A Modelling Framework to Estimate Vector Dispersal and Disease Spread in an Important Agricultural Pathosystem

ABSTRACT Cereal aphids vector devastating cereal pathogens, primarily yellow dwarf viruses, with severe infection reducing yields by 20%–80%. Several aphid species are of concern in cereal agro‐ecosystems, and farmers are currently advised to apply insecticide if a single cereal aphid is found within the crop. Current practices oversimplify the biology and ecology of the system: Each aphid species can transmit a range of yellow dwarf virus species with variable efficiency, and aphid genotypic diversity can influence this further. Incorporating this variation into decision‐making processes could help with developing bespoke, risk‐based management options that account for the composition of the local vector–virus population and support more sustainable management strategies. We describe a stage‐structured model that can estimate vector dispersal and disease spread for discrete vector–virus combinations. We use data for the two main cereal aphid species and the two species of yellow dwarf virus of greatest concern in Europe to examine how diversity at each level of the vector–virus system impacts disease spread. Our modelling highlights diversity at each scale as an important factor. The two main vector species have contrasting dispersal patterns, and this interacts with virus transmission efficacy to influence disease spread; genetic variation within a vector population is identified as an important driver behind disease spread and risk; and for vector species that transmit multiple virus species, the specific vector–virus species combination is a key risk factor to consider. Our study highlights the variable levels of risk presented by different vector–virus combinations. By integrating this information into the decision‐making process, farmers and growers can transition towards more risk‐based and sustainable pest and pathogen management strategies. Our modelling framework represents a tool that can be used to explore vector–virus–host interactions in greater detail, and here we use cereal systems as a case study.