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

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 21 ) 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.

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“…The role of animal transportation in the dissemination of BTV-8 in northwest Europe may have been significant [44].…”

Section: (D) Further Consideration Of the Extrinsic Incubation Periodmentioning

confidence: 99%

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

et al. 2012

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“…Some of these methods are based on data from surveillance and monitoring programmes. For example, [9] estimated between herds for the Netherlands. Furthermore, a theoretical study on using a deterministic epidemic model was introduced by [10] to investigate the seasonal spread of BTV over several years and to evaluate the effectiveness of vaccination strategies.…”

Section: Introductionmentioning

confidence: 99%

Bluetongue Disease Risk Assessment Based on Observed and Projected Culicoides obsoletus spp. Vector Densities

Brugger

Rubel

2013

PLoS ONE

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Bluetongue is an arboviral disease of ruminants causing significant economic losses. Our risk assessment is based on the epidemiological key parameter, the basic reproduction number. It is defined as the number of secondary cases caused by one primary case in a fully susceptible host population, in which values greater than one indicate the possibility, i.e., the risk, for a major disease outbreak. In the course of the Bluetongue virus serotype 8 (BTV-8) outbreak in Europe in 2006 we developed such a risk assessment for the University of Veterinary Medicine Vienna, Austria. Basic reproduction numbers were calculated using a well-known formula for vector-borne diseases considering the population densities of hosts (cattle and small ruminants) and vectors (biting midges of the Culicoides obsoletus spp.) as well as temperature dependent rates. The latter comprise the biting and mortality rate of midges as well as the reciprocal of the extrinsic incubation period. Most important, but generally unknown, is the spatio-temporal distribution of the vector density. Therefore, we established a continuously operating daily monitoring to quantify the seasonal cycle of the vector population by a statistical model. We used cross-correlation maps and Poisson regression to describe vector densities by environmental temperature and precipitation. Our results comprise time series of observed and simulated Culicoides obsoletus spp. counts as well as basic reproduction numbers for the period 2009–2011. For a spatio-temporal risk assessment we projected our results from the location of Vienna to the entire region of Austria. We compiled both daily maps of vector densities and the basic reproduction numbers, respectively. Basic reproduction numbers above one were generally found between June and August except in the mountainous regions of the Alps. The highest values coincide with the locations of confirmed BTV cases.

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“…The virus overwintered and spread over most of Europe causing massive losses to the livestock industries of several countries over a number of years [29], [30]. Phylogenetic analyses showed that the northern European strain of BTV-8 is most closely related to a strain from Central Africa [31], although the route of introduction has not yet been identified.…”

Section: Introductionmentioning

confidence: 99%

Real Time RT-PCR Assays for Detection and Typing of African Horse Sickness Virus

et al. 2014

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Although African horse sickness (AHS) can cause up to 95% mortality in horses, naïve animals can be protected by vaccination against the homologous AHSV serotype. Genome segment 2 (Seg-2) encodes outer capsid protein VP2, the most variable of the AHSV proteins. VP2 is also a primary target for AHSV specific neutralising antibodies, and consequently determines the identity of the nine AHSV serotypes. In contrast VP1 (the viral polymerase) and VP3 (the sub-core shell protein), encoded by Seg-1 and Seg-3 respectively, are highly conserved, representing virus species/orbivirus-serogroup-specific antigens. We report development and evaluation of real-time RT-PCR assays targeting AHSV Seg-1 or Seg-3, that can detect any AHSV type (virus species/serogroup-specific assays), as well as type-specific assays targeting Seg-2 of the nine AHSV serotypes. These assays were evaluated using isolates of different AHSV serotypes and other closely related orbiviruses, from the ‘Orbivirus Reference Collection’ (ORC) at The Pirbright Institute. The assays were shown to be AHSV virus-species-specific, or type-specific (as designed) and can be used for rapid, sensitive and reliable detection and identification (typing) of AHSV RNA in infected blood, tissue samples, homogenised Culicoides, or tissue culture supernatant. None of the assays amplified cDNAs from closely related heterologous orbiviruses, or from uninfected host animals or cell cultures.

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

Cited by 41 publications

References 24 publications

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

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

Bluetongue Disease Risk Assessment Based on Observed and Projected Culicoides obsoletus spp. Vector Densities

Real Time RT-PCR Assays for Detection and Typing of African Horse Sickness Virus

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