The Zanzemap project: artificial intelligence models and satellite data to forecast vector dynamics in Northern Italy

The project "ZanZeMap" aims to enhance public health in the Autonomous Province of Trento (Northern Italy) by developing user-friendly maps that indicate the risk of tick and mosquito presence and activity, addressing significant public health challenges posed by vector-borne diseases. Utilizing advanced artificial intelligence (AI) and machine learning techniques, this initiative analyzes detailed climatic and environmental data to predict where and when these arthropods are most active. Key to this project is the integration of high-resolution climate data, including satellite observations, providing insights into temperature, humidity, and vegetation cover—critical factors for understanding vector habitats and behaviors. The project can forecast changes in mosquito and tick populations up to two weeks in advance under various climate scenarios, allowing for proactive vector management. Additionally, field-based vector monitoring will be incorporated to validate the model’s forecasts, enhancing the accuracy of vector activity assessments and enabling timely interventions. The resulting online maps will empower the local population and stakeholders by providing real-time information on vector phenology and activity, facilitating personal protective measures against bites such as using repellents and fostering a collaborative environment in public health initiatives. Ultimately, this project not only aims to improve local vector surveillance but also has the potential for application in diverse geographical contexts facing similar public health challenges exacerbated by climate change. By establishing a robust framework for ongoing data analysis and community involvement, the initiative seeks to enhance public health outcomes and quality of life in the Autonomous Province of Trento and the Alpine area in the future