Periodic Reporting for period 3 - MOOD (MOnitoring Outbreak events for Disease surveillance in a data science context)
Período documentado: 2023-01-01 hasta 2023-12-31
The emergence of the new coronavirus virus (COVID-19) at the end of 2019 highlighted the importance of early detection, monitoring, and assessment of emerging infectious diseases (EID) to help epidemic intelligence (EI) staff at public/animal health agencies and decision-makers in the management of epidemics. The MOOD project aims to harness data mining and analytical techniques to the big data originating from multiple sources (official outbreak reports, unofficial media reports, covariates on vectors, host and environmental risk factors for disease emergence) to improve the detection, monitoring, and assessment of EID, all available through a MOOD platform. MOOD outputs are designed and developed with EI staff to ensure routine use during and beyond MOOD. In addition, the consortium will set up an international not-for-profit association (INPA) to ensure the sustainability of the MOOD innovations and platform. The work will be conducted through five case studies: Avian influenza (AI), West Nile virus (WNV), Dengue, Zika and Chikungunya, Leptospirosis, Tick-borne encephalitis (TBE), Antimicrobial resistance (AMR), and disease X (COVID-19) (Figure 1).
During the RP3, we reinforced the links and collaborations between WPs and in particular:
1) We continued the implementation of the learning loops [WP1] (interaction between end-users and developers/researchers to foster the innovations) through six disease-specific modules (WNV, TBE, AMR, COVID-19, CHIK/DEN, HPAI) and three generic modules (covariates visualisation and exploitation, epi data visualisation EDE and PADI-web media-monitoring tool). A first in person testing of the MOOD modules was organised in June 2023 and in link with WP6 (task on outcomes) and WP7 (task on impact), user inputs were used to assess the outcomes and impact/innovation pathway process. We continued to exchange on the scientific advances and MODO platform, though in-person meeting between task leaders and including the WP leaders, on trimestral basis.
2) During the RP3, the research and modelling activities initiated in the former reporting period were intensified, especially on the priority diseases chosen with end-users for the implementation of the MOOD platform (TBE, WNV, HPAI, AMR, COVID-19) (WP2-WP4). Many of the conducted studies, provide the code, the data and covariates (where applicable) to nourish an open science and FAIR (findable, accessible, interoperable & reusable) research. Completed disease profiles were achieved for all disease models (WP2) – they provide a very detailed and useful description on the situation, and perspectives for surveillance, control and research (including gender aspects) for Europe.
3) The information workflow to feed the MOOD platform, which begins from big heterogeneous data sources (related to disease and non-disease data) to provide standardized data according to spatial, temporal, and thematic dimensions, as well as quality evaluation for the MOOD platform continued during the RP3. Linking of the EDE and PADI-web tools with the covariates module of the MOOD platform has been achieved (WP2-WP5).
4) The MOOD platform (WP5 with inputs from WP2-WP4) current prototype is available at: https://mood-platform.avia-gis.com/core
5) We delivered the business plan for the MOOD not-for-profit association (INPA) to be set by the end of the project to allow for sustainability of the MOOD tools and services, with as of December 2023, five partners accepting to be members.
6) We continued to promote the project achievements with regular updates of the MOOD website and social media, along with trimestral webinars and monthly newsletters, and a summer school and hackathon in May 2023 (WP6).
7) The Coordination in link with the two external advisors on ethics and data protection, continued to monitor the respect of ethics and data protection law and principles for all the tasks and activities of the project (WP7 and WP8).
1) We continued the implementation of the learning loops [WP1] (interaction between end-users and developers/researchers to foster the innovations) through six disease-specific modules (WNV, TBE, AMR, COVID-19, CHIK/DEN, HPAI) and three generic modules (covariates visualisation and exploitation, epi data visualisation EDE and PADI-web media-monitoring tool). A first in person testing of the MOOD modules was organised in June 2023 and in link with WP6 (task on outcomes) and WP7 (task on impact), user inputs were used to assess the outcomes and impact/innovation pathway process. We continued to exchange on the scientific advances and MODO platform, though in-person meeting between task leaders and including the WP leaders, on trimestral basis.
2) During the RP3, the research and modelling activities initiated in the former reporting period were intensified, especially on the priority diseases chosen with end-users for the implementation of the MOOD platform (TBE, WNV, HPAI, AMR, COVID-19) (WP2-WP4). Many of the conducted studies, provide the code, the data and covariates (where applicable) to nourish an open science and FAIR (findable, accessible, interoperable & reusable) research. Completed disease profiles were achieved for all disease models (WP2) – they provide a very detailed and useful description on the situation, and perspectives for surveillance, control and research (including gender aspects) for Europe.
3) The information workflow to feed the MOOD platform, which begins from big heterogeneous data sources (related to disease and non-disease data) to provide standardized data according to spatial, temporal, and thematic dimensions, as well as quality evaluation for the MOOD platform continued during the RP3. Linking of the EDE and PADI-web tools with the covariates module of the MOOD platform has been achieved (WP2-WP5).
4) The MOOD platform (WP5 with inputs from WP2-WP4) current prototype is available at: https://mood-platform.avia-gis.com/core
5) We delivered the business plan for the MOOD not-for-profit association (INPA) to be set by the end of the project to allow for sustainability of the MOOD tools and services, with as of December 2023, five partners accepting to be members.
6) We continued to promote the project achievements with regular updates of the MOOD website and social media, along with trimestral webinars and monthly newsletters, and a summer school and hackathon in May 2023 (WP6).
7) The Coordination in link with the two external advisors on ethics and data protection, continued to monitor the respect of ethics and data protection law and principles for all the tasks and activities of the project (WP7 and WP8).
The collective thinking of MOOD partners on the impact pathway has allowed identifying the output and outcome contributing to the four MOOD impacts:
a) Strengthen EU preparedness to address (re-)emerging infectious disease threats by making available the appropriate technology and tools to support an appropriate public health response.
b) Contribute to the EU One-Health action plan against antimicrobial resistance.
c) Contribute to the digital transformation of health and care in the EU Digital Single Market context.
d) Contribute to the Sustainable Development Goals (SDG):
• SDG03: (i) combat epidemics, and (ii) strengthen capacities for early warning and response to health risks.
• SDG13: (i) integrate climate change measures into national policies, strategies, and planning, and (ii) improve education, awareness, and institutional capacities on climate change adaptation, impact reduction, and early warning.
MOOD impacts are linked to the appropriation of MOOD tools and services and changes in EI practices in national and European PH/AH agencies.
We defined 22 impact indicators for the entire project duration. During the RP3 reporting period, we monitored 22 indicators.
a) Strengthen EU preparedness to address (re-)emerging infectious disease threats by making available the appropriate technology and tools to support an appropriate public health response.
b) Contribute to the EU One-Health action plan against antimicrobial resistance.
c) Contribute to the digital transformation of health and care in the EU Digital Single Market context.
d) Contribute to the Sustainable Development Goals (SDG):
• SDG03: (i) combat epidemics, and (ii) strengthen capacities for early warning and response to health risks.
• SDG13: (i) integrate climate change measures into national policies, strategies, and planning, and (ii) improve education, awareness, and institutional capacities on climate change adaptation, impact reduction, and early warning.
MOOD impacts are linked to the appropriation of MOOD tools and services and changes in EI practices in national and European PH/AH agencies.
We defined 22 impact indicators for the entire project duration. During the RP3 reporting period, we monitored 22 indicators.