Establishing an observatory for early warning, risk assessment and monitoring of Emerging Infectious Diseases and Antimicrobial resistance

VEO will strive to establish an interactive virtual observatory for the generation and distribution of high-quality actionable information for evidence-based early warning, risk assessment and monitoring of emerging infectious diseases (EID) threats by public health actors and researchers in the One Health domain. VEO has started in January 2020 and will run until 2025. 

VEO will be built by an iterative process between data science and technology experts, disease experts from public health and academia, social scientists, and citizen scientists. The VEO data platform will support mining, sharing, integration, presentation and analysis of traditional and novel ‘Biodata’ with a range of “Contextual data”, integrating publicly available and confidential data. The VEO analytical platform will support data-intensive interdisciplinary collaboration of geographically distributed international teams, co-creation of novel advanced analytical solutions, and involving citizen scientists through crowdsourcing of specific challenges.

In addition, we will develop workflows to integrate high-density laboratory data (genomics, phenotyping, immunomics) into the VEO system and into risk assessments. The VEO system is (co)designed and tested through five complementary use case scenarios, reflecting main pathways of disease emergence, to attune developments to the needs of its intended users, and obtain proof-of-principle of utility, including ethical, legal and social implications.

VEO consists of 20 partners from 12 different countries. Erasmus MC is the coordinator of the project.

RIVM role

RIVM is the coordinator of the work package that will develop an inventory, analysis and guideline(s) for the Ethical, Legal and Social Implications of integrating novel types of data into the VEO core data hubs. A guiding principle within the WP is building the public’s trust in the innovative use of big data for health protection. Emphasis is on next-generation-sequencing data and data obtained from citizen science. 

RIVM colleagues involved:  George Haringhuizen, Carolina dos Santos Ribeiro and Mart Stein.

In addition, RIVM has a large contribution to especially the work package on silent epidemics. The latter concerns infectious disease threats that are characterised by relatively low mortality and/or morbidity. As a result, these ‘silent epidemics’ are difficult to detect and quantify. We aim at exploring the use of sewage metagenomic data for intelligent and efficient surveillance of circulation of pathogens independent of disease notifications. The project will assess how sewage surveillance can be used to detect ‘silent epidemics’, quantify their burden, and assess whether it can be used to reconstruct transmission networks.

RIVM colleague involved: Eelco Franz.


VEO is a research and innovation action funded by the European Commission’s Horizon2020 framework programme under grant agreement ID 874735.