Modelling local dispersal of bluetongue virus serotype 8 using random walk

An Agent-Based Model of Biting Midge Dynamics to Understand Bluetongue Outbreaks

Bluetongue (BT) is a well-known vector-borne disease that infects ruminants such as sheep, cattle, and deer with high mortality rates. Recent outbreaks in Europe highlight the importance of understanding vector-host dynamics and potential courses of action to mitigate the damage that can be done by BT. We present an agent-based model, entitled 'MidgePy', that focuses on the movement of individual Culicoides spp. biting midges and their interactions with ruminants to understand their role as vectors in BT outbreaks, especially in regions that do not regularly experience outbreaks. The results of our sensitivity analysis suggest that midge survival rate has a significant impact on the probability of a BTV outbreak as well as its severity. Using midge flight activity as a proxy for temperature, we found that an increase in environmental temperature corresponded with an increased probability of outbreak after identifying parameter regions where outbreaks are more likely to occur. This suggests that future methods to control BT spread could combine large-scale vaccination programs with biting midge population control measures such as the use of pesticides. Spatial heterogeneity in the environment is also explored to give insight on optimal farm layouts to reduce the potential for BT outbreaks.

Monitoring and Surveillance of Small Ruminant Health in The Netherlands

In contemporary society and modern livestock farming, a monitoring and surveillance system for animal health has become indispensable. In addition to obligations arising from European regulations regarding monitoring and surveillance of animal diseases, The Netherlands developed a voluntary system for the monitoring and surveillance of small ruminant health. This system aims for (1) early detection of outbreaks of designated animal diseases, (2) early detection of yet unknown disease conditions, and (3) insight into trends and developments. To meet these objectives, a system is in place based on four main surveillance components, namely a consultancy helpdesk, diagnostic services, multiple networks, and an annual data analysis. This paper describes the current system and its ongoing development and gives an impression of nearly twenty years of performance by providing a general overview of key findings and three elaborated examples of notable disease outbreaks. Results indicate that the current system has added value to the detection of various (re)emerging and new diseases. Nevertheless, animal health monitoring and surveillance require a flexible approach that is able to keep pace with changes and developments within the industry. Therefore, monitoring and surveillance systems should be continuously adapted and improved using new techniques and insights.

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): bluetongue

A specific concept of strain was developed in order to classify the BTV serotypes ever reported in Europe based on their properties of animal health impact: the genotype, morbidity, mortality, speed of spread, period and geographical area of occurrence were considered as classification parameters. According to this methodology the strain groups identified were (i) the BTV strains belonging to serotypes BTV-1-24, (ii) some strains of serotypes BTV-16 and (iii) small ruminant-adapted strains belonging to serotypes BTV-25, -27, -30. Those strain groups were assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7, Article 5 on the eligibility of bluetongue to be listed, Article 9 for the categorisation according to disease prevention and control rules as in Annex IV and Article 8 on the list of animal species related to bluetongue. The assessment has been performed following a methodology composed of information collection, expert judgement at individual and collective level. The output is composed of the categorical answer, and for the questions where no consensus was reached, the different supporting views are reported. The strain group BTV (1-24) can be considered eligible to be listed for Union intervention as laid down in Article 5(3) of the AHL, while the strain group BTV-25-30 and BTV-16 cannot. The strain group BTV-1-24 meets the criteria as in Sections 2 and 5 of Annex IV of the AHL, for the application of the disease prevention and control rules referred to in points (b) and (e) of Article 9(1) of the AHL. The animal species that can be considered to be listed for BTV-1-24 according to Article 8(3) are several species of Bovidae, Cervidae and Camelidae as susceptible species; domestic cattle, sheep and red deer as reservoir hosts, midges insect of genus Culicoides spp. as vector species.

