spread of SBV in Europe both temporally and spatially at an appropriate granularity to support decision makers. Information on the results of the laboratory testing could be reported by all countries but information on herd size, birth outcomes and clinical cases was lacking. Surveillance activities and databases on animal diseases are structured generally for case detection, making the estimation of infection/disease prevalence and the investigation of disease risk factors difficult. It is essential in emerging disease outbreaks that the disease impact is estimated to allow risk managers to take appropriate action (e.g. mandatory surveillance and notification or implementation of control measures). The lack of ‘ready to use’ data with relation to the number of animals per herd (herd size), the annual replacement rates and baseline incidence estimates of abortions and malformations limited this estimation of risk and impact of SBV. Therefore, it is recommended to define a priori simple within-herd impact indicators suitable for emerging disease outbreaks in order to be measured as part of routine animal health surveillance programmes and to allow for rapid and reliable impact assessment of emerging animal diseases at European level. Conflict of interest None declared. Acknowledgments The authors would like to acknowledge all reporting officers that have submitted data on SBV occurrence in European countries, the EFSA Animal Health and Welfare Network on the Ad-hoc working group on Schmallenberg virus experts and EFSA scientific staff. References Ander, M., Meiswinkel, R., Chirico, J., 2012. Seasonal dynamics of biting midges (Diptera: Ceratopogonidae: Culicoides), the potential vectors of bluetongue virus, in Sweden. Veterinary Parasitology 184, 59–66. Bilk, S., Schulze, C., Fischer, M., Beer, M., Hlinak, A., Hoffmann, B., 2012. Organ distribution of Schmallenberg virus RNA in malformed newborns. Veterinary Microbiology 159, 236–238. Cay, A.B., Regge, N., Riocreux, F., Meroc, E., Stede, Y., Loo, H., Bertels, G., Saulmont, M., Delooz, L., Deblauwe, I., Vantieghem, P., Hooyberghs, J., Berg, T., 2011. Schmallenberg virus in Belgium: first diagnosis and initial assessments. Le Nouveau Praticien Veterinaire Elevages et Sante, 29–34. Cleveland, W.S., Devlin, S.J., 1988. Locally weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association 83, 596–610. Cleveland, W.S., Grosse, E., Shyu, W.M., 1993. Local regression models. In: Chambers, J.M., Hastie, T.J. (Eds.), Statistical Models in S. Chapman and Hall, London.

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Post-epidemic Schmallenberg virus circulation: parallel bovine serological and Culicoides virological surveillance studies in Ireland.

Schmallenberg Virus Recurrence, Germany, 2014.

EFSA assesses current knowledge of Schmallenberg virus.

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Evidence of excretion of Schmallenberg virus in bull semen.

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Generation of recombinant Schmallenberg virus nucleocapsid protein in yeast and development of virus-specific monoclonal antibodies.

Schmallenberg virus: could wildlife reservoirs threaten domestic livestock?

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[Alert - epidemic due to the Ebola virus].