Emerging and endemic mosquito-borne viruses can be difficult to detect and monitor because they often cause asymptomatic infections in human or vertebrate animals or cause nonspecific febrile illness with a short recovery waiting period. Cases′ detection in vertebrate hosts can be complemented by entomological surveillance, but this method is not adapted to low infection rates in mosquito populations that typically occur in low or non-endemic areas. We identified West Nile Virus circulation in Camargue, a wetland area in South of France, using a cost effective innovative xenomonitoring method based on the molecular detection of virus in excreta from trapped mosquitoes. We also succeeded at identifying the mosquito community diversity dynamic on several sampling sites, together with the vertebrate hosts on which they fed prior to be captured using amplicon-based metagenomic on mosquito excreta without processing any mosquito. Mosquito excreta-based virus surveillance can be considered as a cost-effective and non-invasive strategy that offers the additional asset to reveal the ecological network underlying arbovirus circulation.

Mosquito species belonging to the genus Aedes have attracted the interest of scientists and public health officers for their invasive species traits and efficient capacity of transmitting viruses affecting humans. Some of these species were brought outside their native range by human activities such as trade and tourism, and colonised new regions thanks to a unique combination of eco-physiological traits. Considering mosquito physiological and behavioural traits to understand and predict the spatial and temporal population dynamics is thus a crucial step to develop strategies to mitigate the local densities of invasive Aedes populations. Here, we synthesised the life cycle of four invasive Aedes species (Ae. aegypti, Ae. albopictus, Ae. japonicus and Ae. koreicus) in a single multi-scale stochastic modelling framework which we coded in the R package dynamAedes. We designed a stage-based and time-discrete stochastic model driven by temperature, photo-period and inter-specific larval competition that can be applied to three different spatial scales: punctual, local and regional. These spatial scales consider different degrees of spatial complexity and data availability, by accounting for both active and passive dispersal of mosquito species as well as for the heterogeneity of the input temperature data. Our overarching aim was to provide a flexible, open-source and user-friendly tool rooted in the most updated knowledge on species biology which could be applied to the management of invasive Aedes populations as well as for more theoretical ecological inquiries.