Spatial epidemiological analysis of bovine encephalomyelitis outbreaks caused by Akabane virus infection in western Japan in 2011

Akabane disease, which is distributed in temperate and tropical regions in the world, is a vector-borne disease of ruminants caused by the Akabane virus, transmitted by Culicoides biting midges. In 2011, outbreaks of Akabane viral encephalomyelitis occurred in the Shimane Prefecture in western Japan. In this study, a spatial epidemiological analysis was conducted to understand environmental factors associated with the spread of Akabane disease. By applying a conditional autoregressive model, the relationship between infection and environmental variables was explored. The results showed that the dominance of farmlands and the presence of infected farms within a 3-km radius had a significant effect on infection. This result implies that land use, which would relate with the vector habitat, and the presence of neighboring infected farms as a source of infection may have influenced the spread of the disease in this region. These findings provide basic insights into the spread of Akabane disease and useful suggestions for developing a surveillance program and preventive measures against the disease.

Characteristics of Wind-Infective Farms of the 2006 Bluetongue Serotype 8 Epidemic in Northern Europe

Bluetongue is a Culicoides-borne viral disease of livestock. In 2006, northern Europe experienced a major outbreak of this disease with devastating effects on the livestock industry. The outbreak quickly spread over the region, primarily affecting cattle and sheep. A previous analysis of the role of vector flight and wind in the spread of this virus across northern Europe indicated that infection at 1,326 (65%) of the reported infected farms could be traced back to just 599 (29%) farms (wind-infective farms). Rather than focusing on presence or absence of vectors or difference between infected and non-infected farms, we investigate the zoological and environmental characteristics of these 599 wind-infective farms (which can be thought of as super-spreaders) in order to characterize what makes them distinct from non-infective farms. Differences in temperature, precipitation, and the density of sheep at individual farms were identified between these two groups. These environmental and zoological factors are known to affect vector abundance and may have promoted bluetongue virus transmission. Identifying such ecological differences can help in the description and quantification of relative risk in affected areas.

Modelling the dynamics of bluetongue disease and the effect of seasonality

We present mathematical models for the midge-borne disease bluetongue, with cattle and sheep as hosts. The models take the form of delay differential equations and incorporate the incubation time of bluetongue in cattle, sheep and midges, and also the larval developmental time of midges. Recovery in cattle and sheep is also included. Both an autonomous and a periodic model are considered, to take account of seasonality. For both models we present conditions for the disease-free state to be linearly stable, and a detailed interpretation of those conditions. The results of simulations are also presented. Important findings include the need for prompt diagnosis of latent infection and appropriate action before the animal turns infectious, and the need for measures that reduce insect bites.

Serosurveillance of Schmallenberg virus in Switzerland using bulk tank milk samples

Infections with Schmallenberg virus (SBV), a novel Orthobunyavirus transmitted by biting midges, can cause abortions and malformations of newborns and severe symptoms in adults of domestic and wild ruminants. Understanding the temporal and spatial distribution of the virus in a certain territory is important for the control and prevention of the disease. In this study, seroprevalence of antibodies against SBV and the spatial spread of the virus was investigated in Swiss dairy cattle applying a milk serology technique on bulk milk samples. The seroprevalence in cattle herds was significantly higher in December 2012 (99.5%) compared to July 2012 (19.7%). This high between-herd seroprevalence in cattle herds was observed shortly after the first detection of viral infections. Milk samples originating from farms with seropositive animals taken in December 2012 (n=209; mean 160%) revealed significantly higher S/P% ratios than samples collected in July 2012 (n=48; mean 103.6%). This finding suggests a high within-herd seroprevalence in infected herds which makes testing of bulk tank milk samples for the identification farms with past exposures to SBV a sensitive method. It suggests also that within-herd transmission followed by seroconversion still occurred between July and December. In July 2012, positive bulk tank milk samples were mainly restricted to the western part of Switzerland whereas in December 2012, all samples except one were positive. A spatial analysis revealed a separation of regions with and without positive farms in July 2012 and no spatial clustering within the regions with positive farms. In contrast to the spatial dispersion of bluetongue virus, a virus that is also transmitted by Culicoides midges, in 2008 in Switzerland, the spread of SBV occurred from the western to the eastern part of the country. The dispersed incursion of SBV took place in the western part of Switzerland and the virus spread rapidly to the remaining territory. This spatial pattern is consistent with the hypothesis that transmission by Culicoides midges was the main way of spreading.

