Introduction

Amongst the numerous diseases of ruminants, bluetongue (BT) has gained considerable importance in recent years as one of the best examples of the effects of climate change on disease spread [1], [2], [3], [4]. As an arbovirus, bluetongue virus (BTV), the aetiological agent of BT, depends almost entirely on the presence of competent Culicoides biting midges to be transmitted to the local host population. Currently, 24 serotypes of BTV have been identified worldwide, with most infected countries confronted with the challenge of dealing with multiple serotypes circulating in their ruminant populations [5]. The global range of BTV has historically been assumed to be restricted by regional differences in vector competence amongst Culicoides species as well as by the temperature requirements of the virus for replication. In recent years, however, the emergence and rapid spread of previously unreported serotypes (and strains) has occurred in a number of regions globally, including Europe and North America [5], [4].

Between 1998 and 2006, several BTV serotypes made incursions into Europe, but their distribution was limited to the Mediterranean Basin where the main Afro-Asiatic vector, Culicoides imicola, was present [3]. Limited evidence indicated that northern European Culicoides species could also potentially transmit the virus [6], but the risk of BT for the northern parts of Europe was considered minimal [7]. Indeed, before 2006, no case of BT had ever been reported above 50°N [1], [2]. It was therefore unexpected, when, in August 2006, the first cases of BTV serotype 8 (BTV-8) were recorded near Maastricht in the Netherlands (over 900km further north than ever before), with subsequent cases reported in Belgium, Germany, France and Luxembourg [8], [9]. By mid-January 2007, approximately 2,000 holdings had been affected. In May 2007, BTV-8 re-emerged and caused major outbreaks across the previously-affected countries, and spread into new areas of northern mainland Europe. The number of BT cases recorded in 2007 reached tens of thousands of affected farms in some countries [9]. The first case of BTV-8 in Great Britain (GB) was reported at Baylham Farm, near Ipswich on 22 September 2007 and, by the end of the year, a total of 67 affected holdings had been identified, although pre-movement testing later increased the number of known affected holdings to 125 by early 2008 [10].

A voluntary vaccination programme was launched in GB in May 2008, making use of an inactivated vaccine against BTV-8 which had only just become available. In contrast with other European countries, GB reported no cases of transmission of BTV-8 within its borders in 2008. It is essential to investigate why this was the case and, in particular, to identify key factors influencing the apparent success of vaccination in order to assess the risk from future reintroductions if, for instance, the level of vaccine uptake declines or if temperatures are warmer during the period of potential BTV transmission. To address these questions we use a stochastic, spatially-explicit model to describe the spread of BTV within and between farms in GB, which incorporates the effects of temperature on infection dynamics and also integrates the currently available data on BTV epidemiology [11].

Methods

Vaccination

Vaccination was assumed to act by reducing the probability of transmission from vector to host (b; i.e. it reduces the probability that an animal acquires infection) and from host to vector (β; to reflect lower virus titres in infected, vaccinated animals). The probabilities decreased linearly over time until full protection was reached, so that,(1)where b and β are the baseline probabilities (i.e. in unvaccinated animals), ε is the vaccine efficacy (assumed to be 100%, unless stated otherwise) and t_vacc and are the time of vaccination and time at which full protection is reached in species i (cattle (C) or sheep (S)), respectively. Data on the time to full protection in sheep and cattle were obtained from information supplied by the vaccine manufacturers: in sheep this is reached at 14 days post vaccination (dpv) (see also [13], [14]); in cattle it is reached at 60 dpv (see also [14]).

Protection zones (PZ), which identify where vaccine can be used, were defined by counties within the vaccination zones declared by Defra. All vaccination scenarios were based on the roll-out plan implemented by Defra [15], [16], using the actual dates of extension of the PZ as published on the Defra website [16] from 30 April 2008 (when the first batch of vaccine was released) up to 1 September 2008 (when the whole of England and Wales was declared to be a PZ). Under this approach farmers in counties not-yet infected were able to vaccinate in a preventive manner.

Only limited data are available on the level of vaccine uptake. In the summer of 2008, farmer surveys were carried out in East Anglia (an area affected by BTV in 2008) by the University of Cambridge, where estimates for vaccine uptake of up to 95% were recorded on sheep farms, although uptake was lower on cattle farms (Webb, Oura, O'Brien, Floyd and JLNW, unpublished). Data on sales of vaccine imply, however, that uptake in other areas was considerably lower. Thus, we simulated vaccination according to the Defra roll-out plan, assuming different levels of uptake (i.e. proportion of farmers vaccinating their stock; Table 1): 95% (the best-case scenario); 80% (the target level of coverage [17]); 50% (a more pessimistic scenario); and a scenario where the level of uptake increased with proximity to the area affected in 2007. In this case, vaccine uptake was 95% in the 2007 PZ, 75% in the 2007 surveillance zone, and 50% elsewhere (the 2007 free area). In addition, the impact of reduced uptake by cattle-only farms was investigated, following preliminary results of surveys conducted in East Anglia in summer 2008, which suggested there was a 10% lower level of uptake in this farm type (Webb, Oura, O'Brien, Floyd and JLNW, unpublished). The different scenarios for vaccine uptake are summarised in Table 1.

