[FPU2019] Ecología teórica y Computacional

Our vision is to establish a Versatile forecasting, nowcasting, and tracking system (VEO) serving as an interactive observatory for the generation and distribution of high quality actionable information for evidence-based early warning, risk assessment and monitoring of Emerging InfectiouOur s Diseases and Antimicrobial resistance by public health actors and researchers in the One-Health domain.VEO will be built by an iterative process between data science and technology experts, disease experts from public health and academia, social scientists, and citizen scientists. The VEO data platform
will support mining, sharing, integration, presentation and analysis of traditional and novel ‘Bio data’ with a range of “Contextual data”, integrating publicly available and confidential data. The VEO analytical platform will support data-intensive interdisciplinary collaboration of geographically distributed
international teams, co-creation of novel advanced analytical solutions, and involving citizen scientists through crowdsourcing of specific challenges. In addition, we will develop workflows to integrate high density laboratory data
(genomics, phenotyping, immunomics) into the VEO system and into risk assessments. The VEO system is (co)designed and tested through five complementary use case scenarios, reflecting main pathways of disease emergence, to attune developments to the needs of its intended users, and obtain proof-of-principle of utility, including ethical, legal and social
implications.

In this context the work of the PhD student will be to produce big data and citizen science data-driven models of mosquito populations (Aedes albopictus, and others) and disease transmission risk (Dengue, Zika, Chiklungunya) that will be incorporated in a real-time platform for stakeholders. The PhD student will form part of the Theoretical and Computational Ecology Lab, and a big team of research technicians and postdoctoral researchers working on research topics related to the platform Mosquito Alert, and relevant partners in the field of vector and disease dynamics in Europe. The main tasks will be related to big data data analysis and modelling, as an example of how the data generated in the VEO platform can be used to build up disease and vector risk models.