The Mondrian matrix: Culicoides biting midge abundance and seasonal incidence during the 2006-2008 epidemic of bluetongue in the Netherlands

During the northern Europe epidemic of bluetongue (BT), Onderstepoort-type blacklight traps were used to capture Culicoides Latreille (Diptera: Ceratopogonidae) biting midges weekly between November 2006 and December 2008 on 21 livestock farms in the Netherlands. Proven and potential vectors for the bluetongue virus (BTV) comprised almost 80% of the midges collected: the Obsoletus complex, constituting C. obsoletus (Meigen) and C. scoticus Downes & Kettle (44.2%), C. dewulfi Goetghebuer (16.4%), C. chiopterus (Meigen) (16.3%) and C. pulicaris (Linnaeus) (0.1%). Half of the 24 commonest species of Culicoides captured completed only one (univoltine) or two (bivoltine) generations annually, whereas multivoltine species (including all BTV vectors) cycled through five to six generations (exceeding the one to four generations calculated in earlier decades). Whether this increment signals a change in the phenology of northern Europe Culicoides or simply is an adaptive response that manifests during warmer episodes, thus heightening periodically the incursive potential of midge-borne arboviruses, remains to be clarified. Culicoides duddingstoni Kettle & Lawson, C. grisescens Edwards, C. maritimus Kieffer, C. pallidicornis Kieffer and C. riethi Kieffer are new records for the biting midge fauna of the Netherlands. It is suggested that C. punctatus (Meigen) be added to the European list of vector Culicoides.

Evaluation of a continuous indicator for syndromic surveillance through simulation. application to vector borne disease emergence detection in cattle using milk yield

Two vector borne diseases, caused by the Bluetongue and Schmallenberg viruses respectively, have emerged in the European ruminant populations since 2006. Several diseases are transmitted by the same vectors and could emerge in the future. Syndromic surveillance, which consists in the routine monitoring of indicators for the detection of adverse health events, may allow an early detection. Milk yield is routinely measured in a large proportion of dairy herds and could be incorporated as an indicator in a surveillance system. However, few studies have evaluated continuous indicators for syndromic surveillance. The aim of this study was to develop a framework for the quantification of both disease characteristics and model predictive abilities that are important for a continuous indicator to be sensitive, timely and specific for the detection of a vector-borne disease emergence. Emergences with a range of spread characteristics and effects on milk production were simulated. Milk yields collected monthly in 48 713 French dairy herds were used to simulate 576 disease emergence scenarios. First, the effect of disease characteristics on the sensitivity and timeliness of detection were assessed: Spatio-temporal clusters of low milk production were detected with a scan statistic using the difference between observed and simulated milk yields as input. In a second step, the system specificity was evaluated by running the scan statistic on the difference between observed and predicted milk yields, in the absence of simulated emergence. The timeliness of detection depended mostly on how easily the disease spread between and within herds. The time and location of the emergence or adding random noise to the simulated effects had a limited impact on the timeliness of detection. The main limitation of the system was the low specificity i.e. the high number of clusters detected from the difference between observed and predicted productions, in the absence of disease.

Quantifying dispersal of european culicoides (Diptera: Ceratopogonidae) vectors between farms using a novel mark-release-recapture technique

Studying the dispersal of small flying insects such as Culicoides constitutes a great challenge due to huge population sizes and lack of a method to efficiently mark and objectively detect many specimens at a time. We here describe a novel mark-release-recapture method for Culicoides in the field using fluorescein isothiocyanate (FITC) as marking agent without anaesthesia. Using a plate scanner, this detection technique can be used to analyse thousands of individual Culicoides specimens per day at a reasonable cost. We marked and released an estimated 853 specimens of the Pulicaris group and 607 specimens of the Obsoletus group on a cattle farm in Denmark. An estimated 9,090 (8,918-9,260) Obsoletus group specimens and 14,272 (14,194-14,448) Pulicaris group specimens were captured in the surroundings and subsequently analysed. Two (0.3%) Obsoletus group specimens and 28 (4.6%) Pulicaris group specimens were recaptured. The two recaptured Obsoletus group specimens were caught at the release point on the night following release. Eight (29%) of the recaptured Pulicaris group specimens were caught at a pig farm 1,750 m upwind from the release point. Five of these were recaptured on the night following release and the three other were recaptured on the second night after release. This is the first time that movement of Culicoides vectors between farms in Europe has been directly quantified. The findings suggest an extensive and rapid exchange of disease vectors between farms. Rapid movement of vectors between neighboring farms may explain the the high rate of spatial spread of Schmallenberg and bluetongue virus (BTV) in northern Europe.