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Table 1. Summary of the scenarios for vaccine uptake.

https://doi.org/10.1371/journal.pone.0009353.t001

Under each scenario, a list of farms to be vaccinated within a county was created in the following way. A farm was added to the list with probability given by the specified level of uptake. Once this was done for all farms in the county, the order of vaccination was determined by randomising the list of farms to be vaccinated. The farms on the list were then vaccinated starting from the date when the county became part of a PZ. Because it is farmers themselves who vaccinate their stock, not specialised teams as would be the case for foot-and-mouth disease, vaccination was implemented at a constant number of farms per day in each county, such that all farms were vaccinated within 21 days following the date when that county became part of a PZ. Preliminary results of surveys conducted in East Anglia in summer 2008 by the University of Cambridge indicated that this was an appropriate time-scale to consider (Webb, Oura, O'Brien, Floyd and JLNW, unpublished). If a farm was vaccinated, all animals on that farm were assumed to be vaccinated. The number of doses of vaccine required (one per sheep and two per bovine) was recorded, but was assumed not to constrain the strategy.

Results

Spatio-Temporal Dynamics of BTV-8 in GB

In the absence of vaccination the model predicted severe outbreaks of BTV-8 in GB in terms of both the incidence of clinical disease (Figure 1A,B) and spatial spread (Figure 2A,B), particularly so for simulations using the warmer 2006 temperatures. Vaccination reduced both the incidence and spatial spread, with increasing levels of coverage resulting in greater reductions (Figures 1 and 2). However, even at high levels of uptake (95%) the model predicted some spread of BTV (Figures 1G,H and 2G,H). For the scenarios in which vaccine uptake varied according to distance from the 2007 affected area, the model predictions were similar to those assuming high levels (95%) of uptake everywhere, except for certain replicates where the virus escaped the high uptake area resulting in higher incidence and greater spread (Figures 1I,J and 2I,J; cf. Figures 1G,H and 2G,H). Finally, there was a marked impact of temperature with larger outbreaks (Figure 1) and more extensive spread (Figure 2) for the 2006 compared with the 2007 temperatures.

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Figure 1. Predicted time-course of BTV-8 epidemics in GB under different vaccination and temperature scenarios.

Results presented are for: (A, B) no vaccination; vaccination with (C, D) 50% uptake; (E, F) 80% uptake; (G, H) 95% uptake; and (I, J) variable levels of uptake (95% in the 2007 protection zone, 75% in the 2007 surveillance zone and 50% elsewhere). Simulations are based on (A, C, E, G, I) 2007 or (B, D, F, H, J) 2006 temperatures, assuming the best-fit Gaussian kernel to the north European data, a time to full protection in cattle of 60 dpv and vaccine efficacy of 100%. Each figure shows the median (circles) and 10th and 90th percentiles (error bars) for the incidence of BTV (number of new clinical holdings per week).

https://doi.org/10.1371/journal.pone.0009353.g001

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Figure 2. Predicted spatial distribution of BTV-8 in GB under different vaccination and temperature scenarios.

The different maps represent the extent of the predicted spatial spread up to the end of 2008 under different scenarios for vaccination and temperature: (A, B) no vaccination; vaccination with (C, D) 50% uptake; (E, F) 80% uptake; (G, H) 95% uptake; and (I, J) variable levels of uptake (95% in the 2007 protection zone, 75% in the 2007 surveillance zone and 50% elsewhere). Simulations are based on (A, C, E, G, I) 2007 or (B, D, F, H, J) 2006 temperatures, assuming the best-fit Gaussian kernel to the north European data, a time to full protection in cattle of 60 dpv and vaccine efficacy of 100%. The maps show the cumulative risk (see colour bars) expressed as the proportion of simulated outbreaks (out of 30 which took off; see Methods) for which at least one farm was affected by BTV within each 5km grid square.

https://doi.org/10.1371/journal.pone.0009353.g002

Outbreak Size

Comparing the results of different scenarios for vaccine uptake and temperature (Figure 3A,B) indicated that both vaccine uptake and temperature had a significant (P<0.001) impact on outbreak size, but that the effect of uptake depended on the temperature data-set (i.e. there was a significant (P = 0.006) interaction between uptake and temperature). However, lower uptake by cattle-only farms did not significantly affect outbreak size (P = 0.25).

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Figure 3. Sensitivity analysis of predicted outbreak size for BTV-8 in GB.

