CENTRE DE COOPERATION INTERNATIONALE EN RECHERCHE AGRONOMIQUE POUR LEDEVELOPPEMENT - C.I.R.A.D. EPIC

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(H2020) Innovative models, tools and services for early detection and monitoring of emerging disease to increase the operational capabilities of EU public health.

The MOOD project aims at taking advantage of data mining, analysis and visualization of health, environmental and other data to enhance the utility of event-based surveillance (EBS). Ultimately, MOOD is supporting the work of European and global public and veterinary health agencies and surveillance practitioners by providing existing monitoring platforms with novel features, and methodological and practical support adapted to their needs.

The detection of infectious disease emergence relies on reporting cases, i.e. indicator-based surveillance (IBS). This method lacks sensitivity, due to non or delayed reporting of cases. In a changing environment due to climate change, animal and human mobility, population growth and urbanization, there is an increased risk of emergence of new and exotic pathogens, which may pass undetected with IBS. Hence, the need to detect signals of disease emergence using informal, multiple sources, i.e. event-based surveillance (EBS).

The MOOD project aims at harness the data mining and analytical techniques to the big data originating from multiple sources to improve detection, monitoring, and assessment of emerging diseases in Europe. To this end, MOOD will establish a framework and visualisation platform allowing real-time analysis and interpretation of epidemiological and genetic data in combination with environmental and socio-economic covariates in an integrated inter-sectorial, interdisciplinary, One health approach:

1. Data mining methods for collecting and combining heterogeneous Big data,
2. A network of disease experts to define drivers of disease emergence,
3. Data analysis methods applied to the Big data to model disease emergence and spread,
4. Ready-to-use online platform destined to end users, i.e. national and international human and veterinary public health organizations, tailored to their needs, complimented with capacity building and network of disease experts to facilitate risk assessment of detected signals.

MOOD output will be designed and developed with end users to assure their routine use during and beyond MOOD. They will be tested and fine-tuned on air-borne, vector-borne, water-borne model diseases, including anti-microbial resistance. Extensive consultations with end users, studies into the barriers to data sharing, dissemination and training activities and studies on the cost-effectiveness of MOOD output will support future sustainable user uptake.