Assessment of the risk of a bluetongue outbreak in Europe caused by Culicoides midges introduced through intracontinental transport and trade networks

The importation of infected hosts and the arrival of windborne infected Culicoides (Diptera: Ceratopogonidae) were considered unlikely mechanisms for bluetongue virus (BTV) incursion into a BTV-free area during the recent BTV serotype 8 (BTV-8) epidemic in northern Europe. Therefore, alternative mechanisms need to be considered. Air, sea and land transport networks continue to expand, and an important consequence of this is vector-borne pathogen importation. One important aspect of bluetongue (BT) epidemiology not yet addressed is the potential movement of infected Culicoides via transport and trade networks. Therefore, a risk assessment model was constructed to assess the probability of a BTV outbreak as a consequence of the introduction of Culicoides via these networks. The model was applied to calculate the risk for a BTV-8 epidemic in Spain in 2007 caused by the introduction of Culicoides from affected northern European countries. The mean weighted annual risk for an outbreak caused by transportation of a single vector from an affected northern European country varied from 1.8 × 10(-7) to 3.0 × 10(-13), with the highest risks associated with Culicoides imported from Belgium, the Netherlands, Germany and France. For this mechanism to pose a significant risk to BTV-free countries, a large number of vectors would have to be transported.

Factors affecting Bluetongue serotype 8 spread in Northern Europe in 2006: the geographical epidemiology

In 2006, Bluetongue serotype 8 was notified for the first time in north-western Europe, more specifically in Belgium, the Netherlands, Luxemburg, Germany and France. The disease spread very rapidly, affecting mainly cattle and sheep farms. In this paper, we examined risk factors affecting the spatial incidence of reported Bluetongue events during the first outbreak in 2006. Previous studies suggested that the Bluetongue incidence was enhanced by environmental factors, such as temperature and wind speed and direction, as well as by human interventions, such as the transport of animals. In contrast to the previous studies, which were based on univariable analyses, a multivariable epidemiological analysis describing the spatial relationship between Bluetongue incidence and possible risk factors is proposed in this paper. This disentangles the complex interplay between different risk factors. Our model shows that wind is the most important factor affecting the incidence of the disease. In addition, areas with high precipitation are slightly more sensitive to the spread of the infection via the wind. Another important risk factor is the land cover; high-risk areas for infection being characterized by a fragmentation of the land cover, especially the combination of forests and urban areas. Precipitation and temperature are also significant risk factors. High precipitation in areas with a large coverage of forests and/or pasture increases the risk whereas high temperature increases the risk considerably in municipalities covered mainly with pasture. Local spread via the vector is strongest in areas with a large coverage of forests and smallest in highly urbanized areas. Finally, the transport of animals from infected areas is a risk factor.

Statistical models for spatially explicit biological data

Existing algorithms for predicting species' distributions sit on a continuum between purely statistical and purely biological approaches. Most of the existing algorithms are aspatial because they do not consider the spatial context, the occurrence of the species or conditions conducive to the species' existence, in neighbouring areas. The geostatistical techniques of kriging and cokriging are presented in an attempt to encourage biologists more frequently to consider them. Unlike deterministic spatial techniques they provide estimates of prediction errors. The assumptions and applications of common geostatistical techniques are presented with worked examples drawn from a dataset of the bluetongue outbreak in northwest Europe in 2006. Emphasis is placed on the importance and interpretation of weights in geostatistical calculations. Covarying environmental data may be used to improve predictions of species' distributions, but only if their sampling frequency is greater than that of the species' or disease data. Cokriging techniques are unable to determine the biological significance or importance of such environmental data, because they are not designed to do so.