Impact of: (A,B) vaccination uptake assuming (A) 2007 or (B) 2006 temperatures (see Table 1 for codes for different uptake levels); (C) time to full protection in cattle; (D) vaccine efficacy; (E) Gaussian kernel parameter; (F) shape of the transmission kernel; and (G) a threshold temperature below which no transmission between farms was assumed to occur. The default scenario assumed variable vaccine uptake, 2007 temperatures, a time to full protection in cattle of 60 dpv, vaccine efficacy of 100% and the best-fit Gaussian kernel to the north European data (i.e. no temperature dependence). The boxplots show the median (red line) and the 25th and 75th percentile (blue box); the whiskers indicate 1.5 times the interquartile range; and the red crosses show outlying values for the cumulative number of affected holdings at 3 November 2008.

https://doi.org/10.1371/journal.pone.0009353.g003

For those simulations using the 2007 temperature data-set the scenarios could be divided simply into high (≥80%) or low (≤50%) levels of uptake, with smaller outbreaks occurring for the high compared with low levels of uptake (Figure 3A). In contrast, there were differences in outbreak size between all five levels of vaccine uptake considered (Table 1) for simulations based on 2006 temperatures (Figure 3B).

Discussion

This paper presents an investigation of the key factors influencing the success of a vaccination programme against BTV and, in particular, the effects of the level of vaccine uptake by farmers and temperature. To address these issues we used mathematical models developed to describe the spread of BTV within and between farms in GB, which had been validated using data on the spread of BTV-8 in GB in 2007 [11].

Qualitatively, the model predicts a similar pattern of outbreaks (Figure 1) to that observed in northern Europe in 2006 and 2007 (i.e. in the absence of vaccination), with small numbers of affected holdings in the first year, followed by large numbers in the second year [9]. Although a quantitative comparison between countries in the number of outbreaks is problematic because of differences in size and farming practices, outbreaks involving many thousands of BTV-8 affected holdings were reported in 2007 for Belgium, Germany, France and the Netherlands [9]. This was also the case for the simulations for GB using the 2007 temperature data (Figure 3A), though outbreak sizes were much larger for simulations using the 2006 temperatures (Figure 3B).

Vaccination was predicted to reduce incidence (Figure 1), extent of spread (Figure 2) and outbreak size (Figure 3A,B), with a greater reduction achieved for higher levels of coverage, in particular, in previously affected areas. However, even at high levels of uptake, there was still some spread, though at much lower levels compared with no vaccination (Figure 1), which is, in part, a consequence of transmission occurring in the model before vaccination started (on 30 April 2008, i.e. 39 weeks after 4 August 2007). This observation suggests more consideration needs to be given to the seasonal dynamics of the vector [11] and, more generally, to the overwintering of BTV, something which is discussed in more detail below.

A high level (>80%) of vaccine uptake in the previously-affected area was most important for controlling the spread of BTV (Figures 1 and 2). If, however, uptake was lower in areas outside those previously affected, there was a risk of escape of BTV into areas with lower coverage and, hence, greater potential for spread (Figure 2I,J; cf. Figure 2G,H). This observation highlights the need for a buffer zone beyond the previously affected area with high levels of vaccine uptake to contain the spread of BTV. The size of the buffer will depend critically on the transmission kernel [11], with a larger buffer required for kernels with fatter tails (i.e. higher probabilities of transmission at long distances).

Our analyses suggest that the absence of reported cases of BTV-8 in GB during 2008 and the apparent success of control can be attributed to the high levels of vaccine coverage achieved in previously affected areas, coupled with cooler temperatures in 2008. Although there were no reported cases in GB, the virus was still circulating in northern mainland Europe in 2008 and 2009 and, consequently, there remains a risk of reintroduction. Furthermore, other serotypes currently threaten GB, including BTV-1, which reached the northern French coast in late 2008 with further cases in 2009. In addition, BTV-6 was reported to be circulating in the Netherlands and Germany in 2008 [20], and evidence of BTV-11 infection (but not circulation) was found in cattle in Belgium [21].

Although an inactivated vaccine against BTV-1 is available, it cannot currently be used in a preventive manner in GB without the prior creation of a so-called “blue zone” for that serotype. In addition, no vaccine has yet been developed against BTV-6 or BTV-11. The results of the simulations indicate that a re-incursion by BTV-8 or an incursion by BTV-1 (or any other serotype) could be controlled provided high levels of vaccine coverage are achieved (Figures 1 & 2). As re-vaccination with the new inactivated vaccines is recommended annually, it is essential that the level of vaccination against BTV-8 does not decline over the coming year and that sufficient stocks of vaccine against BTV-1 are available and can be deployed rapidly should an incursion of this serotype occur. By contrast, with no inactivated vaccine available, an incursion of BTV-6 could potentially be very serious, especially if temperatures are warmer (Figures 1 and 2), though this assumes that the transmission dynamics for different serotypes would be similar.

