Project Title 35 |
Demonstration of intelligent decision support for pandemic crisis prediction and management within and across European borders (STAMINA) H2020 Innovation Action |
||||
Name of legal entity |
Country |
Name of client |
Origin of funding |
Dates (start-end) |
Name of consortium members, if any |
BYS Grup |
Türkiye |
EU |
EU |
ONGOING September 2020 – August 2022 March 2023 -extension received |
38 partners from EU, Tunisia, Turkey (BYS Grup) and the UK |
Detailed description of project |
Type and scope of services provided |
||||
STAMINA develops an intelligent decision support tool set for pandemic prediction and management and demonstrates its use by practitioners at national and regional levels within and across EU borders. The STAMINA toolset enables national planners and first responders to anticipate and respond to the “known-unknowns” in their daily effort to enhance health security. Main functionality of the toolset includes:
The toolset is accompanied by a set of Guidelines on effective implementation of risk communication principles and best practices in cross-organisational preparedness and response plans. The use of the STAMINA toolset will be demonstrated through 12 national and regional small-scale demonstrators and one large-scale cross-border simulation exercise involving all consortium partners. |
BYS Group will be responsible for the implementation of Task 4.1. Data collection in cooperation with the Ministry of Health of Turkey. The goal of this task is to identify and characterize the input data that the STAMINA toolset will exploit. The existing data sources, either open or available within the consortium/project, will be mapped and integrated and a strategy for employing this data will be defined. The characteristics of each data source will be specified, including the size of the data (volume and velocity), its type, and the format in which it is provided. Furthermore, an analysis of their quality and reliability will be done, including the completeness, consistency, duplication, correctness, temporal stability, spatial stability, contextualization, predictive value and reliability, with special attention to the multi-source variability and the temporal shift. The partners that are in charge of national demo support will lead the data collection for each country with the support of the rest end-user partners. |