Beyond COVID - how the BY-COVID project is increasing European pandemic preparedness

Informed and rapid decision-making during public health emergencies is contingent on the availability of accurate, interoperable and timely data on a global scale. Effective collection, analysis, reporting and transparent sharing of data and analytical workflows with and between clinicians, researchers and policymakers is therefore vital. Further, the ability to integrate diverse data sets from multiple disciplines is paramount in assisting decision makers in both in surveillance and crisis situations. It is well established that knowledge and data that are not stored in an organised manner become inaccessible and impossible to reuse (Vines et al., 2014). Effective data sharing is key in the response to future pandemics by shaping priorities for research, preparedness plans and effective policymaking. As nations emerge from the acute phase of the COVID-19 outbreak, it is now time to reflect on the regional, national and international challenges faced in data sharing and consolidate the lessons learnt and innovative solutions into Europe's future toolkit for pandemic preparedness. BY-COVID is a Horizon Europe-funded project bringing together a consortium covering clinical, public health, social and bio-molecular sciences. It aims to address some of the key challenges in data-driven decision-making, both in the support of the continuing response to COVID-19 and in the preparedness for future infectious disease outbreaks. Extending beyond infectious diseases, many of the project outcomes and resources can be reapplied in other contexts, for example, food security and the biodiversity crisis. This is enabled by using the FAIR principles (Findable, Accessible, Interoperable, Reusable) as a basis for data and knowledge preservation, analysis and reporting methods (Wilkinson et al., 2016). As we pass the midpoint of the project, we are taking stock and reporting on the progress, value and impact for future outbreak control, disease surveillance and pathogen data sharing (for example, in curation, sequence analysis, genotyping, phenotyping), as well as the impact of collaborations across scientific disciplines.