Imagine a weather app, but instead of rain, it predicts where disease-carrying sand flies will move as the planet warms. It uses sensors and big data to spot risky areas before outbreaks happen. This helps cities and health services prepare their defenses in advance.
Climate change is expanding the range of sand fly-borne diseases, leaving healthcare systems unprepared for new outbreaks. There is a lack of integrated, real-time data to predict where these diseases will emerge.
An interactive online platform and an Early Warning System (EWS) for disease prediction. They also developed a new physical trapping solution for vector monitoring.
If you are a software provider dealing with unpredictable disease outbreaks — this project developed an Early Warning System (EWS) that provides accurate infection risk prognosis and range expansions. This allows for the creation of precision surveillance networks across 14 countries.
If you are a hardware manufacturer dealing with inefficient pest tracking — this project developed new innovative technical solutions for vector monitoring, including a new trapping solution. This provides a blueprint for scalable, climate-aware IoT sensor deployment.
If you are an insurer dealing with rising costs of climate-induced health risks — this project developed socio-economic risk assessments and cost-benefit evaluations. This helps in pricing policies based on science-backed infection risk data.
Based on available project data, no commercial pricing is listed as the project focuses on an open access online platform and open-source tools for public healthcare.
The project demonstrates scalability by implementing surveillance networks across 14 countries and utilizing big data time series for EU-wide monitoring.
The project aims to provide an open access interactive platform and an open-source tool via the European Commission ISA JoinUP, suggesting a non-proprietary licensing model.
It uses new interoperability data ontologies (OBO and OGC) to ensure data can be shared across different biological, biomedical, and geospatial systems.
The project runs from 2022-09-01 to 2026-05-31, with iterative EWS versions delivered during the surveillance seasons.
The consortium is heavily research-oriented with 17 universities and 4 research institutes, but it maintains a practical edge with 5 industry partners (all SMEs). With 30 partners across 16 countries, the project has a strong geographical footprint, ensuring the resulting data and tools are validated across diverse European climates.
Contact Universidade Nova de Lisboa in Portugal
Contact us to explore licensing for the open-source EWS tools.