Why did bluetongue spread the way it did? Environmental factors influencing the velocity of bluetongue virus serotype 8 epizootic wave in France

Understanding where and how fast an infectious disease will spread during an epidemic is critical for its control. However, the task is a challenging one as numerous factors may interact and drive the spread of a disease, specifically when vector-borne diseases are involved. We advocate the use of simultaneous autoregressive models to identify environmental features that significantly impact the velocity of disease spread. We illustrate this approach by exploring several environmental factors influencing the velocity of bluetongue (BT) spread in France during the 2007–2008 epizootic wave to determine which ones were the most important drivers. We used velocities of BT spread estimated in 4,495 municipalities and tested sixteen covariates defining five thematic groups of related variables: elevation, meteorological-related variables, landscape-related variables, host availability, and vaccination. We found that ecological factors associated with vector abundance and activity (elevation and meteorological-related variables), as well as with host availability, were important drivers of the spread of the disease. Specifically, the disease spread more slowly in areas with high elevation and when heavy rainfall associated with extreme temperature events occurred one or two months prior to the first clinical case. Moreover, the density of dairy cattle was correlated negatively with the velocity of BT spread. These findings add substantially to our understanding of BT spread in a temperate climate. Finally, the approach presented in this paper can be used with other infectious diseases, and provides a powerful tool to identify environmental features driving the velocity of disease spread.

Modelling bluetongue virus transmission between farms using animal and vector movements

Bluetongue is a notifiable disease of ruminants which, in 2007, occurred for the first time in England. We present the first model for bluetongue that explicitly incorporates farm to farm movements of the two main hosts, as well as vector dispersal. The model also includes a seasonal vector to host ratio and dynamic restriction zones that evolve as infection is detected. Batch movements of sheep were included by modelling degree of mixing at markets. We investigate the transmission of bluetongue virus between farms in eastern England (the focus of the outbreak). Results indicate that most parameters affecting outbreak size relate to vectors and that the infection generally cannot be maintained without between-herd vector transmission. Movement restrictions are effective at reducing outbreak size, and a targeted approach would be as effective as a total movement ban. The model framework is flexible and can be adapted to other vector-borne diseases of livestock.

A new algorithm quantifies the roles of wind and midge flight activity in the bluetongue epizootic in northwest Europe

The 2006 bluetongue (BT) outbreak in northwestern Europe had devastating effects on cattle and sheep in that intensively farmed area. The role of wind in disease spread, through its effect on Culicoides dispersal, is still uncertain, and remains unquantified. We examine here the relationship between farm-level infection dates and wind speed and direction within the framework of a novel model involving both mechanistic and stochastic steps. We consider wind as both a carrier of host semio-chemicals, to which midges might respond by upwind flight, and as a transporter of the midges themselves, in a more or less downwind direction. For completeness, we also consider midge movement independent of wind and various combinations of upwind, downwind and random movements. Using stochastic simulation, we are able to explain infection onset at 94 per cent of the 2025 affected farms. We conclude that 54 per cent of outbreaks occurred through (presumably midge) movement of infections over distances of no more than 5 km, 92 per cent over distances of no more than 31 km and only 2 per cent over any greater distances. The modal value for all infections combined is less than 1 km. Our analysis suggests that previous claims for a higher frequency of long-distance infections are unfounded. We suggest that many apparent long-distance infections resulted from sequences of shorter-range infections; a 'stepping stone' effect. Our analysis also found that downwind movement (the only sort so far considered in explanations of BT epidemics) is responsible for only 39 per cent of all infections, and highlights the effective contribution to disease spread of upwind midge movement, which accounted for 38 per cent of all infections. The importance of midge flight speed is also investigated. Within the same model framework, lower midge active flight speed (of 0.13 rather than 0.5 m s(-1)) reduced virtually to zero the role of upwind movement, mainly because modelled wind speeds in the area concerned were usually greater than such flight speed. Our analysis, therefore, highlights the need to improve our knowledge of midge flight speed in field situations, which is still very poorly understood. Finally, the model returned an intrinsic incubation period of 8 days, in accordance with the values reported in the literature. We argue that better understanding of the movement of infected insect vectors is an important ingredient in the management of future outbreaks of BT in Europe, and other devastating vector-borne diseases elsewhere.

Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue

Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SAR_err model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SAR_err model, which led to a trend SAR_err model. Overall, BT spread from north-eastern to south-western France. The average trend SAR_err-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SAR_err-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SAR_err models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases.

Quantitative analysis of transmission parameters for bluetongue virus serotype 8 in Western Europe in 2006

The recent bluetongue virus serotype 8 (BTV-8) epidemic in Western Europe struck hard. Controlling the infection was difficult and a good and safe vaccine was not available until the spring of 2008. Little was known regarding BTV transmission in Western Europe or the efficacy of control measures. Quantitative details on transmission are essential to assess the potential and efficacy of such measures.

To quantify virus transmission between herds, a temporal and a spatio-temporal analysis were applied to data on reported infected herds in 2006. We calculated the basic reproduction number between herds (R_h: expected number of new infections, generated by one initial infected herd in a susceptible environment). It was found to be of the same order of magnitude as that of an infection with Foot and Mouth Disease (FMD) in The Netherlands, e.g. around 4. We concluded that an average day temperature of at least 15°C is required for BTV-8 transmission between herds in Western Europe. A few degrees increase in temperature is found to lead to a major increase in BTV-8 transmission.

We also found that the applied disease control (spatial zones based on 20 km radius restricting animal transport to outside regions) led to a spatial transmission pattern of BTV-8, with 85% of transmission restricted to a 20 km range. This 20 km equals the scale of the protection zones. We concluded that free animal movement led to substantial faster spread of the BTV-8 epidemic over space as compared to a situation with animal movement restrictions.

The shape of the spatial kernel and its implications for biological invasions in patchy environments

Ecological and epidemiological invasions occur in a spatial context. We investigated how these processes correlate to the distance dependence of spread or dispersal between spatial entities such as habitat patches or epidemiological units. Distance dependence is described by a spatial kernel, characterized by its shape (kurtosis) and width (variance). We also developed a novel method to analyse and generate point-pattern landscapes based on spectral representation. This involves two measures: continuity, which is related to autocorrelation and contrast, which refers to variation in patch density. We also analysed some empirical data where our results are expected to have implications, namely distributions of trees (Quercus and Ulmus) and farms in Sweden. Through a simulation study, we found that kernel shape was not important for predicting the invasion speed in randomly distributed patches. However, the shape may be essential when the distribution of patches deviates from randomness, particularly when the contrast is high. We conclude that the speed of invasions depends on the spatial context and the effect of the spatial kernel is intertwined with the spatial structure. This implies substantial demands on the empirical data, because it requires knowledge of shape and width of the spatial kernel, and spatial structure.

The most likely time and place of introduction of BTV8 into Belgian ruminants

BACKGROUND

In northern Europe, bluetongue (BT) caused by the BT virus (BTV), serotype 8, was first notified in August 2006 and numerous ruminant herds were affected in 2007 and 2008. However, the origin and the time and place of the original introduction have not yet been determined.

METHODS AND PRINCIPAL FINDINGS

Four retrospective epidemiological surveys have been performed to enable determination of the initial spatiotemporal occurrence of this emerging disease in southern Belgium: investigations of the first recorded outbreaks near to the disease epicenter; a large anonymous, random postal survey of cattle herds and sheep flocks; a random historical milk tank survey of samples tested with an indirect ELISA and a follow-up survey of non-specific health indicators. The original introduction of BTV into the region probably occurred during spring 2006 near to the National Park of Hautes Fagnes and Eifel when Culicoides become active.

CONCLUSIONS/SIGNIFICANCE

The determination of the most likely time and place of introduction of BTV8 into a country is of paramount importance to enhance awareness and understanding and, to improve modeling of vector-borne emerging infectious diseases.

A modeling framework to describe the transmission of bluetongue virus within and between farms in Great Britain

BACKGROUND

Recently much attention has been given to developing national-scale micro-simulation models for livestock diseases that can be used to predict spread and assess the impact of control measures. The focus of these models has been on directly transmitted infections with little attention given to vector-borne diseases such as bluetongue, a viral disease of ruminants transmitted by Culicoides biting midges. Yet BT has emerged over the past decade as one of the most important diseases of livestock.

