Spain's Ministry of Health has added AIMA, an artificial-intelligence tool, to the Mosquito Alert citizen-science network. It identifies invasive mosquitoes from a phone photograph in under five minutes. The tiger mosquito has now been recorded in 156 municipalities, and a second invasive species, Aedes japonicus, has been detected in the cool, green north. The published figures are plain: AIMA classifies 55 of every 100 tiger-mosquito images correctly and auto-publishes the most confident quarter.
A person in Spain photographs a mosquito on a kitchen wall, opens an app, and uploads the picture. Four minutes later an algorithm has examined it. Within five minutes, the photographer has an answer. If the mosquito is an invasive species found somewhere it has not been recorded before, a regional health department receives an alert. No entomologist had to be awake. This is AIMA, the artificial-intelligence tool Spain's Ministry of Health has added to its national citizen-science surveillance network. It is a notable development in European vector control this year.
The announcement came from the Ministerio de Sanidad and the Mosquito Alert project. It arrived alongside two facts that explain why Spain built it. The tiger mosquito, Aedes albopictus, has now been confirmed in 156 municipalities since 2023. A second invasive species, the Japanese mosquito Aedes japonicus, has been detected in 10 municipalities across Asturias, Cantabria and the Basque Country. That is the cool, green north, not the warm Mediterranean coast.
What matters here is not that Spain has more mosquitoes. It is how the country found out, and what that method says about where surveillance is heading.
What AIMA does, and how well
Mosquito Alert is not new. For years it has run on the same principle as a birdwatching app. Ordinary people photograph mosquitoes and upload them, and a panel of expert entomologists confirms the species. The data feed a public map and a national early-warning system. The weakness was the bottleneck: every photograph needed a human expert, and humans are finite. As uploads climbed into the tens of thousands, the queue grew.
AIMA, an AI for the identification and monitoring of mosquitoes, is built to ease that bottleneck. The system processes incoming observations every four minutes and returns a verdict to the user in under five. It has been trained to recognise the species that matter: Aedes albopictus; the Culex genus that carries West Nile virus; the newly arrived Aedes japonicus, which it learns to tell apart from its near-twin Aedes koreicus; and Aedes aegypti, the yellow-fever mosquito. Aedes aegypti is not yet established in Spain. Spain plainly wants its detector trained before that species arrives.
Now the published performance figures, which are more revealing than a rounded-up accuracy claim. Of every 100 tiger-mosquito images AIMA receives, it classifies 55 correctly. Of those, the 25 it is most confident about, above 98% certainty, are published straight to the public map with no human in the loop. The remaining cases go to the expert entomologists who ran the system before. AIMA is not replacing the specialists. It clears the high-confidence cases so they can spend their attention on the ambiguous photographs. That is a measured division of labour, and a more trustworthy claim than "the machine does it all."
The scale of participation
The bottleneck mattered because of the participation numbers. Through the Mosquito Alert app, Spanish citizens logged more than 19,000 observations in 2023 and nearly 10,000 in 2024. In the first months of 2025 they logged more than 4,600. Each one is a data point an entomologist would otherwise have had to chase in the field. The whole apparatus is, in effect, a national sensor network made of phones and curiosity, with an algorithm now at the front desk.
This matters because it inverts a common assumption. Headlines about mosquitoes and technology usually involve gene drives, sterile males, or Wolbachia releases, interventions that change the mosquito. AIMA does nothing to the mosquito. It simply sees it faster. Seeing it faster decides whether a newly arrived species is caught in its first season or its third. Surveillance is the least cinematic part of vector control and often the most decisive.
What other countries can take from it
Aedes japonicus establishing in Cantabria is not a Mediterranean problem. It is a northern, temperate, cool-climate problem, which is to say a preview of conditions much of central and northern Europe shares. The species is a competent vector under laboratory conditions and tolerates cold better than its tropical relatives. Spain's value to the rest of Europe is not its weather. It is its method: a working, public, AI-assisted citizen network that turns a phone photograph into a surveillance signal in five minutes.
The practical lesson for a household is encouraging because it asks so little. The standing water that breeds these mosquitoes is also what an individual can remove in an afternoon: the saucer under the flowerpot, the blocked gutter, the bucket left in the rain. Surveillance maps where the mosquito is. Removing standing water and using physical barriers reduce the risk. Spain's system is good at the first half. The second half happens at home.
A new record on the map is not a defeat. A mosquito photographed, classified and mapped within five minutes is one that health teams can track and act on. You cannot manage what you cannot see, and Spain has made itself able to see much more, much faster.
What to watch next
Two things. First, whether AIMA's published accuracy improves as the training set grows. A score of 55 in 100 is a respectable start for a system designed to defer its uncertain cases. The number to watch is how the high-confidence, auto-published share climbs over the coming season. Second, and more important for the continent: whether other European countries adopt the model rather than rebuild it. Mosquito Alert already has sister projects beyond Spain. An AI-assisted citizen network gets cheaper and better the more places run it, because every new photograph anywhere improves the detector everywhere.
The Ministry framed the launch as Spain consolidating itself "as a European reference in this field." AIMA gives other European countries a working model to examine.
A note on sourcing: this piece draws on Spanish-language announcements from the Ministerio de Sanidad and iSanidad.
Sources cited
- Ministerio de Sanidad, nota de prensa on AIMA and invasive mosquito surveillance (Spanish), May 2026, https://www.sanidad.gob.es/gabinete/notasPrensa.do?id=6704&metodo=detalle
- iSanidad, El mosquito tigre se expande hasta 156 municipios en España y el mosquito de Japón se detecta en Asturias, Cantabria y País Vasco (Spanish), May 2026, https://isanidad.com/335913/el-mosquito-tigre-se-expande-hasta-156-municipios-en-espana-y-el-mosquito-de-japon-se-detecta-en-asturias-cantabria-y-pais-vasco/