A real-time mechanistic framework for early inference of chikungunya transmission and outbreak sizes in mainland France, 2025.

In 2025, mainland France experienced an unprecedented chikungunya outbreak in Europe, likely associated with suitable climatic conditions and established presence of Aedes albopictus, the primary European vector of chikungunya virus (CHIKV). During the early phase of the outbreak (May-July 2025), when only limited case data were available, public health decision-making required rapid situational assessment under substantial uncertainty. Here, we apply a state-of-art, climate-sensitive eco-epidemiological modelling framework to infer transmission dynamics in real-time and to characterise early progression of outbreaks across affected locations in France. The framework is designed to infer transmission relevant information from early epidemic data, including relative outbreak risk across locations, potential timing of the initial amplification phase of transmission, and likely size of outbreaks in the absence of public-health control interventions. The analysis indicates that early epidemic data can be used to identify locations likely to experience substantial transmission episodes and to refining estimates of the timing of key transition phases of transmission, including the initial amplification phase of transmission approximately 2-3-months ahead of peak transmission. Predicted outbreak potential varied considerably across locations, reflecting differences in local climatic conditions and population density incorporated within the modelling framework. This framework supports real-time situational awareness and can be employed to improve the response and targeting of public health interventions during the emerging phase of outbreaks. Furthermore, insights into location-specific differences in predicted outbreak size and response priorities are particularly useful for understanding the localised transmission risk and informing targeted interventions.