METHODOLOGY/PRINCIPAL FINDINGS

We developed a stochastic, spatially-explicit, farm-level model to describe the spread of bluetongue virus (BTV) within and between farms. Transmission between farms was modeled by a generic kernel, which includes both animal and vector movements. Once a farm acquired infection, the within-farm dynamics were simulated based on the number of cattle and sheep kept on the farm and on local temperatures. Parameter estimates were derived from the published literature and using data from the outbreak of bluetongue in northern Europe in 2006. The model was validated using data on the spread of BTV in Great Britain during 2007. The sensitivity of model predictions to the shape of the transmission kernel was assessed.

CONCLUSIONS/SIGNIFICANCE

The model is able to replicate the dynamics of BTV in Great Britain. Although uncertainty remains over the precise shape of the transmission kernel and certain aspects of the vector, the modeling approach we develop constitutes an ideal framework in which to incorporate these aspects as more and better data become available. Moreover, the model provides a tool with which to examine scenarios for the spread and control of BTV in Great Britain.

Endophily in Culicoides associated with BTV-infected cattle in the province of Limburg, south-eastern Netherlands, 2006

Culicoides were captured at a BTV-infected dairy near Gulpen in the province of Limburg (south-east Netherlands) between 14 September and 4 October 2006. Onderstepoort-type blacklight traps were used to sample Culicoides both inside and outside a partially open shed housing 11 cattle. A total of 28 light trap collections were made at the shed and yielded: 9371 Culicoides representing 11 species; >90% comprised five potential vectors of BTV and in order of abundance were Culicoides obsoletus and Culicoides scoticus (of the Obsoletus Complex), Culicoides dewulfi, Culicoides pulicaris and Culicoides chiopterus; Culicoides imicola, the principal Mediterranean (and African) vector of BTV, was absent. 2339 Culicoides representing seven species were captured inside (endophily) the cattle shed; >95% comprised the Obsoletus Complex and C. dewulfi. Conversely, the Pulicaris Complex, represented by five species and including C. pulicaris, showed strong exophily with >97% captured outside the shed. 7032 Culicoides were captured outside the shed, approximately threefold more than inside. This trend was reversed on an overcast day, when eightfold more Culicoides were captured inside; this indicates that when the light intensity outdoors is low Culicoides will attack (i) earlier in the day while cattle are still at pasture, and (ii) might follow cattle into the sheds in the late afternoon leading to elevated numbers of biting midges being trapped inside the shed during the subsequent hours of darkness. Culicoides were captured inside the shed on all 14 sampling nights. On occasion up to 33% were freshly blood fed indicating they had avidly attacked the cattle inside (endophagy); because half the cattle had seroconverted to BTV, and because no cattle were left outdoors at night, the data indicate that (i) the housing of animals in partially open buildings does not interrupt the transmission of BTV, and/or (ii) BTV is being transmitted while cattle are grazing outdoors during the day. The capture of partially engorged midges inside the shed shows they are being disturbed while feeding; this may lead to cattle being attacked repeatedly, and if these attacks include older parous BTV-infected Culicoides, may enhance virus dissemination (particularly in sheds where cattle stand close together). Endo- and exophagy by potential vector Culicoides--coupled to increased adult longevity and multiple feeding events in single (potentially) infected midges--would ensure an R0 of >1, resulting in the continued maintenance and spread of BTV within local vertebrate populations. Four light trap collections made additionally in a mature deciduous forest 70 m from the shed yielded a high proportion (48%) of gravid females amongst which 10% had incompletely digested blackened blood meals in their abdomens; the absence of this age category in Culicoides captured at the sheds indicates that all Culicoides, after engorgement, exit the buildings to undergo oogenesis elsewhere. In Europe, the blacklight trap is used widely for the nocturnal monitoring of Culicoides; a drawback to this approach is that this trap cannot be used to sample midges that are active during the day. Because diurnal biting in vector Culicoides may constitute a significant and underestimated component of BTV transmission a novel capture methodology will be required in future and is discussed briefly.