Integrating Multi-Disciplinary Expertise in a Learning and Adaptive European Pandemic Preparedness System

The COVID-19 pandemic has exposed a global need for accelerating research, improving surveillance, and efficiently developing countermeasures against pathogens with epidemic and pandemic potential. LEAPS aims to demonstrate the value and feasibility of a pro-active policy-supporting strategy for genomic surveillance and for pandemic preparedness and response, by delivering a system-wide stakeholder-validated proof of concept, validated in 4 EU countries, of a learning and adaptive European pandemic preparedness system against pathogen X.'ÄØ LEAPS will fill the gaps observed by global, EU (HERA) and national stakeholders in pandemic response by demonstrating the feasibility of combining genomic One Health surveillance, with genomic epidemiologic modeling for detailed pathogen understanding and precise public health intervention design. LEAPS formalizes dynamic health emergency threat assessment linked to the initiation of governance mechanisms to enable timely decisions in crucial, early stages of an outbreak. 'ÄØLEAPS will develop protocols and models for accelerated medical countermeasure development, availability and accessibility. Based on resulting highly effective intervention strategies, timely countermeasure access and governance mechanisms, model-based policy support is proposed to health authorities for effective, implementable, stakeholder co-created epidemic response scenarios against pathogen X. Scenarios are evaluated on health, socio-economic, and sustainability impact. LEAPS brings together a unique multidisciplinary team with optimal complementary expertise and experience. LEAPS will interact regularly with medical and scientific communities, HERA and health authorities in order to disseminate relevant and accessible information, and during non-emergency periods LEAPS will validate a roadmap for large-scale implementation of LEAPS methodology by EU level, and national authorities and stakeholders in an ecosystem of interlinked actors.