Efficient and rapidly SCAlable EU-wide evidence-driven Pandemic response plans through dynamic Epidemic data assimilation

Pandemics have the potential to disrupt our daily lives and to affect every part of society.

SARS-CoV-2 causing COVID-19 disease painfully showed how responding too late, in a fragmented mannar and/or with too little coordination across different sectors and countries, led to huge human and economic costs.

ESCAPEs main objective is to improve efficiency and scalability of early pandemic response plans by providing evidence-based guidelines, standardised research protocols, retrospective insights, and digital solutions that will support scientists in producing and integrating evidence and inform public health authorities in taking decisions to avert or reduce disease and societal burden.

The project will provide knowledge and tools that will enhance Europes preparedness for a pandemic of pathogen X.

These include a science-based blueprint for faster and better decision-making in managing pandemics, tools and frameworks to improve data availability, collection and sharing, as well as advanced analytics and models to understand and project transmission dynamics of pathogen X under candidate response scenarios.

ESCAPE will also identify determinants of success and failure in managing pathogen X based on the SARS-CoV-2 pandemic, helping to develop effective response strategies for future pandemics.

In addition, the project will contribute to fostering a multi-stakeholder intelligent community allowing improved knowledge sharing and cooperation between policy-makers, the scientific community, the media and the public, ensuring a much more effective response to future pandemics.

In the long-term, by improving pandemic preparedness and the effectiveness of response to a pandemic of pathogen X, the project will contribute to reducing health burden and potential negative societal and economic consequences during pandemics, as well as increase the confidence of policy makers and the public in science-based solutions.