1. Data summary
1.1. Purpose of the data collection/generation and relation to the objectives of the project
The objective of MOOD is to establish a framework and visualization platform allowing detection,
monitoring and assessment of epidemiological and genetic data in combination with
environmental and socio-economic covariates in an integrated inter-sectorial, interdisciplinary, One
MOOD targets air-borne, vector-borne, and multiple-transmission route model diseases, including
anti-microbial resistance (AMR) and disease X.
MOOD relies on eight Work Packages (WP) with the following specific objectives, for early
detection, monitoring and assessment of infectious disease threats:
To implement a participatory process based on the identification of the needs of end-users;
To coordinate communication between the WPs and update the impact pathway to create
optimal conditions for a co-conception of innovations according to end-users needs;
To transform a thorough analysis of disease systems (according to the case-country
priorities) into needs for disease data, Big data, and contextual data;
To develop generic functions for the reduction and integration of heterogeneous disease
data, Big data, and contextual data, from different sources, to guarantee and normalize
To translate user needs and outputs into an epidemic intelligence platform, and to ensure
the sustainability of tools and services by embedding their development in the open source
To disseminate project outputs to end-users and public-health stakeholders in Europe (at
local, national and European level) and promote project outputs at global level.
1.2. Dataset description
MOOD will collect or produce the following types of data:
• Qualitative (and quantitative) data collected through stakeholder, recorded interviews,
online surveys and workshops to understand the current infectious diseases surveillance
including Epidemic Intelligence activities, priority needs for change and innovation, to
explore functional schemes of data flow in institutions, work flow and communication
within and between institutions, to translate user needs into technical development (WP1)
on national, international and local level.
• Epidemiological data acquired by open-access or authorized access databases, and data
from web scrapping and text mining, favouring open/free data sources, in collaboration
with other projects and PH/VH national and EU agencies (WP2).
• Genomic data for phylodynamic analysis collected from a selection of appropriate
• Point prevalence data to study antimicrobial resistance (AMR) in food animals (WP2).
• Environmental, agricultural, climatic, demographic, and socio-economic data, as contextual
data to be integrated with disease datasets, taken from global data platforms such as (not
exhaustive list) Eurostat, Worldclim, Earthdata, ESA’s Copernicus, European Environment
Agency’s (EEA) data repositories and Worldpop (WP2, WP3).
• Disease-specific risk maps, vector distribution data and maps, and AMR risk maps (WP4)
• Codes for models and software will also be developed and will be publicly available at the
end of the project (WP4).
• Video and audio-recordings from workshops, summer schools and hackathons,
conferences and meetings of the MOOD project (WP6).