The model predictions for the impact of vaccination were not greatly affected by assumptions made about the time to full protection in cattle (Figure 3C). This is largely a consequence of the way in which vaccine was deployed in areas well in advance of BTV arriving. If, however, the vaccine were being used reactively in response to a new incursion, this parameter could influence the success of vaccination. As would be expected, a decrease in vaccine efficacy results in an increase in outbreak size (Figure 3D). Although a linear relationship between the logarithm of the outbreak size and the efficacy adequately captured the model predictions, there was evidence for a threshold effect, with a stepped change in outbreak size at efficacies between 70–80% (Figure 3D). This is a consequence of herd immunity [22], such that a herd is protected (i.e. the basic reproduction number (R₀) is reduced below one) provided that a large enough proportion of animals in the herd is protected. Estimates for R₀ for BTV [23] suggest that this should be achieved with a vaccine efficacy of at least 75%, which is likely to be the case, at least for sheep [13].

The shape of the transmission kernel had a major impact on the model predictions (Figure 3E,F). Increasing the probability of longer-range spread, whether by decreasing the shape parameter or by using a kernel with fat tails (i.e. fat-tailed or FMD), dramatically increases the size of the outbreak, even with vaccination. This reflects the impact of movement restrictions (which were assumed to prevent transmission outside the PZ, so that long range transmission is principally a result of animal movements) on predicted spread using different kernels [11]. For the Gaussian kernel, movement restrictions had only a small effect on spread, whereas for the exponential and, especially, the fat-tailed and FMD kernels, these restrictions greatly reduced spread. For these kernels, the roll-out of the protection zone to allow vaccination (see Vaccination in Methods section) has the effect of markedly increasing the potential for transmission and, hence, for spread into areas with low vaccine uptake.

In our earlier analyses of outbreak data for BTV-8 in northern Europe during 2006, we did not identify a significant impact of temperature on transmission [11]. By contrast, the sensitivity analyses in the present study indicated that temperature dependence in the spread of BTV between farms (in this case via a threshold temperature below which transmission was assumed not to occur) could impact on model predictions for the spread and control of BTV. In particular, if no transmission was assumed to occur below 15°C, outbreaks were significantly smaller than if there was no threshold or the threshold was ≤10°C (Figure 3G). A threshold temperature is a simple, but crude and potentially inaccurate method of including temperature dependence. For example, Culicoides species are known to be active at temperatures below 15°C [24], while animal movements are unlikely to be influenced by ambient temperatures. Accordingly, a more detailed description of transmission between farms is needed which disentangles animal from vector movements and which accounts for seasonal variation in vector activity.

Under all the scenarios considered in this paper, BTV-8 was predicted to have persisted in a majority of replicates. The long-term dynamics of BTV-8 are of considerable importance, both in terms of determining how long vaccination needs to be carried out (annual booster vaccination is required to maintain protection) and when freedom from virus circulation can begin to be assessed. However, investigating the long-term dynamics of BTV requires a greater understanding of the ability of the virus to overwinter [25] and of the biology of those Culicoides species implicated as vectors in northern Europe [7].

Recent evidence of vertical [26], [27], [28], [29] and horizontal [28] transmission in the vertebrate host have re-launched the debate about alternative transmission mechanisms being involved in the spread of BTV. These mechanisms could provide routes by which the virus can overwinter in temperate climates [25]; the recent epidemic in northern Europe having confirmed that BTV-8 is able to overwinter successfully and with apparent high probability. The outbreak in northern Europe has also demonstrated the potential for Palaearctic species of Culicoides to transmit BTV efficiently. However, these species are not yet fully characterised in terms of their life history parameters or their responses to the prevailing environmental conditions; vector competence, host preference, biting habits and abundance of the different vector species are also largely unknown. While potential differences between vector species could have a major impact on the risk of BTV to British livestock, the fact that BTV-1 has spread in northern Europe underlines the capacity of the northern species of Culicoides to transmit other serotypes and strains of the virus.

This study represents a first step in analysing the spread and control of BTV at a national level, but shows that the model provides a suitable framework for investigating the consequences of BTV incursions to GB and assessing the relative efficacy of different options for control. Future work should focus on incorporating in the model more realistic descriptions of the seasonal vector dynamics and of the overwintering mechanisms for BTV.

Supporting Information

Acknowledgments

The authors thank Prof. Matthew Baylis (University of Liverpool) for his input at early stages of the project, Dr Olivier Restif (University of Cambridge) for sharing computer time and Dr Sean Rands (University of Bristol) for comments on the manuscript. The authors are particularly grateful to Dr Cerian Webb, Stephanie O'Brien, Toby Floyd (University of Cambridge) and Dr Chris Oura (IAH) for providing preliminary findings from their study.