Modelling the risk posed by Aedes mosquitoes in Europe: Identifying research needs from public health stakeholders and field entomologists

Highlights
• Bridging the gap: We propose a demand-driven co-development framework for vector control.
• Scale relevance: Models must prioritise neighborhood data and weekly update cycles.
• Unified metrics: We advocate for decision-facing indicators shared across geographical and institutional boundaries.
• Multisectoral approach: Technical tools must be embedded in formal policy structures.

Abstract
The growing public health burden of Aedes mosquito-borne diseases requires a comprehensive understanding of Aedes species biology, ecology, and vector competence. Eco-epidemiological modelling of Aedes vector species has grown significantly in recent years, driven by the increasing reports of outbreaks in endemic and non-endemic temperate areas, as well as the latitudinal and altitudinal range expansion of these vectors. A prominent example is the Asian tiger mosquito, Aedes albopictus, a competent arbovirus vector that has spread across most continents through the movement of humans and goods. Species distribution models and mechanistic models have been used to predict the spatio-temporal distribution and dynamics of this vector. However, despite the potential of these models to capture the vector distribution and dynamics, integrating them into practical monitoring, surveillance, and vector control activities remains challenging, often due to a lack of communication and model co-development between scientists and public health stakeholders. This paper reports the results of a workshop on vector modelling held in Bologna (Italy) in September 2024, which brought together European experts in disease modelling, public health stakeholders, and medical entomologists. The workshop identified key priorities for advancing the operational use of Aedes-focused quantitative models, including sustained investment in surveillance, improved representation of environmental and biological drivers, standardisation of model outputs, and the establishment of long-term, co-produced modelling frameworks embedded within public health workflows.