Phlebotomine sand flies spread canine leishmaniosis across parts of southern Europe. Researchers in Spain and Portugal are designing a system to estimate where transmission risk may rise. The PLANET4HEALTH project will combine climate and environmental data with animal health records. Its first case study is intended to provide veterinarians and public health authorities with short-term forecasts for defined areas.
The system is not yet an operational alert network. Researchers will develop and evaluate it, refining the system before assessing whether it can support decisions in practice. Its value will depend on the quality of its predictions and whether veterinary services and health authorities can use them easily.
Leishmania infantum causes canine leishmaniosis, which is transmitted by phlebotomine sand flies. The disease is endemic in the Mediterranean basin, and dogs are the basic domestic reservoirs linked to human infection. European veterinary reviews, including literature in Veterinary Parasitology: Regional Studies and Reports, continue to describe the infection as an impressive zoonotic concern in southern Europe.
The researchers say climate change and environmental degradation, alongside increased movement of people and animals, may expand the distribution of vectors and intensify transmission risk. Temperature and humidity affect sand-fly activity, as do seasonal patterns. Rainfall and soil moisture provide further environmental signals.
The planned system will use historical and near-real-time information. Researchers will assess climate data alongside sand-fly surveillance records. Veterinary inputs will include Leishmania serology results and records of canine leishmaniosis cases, along with information about domestic dog populations.
Data will come from national and European sand-fly surveillance initiatives, as well as veterinary clinical and diagnostic databases in Spain and Portugal. National public health monitoring systems will also contribute. Formal agreements with the organisations providing the information will govern access.
The veterinary sector is also supporting the project. IVC Evidensia Portugal and LETI Pharma will contribute epidemiological data. Hospitals and clinics in both countries are involved, along with university centres.
The analytical stage will use statistical models and machine learning. Researchers plan to describe seasonal vector behaviour and estimate the risk of canine leishmaniosis. They will also produce short-term forecasts for defined geographical areas and develop future projections. The model will connect environmental signals with veterinary evidence, drawing on both sources.
Spain is moving toward predictive risk management in other fields too. A related report showed how another Spanish sector is testing data-driven tools before threats reach critical systems. The health project has a different purpose and evidence base.
Users will test the system through co-creation workshops, with questionnaires and online feedback. Veterinarians and public health authorities, along with other end users, will assess its usefulness and feasibility, as well as how easily it can be used. The assessment will take place in stages.
The evaluation matters as much as the modelling. A technically advanced forecast has limited practical value if the people responsible for animal and public health cannot interpret or apply it. The model is not live.
PLANET4HEALTH is building a One Health structure, rather than a standalone database or weather map. It links vectors and animals with people, while accounting for environmental conditions in one risk assessment. The project's strongest feature is this integration. The decisive test will be whether its alerts are clear enough to support earlier preparation against canine leishmaniosis and flexible enough for other endemic regions.
The wider European surveillance context adds weight to that goal. Recent attention has focused on earlier detection and integrated monitoring, but that context does not change the project's current research and pilot status.
