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Data Readiness

Access to up-to-date, sustainable data streams and epidemiological studies is crucial in supporting scientists to understand and respond effectively to a Pathogen X pandemic.This programme of work is focused on increasing the availability of high-quality data streams and readiness in various ways. Through a comprehensive review of public and private sector data streams, ESCAPE is working to identify the most pressing data needs and current availability. We will map and create a web-based atlas of epidemiological cohort studies, to support the scientific community in identifying the advantages and disadvantages of different methodological approaches.  Alongside these efforts, ESCAPE is establishing a network of data stewards to  facilitate swift and easy access to necessary data.

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Work package lead: 

Institute for Scientific Interchange (ISI)

Participants of the consortium:

Hasselt University (UH), National Institute of Public Health and Environment (RIVM), National Institute of Health and Medical Research (INSERM),

National Institute of Health Doctor Ricardo Jorge (INSA), University of Bern (UBern)

Tasks of the Work Package

Abstracte futuristische achtergrond
1

Identifying data needs and availability

ISI, INSA, UBern

2

Improve epidemiological data collection: mapping and comparing cohorts for global pandemic preparedness

UBern, ISI

3

Synthetic population design

INSERM, RIVM, UH

4

A Data Stewards Network for pandemic preparedness

ISI, UBern, INSA

Output

Article

Exploring influenza vaccination coverage and determinants through digital participatory surveillance

Article

Mobility resolution needed to inform predictive epidemic models for spatial transmission from mobile phone data

Article

Planning and adjusting the COVID-19 booster vaccination campaign to reduce disease burden

This project was supported by the ESCAPE project (101095619), funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible for them. 

This work was funded by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee [grant number 10051037].

This work has received funding from the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 22.00482.

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