Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset.

The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014-2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted European mosquito vectors: , , , , and . Most records are from Spain, reflecting Spanish national and regional funding, but since autumn 2020 substantial records from other European countries are included, thanks to volunteer entomologists coordinated by the AIM-COST Action, and to technological developments to increase scalability.

Multiple invasions, Wolbachia and human-aided transport drive the genetic variability of Aedes albopictus in the Iberian Peninsula.

The Asian tiger mosquito, Aedes albopictus, is one of the most invasive species in the world. Native to the tropical forests of Southeast Asia, over the past 30 years it has rapidly spread throughout tropical and temperate regions of the world. Its dramatic expansion has resulted in public health concerns as a consequence of its vector competence for at least 16 viruses.

First detection of Aedes japonicus in Spain: an unexpected finding triggered by citizen science.

Background: Aedes japonicus is an invasive vector mosquito from Southeast Asia which has been spreading across central Europe since the year 2000. Unlike the Asian Tiger mosquito (Aedes albopictus) present in Spain since 2004, there has been no record of Ae. japonicus in the country until now.

Citizen Science: A Gateway for Innovation in Disease-Carrying Mosquito Management?

Traditional methods for tracking disease-carrying mosquitoes are hitting budget constraints as the scales over which they must be implemented grow exponentially. Citizen science offers a novel solution to this problem but requires new models of innovation in the public health sector.

Citizen science provides a reliable and scalable tool to track disease-carrying mosquitoes.

Recent outbreaks of Zika, chikungunya and dengue highlight the importance of better understanding the spread of disease-carrying mosquitoes across multiple spatio-temporal scales. Traditional surveillance tools are limited by jurisdictional boundaries and cost constraints. Here we show how a scalable citizen science system can solve this problem by combining citizen scientists' observations with expert validation and correcting for sampling effort.

Expectation-Maximization Binary Clustering for Behavioural Annotation.

The growing capacity to process and store animal tracks has spurred the development of new methods to segment animal trajectories into elementary units of movement. Key challenges for movement trajectory segmentation are to (i) minimize the need of supervision, (ii) reduce computational costs, (iii) minimize the need of prior assumptions (e.g.

Approaches to passive mosquito surveillance in the EU.

The recent emergence in Europe of invasive mosquitoes and mosquito-borne disease associated with both invasive and native mosquito species has prompted intensified mosquito vector research in most European countries. Central to the efforts are mosquito monitoring and surveillance activities in order to assess the current species occurrence, distribution and, when possible, abundance, in order to permit the early detection of invasive species and the spread of competent vectors. As active mosquito collection, e.