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Modelling the spatial distribution of Culicoides biting midges at the local scale. [237]


Academic year: 2021

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Presentation: 237 - Modelling the spatial distribution of Culicoides biting midges at the local scale Location: Uxmal 1 ( 5 )

Pres. Time: Friday, Nov 06, 2015, 5:15 PM - 5:30 PM Category: +A9. Vector-borne and parasitic diseases

Author(s): Georgette Kluiters1, David Sugden1, Helene Guis2, K. Marie McIntyre1, Karien Labuschagne3, Matthew Baylis1, 1University of Liverpool, Neston, United Kingdom; 2CIRAD, Montpellier, France; 3ARC - Onderstepoort Veterinary Institute, Onderstepoort, South Africa. Contact:


Abstract: Purpose: The Culicoides midge vectors of bluetongue (BT) are ubiquitous on farms in the UK, but little research has explored their spatial abundance, an important determinant of disease risk. Models to explain and predict variation in their abundance are needed for effective targeting of BT control methods. Although epidemiological models are commonplace at the national scale, no investigations have taken place at a finer spatial scale. Our aim is to identify determinants of midge abundance at a local 1 km scale.

Methods: Midge abundances were estimated using light traps on 35 farms in north Wales. Culicoides catches were combined with remotely-sensed ecological correlates, and on-farm host and environmental data, within a general linear model. Drivers of local scale variation were determined at the 1 km resolution.

Results: Local-scale variation in Obsoletus Group abundance exhibited an almost 500-fold difference (74 to 33,720) between farms, but the Obsoletus Group model explained 81% of this variance. The variance explained was consistently high for the Pulicaris Group, C. pulicaris and C. punctatus (80%, 73%, and 74%), the other possible BTV vector species in the UK. The abundance of all vector species increased with the number of sheep on farms, but this relationship was missing from any of the non-vector models. Performance of the non-vector models was also high (65-87% variance explained), but species differed in their associations with satellite variables. Conclusions: At a large spatial scale, there is significant variation in Culicoides Obsoletus Group abundance, undermining attempts to record their nationwide distribution in larger scale models, which have historically explained the abundance of these vectors poorly. Satellite data can be used to explain a high proportion of this variation and may produce effective predictive models of disease vector abundance.

Relevance: This work highlights how novel local-scale modelling of disease vectors can explain a large degree of spatial variation that national-scale models fail to explain. This should be of note to policy makers when deciding upon guidelines for entomological surveys before, during and after disease outbreaks.

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