The Forecasting, Early Warning System and Tools partners met in the University of Haifa, between 13 and 14 of March 2023, where they discussed and agreed on methodological approaches to sand fly presence and numbers and sand fly borne diseases modelling and projections.
Data and image analysis, climate and health analysis and modelling are one of the CLIMOS tasks. This task aims to concentrate on the construction of the project-generated and collected CLIMOS dataset, including collection and analysis of the supporting data from previous and ongoing European projects, with a focus on a centralized data collection, curation and preparation for web infrastructure, and on providing a detailed specification of collected and generated data to enable sharing and further use outside of the consortium. This dataset will include sand fly surveillance-related records, climate and environmental records, and One Health (human and pet dog infections) data. This meeting aimed to discuss this specific task and agree jointly on the future steps.
On the first day it was discussed mainly the methodologies to be addressed by the team, where some partners introduced their scientific work:
- Dr. Nenad Gligoric, head of research at Zentrix Lab, with his discussion on in-situ data monitoring for localised areas in a scale of 5-10 meters, using data calibration multispatial measurements, as well as by using the outcomes and measurements reported by researchers.
- Prof. Dr. Frank van Langevelde, Wageningen University: understanding and predicting the spread of SF and SFBDs using species distribution modelling (SDM).
- Dr Suzana Blesic, Institute for Medical Research, University of Belgrade, Belgrade, Serbia: Understanding human vector-borne disease cases in relation to temperature and rainfall using wavelet transform analysis. Introduction to the Hurst Space Analysis.
- Prof. Dr. Luis Samaniego, Department Computational Hydrosystems (CHS), Data Science and Hydrology (Uni-Potsdam); Helmholtz Centre for Environmental Research – UFZ: A brief-overview of the statistical approaches used in hydro-meteorological modelling: Bias correction, downscaling/interpolation, causality and stochastic dependence.
- Mr. Daniel San Martín, CEO, Predictia Intelligent Data Solutions SL: A high-resolution urban-scale weather forecasting system for optimizing operations on the metro network.
- Prof. Shlomit Paz, School of Environmental Sciences, University of Haifa, Israel: Evaluating the temperature impact on vector-borne diseases – examples for methodologies from recent studies.
The second day of work was focused on data sources, availability, parameters needed, resolution (temporal and spatial), standardization of sand fly records, distribution of tasks and the main conclusions of the two-day meeting.
The team was also able to have a guided tour at Daliyat el-Carmel, a traditional town of the Druze community. The CLIMOS team thanks the amazing meeting organization to the University of Haifa. The CLIMOS data analysis and modelling team is fully ready to start their work!