MOOD case studies
The MOOD project is collaborating with national and international Public and Veterinary Health agencies in Europe (end-users) to enhance their Epidemic Intelligence capacity through currently five study cases on airborne, vector-borne, multiple transmission routes diseases, including AMR and disease X.
What is the goal of the MOOD case studies?
The technical innovations envisioned by MOOD are based on the constant involvement and co-design with users to ensure they meet their needs. The MOOD case studies establish a close collaborative space where MOOD researchers and end-users discuss together the development of Epidemic Intelligence (EI) tools for a routine use. The case studies focus on model pathogens based on (1) their current impact on the European public health in terms of burden in humans and animals; (2) the economic cost related to their medical care and for outbreak monitoring and control; (3) their sensitivity to climate and other environmental changes and the potential to further emerge; (4) their representativeness of different disease systems (transmission routes) for which different data streams are needed to monitor and early detect possible outbreaks.
In the past year, the MOOD sociologists worked with end-users from Public Health and Veterinary Health agencies from five different countries to identify their daily working routines and desired innovations to improve disease detection, monitoring and assessment. This analysis provided an up-to-date overview of the innovations that end-users expect from the MOOD project.
The study cases will offer the occasion for MOOD researchers to help tackle major EI challenges on:
Data & Covariates
Text Mining
Modelling
Tool Access
MOOD platform for Epidemic Intelligence
3. Integrated generic and disease-specific modules for maximum flexibility and usefulness of the outputs.
How to participate
There are different ways in which you can contribute to the development of a sustainable and functional EBS platform in various phases, including the design, development, testing and validation. Whether you are interested in the overall improvement of EBS or disease-specific tools, MOOD case studies welcome any contribution from Epidemic Intelligence practitioners.
You will be invited to co-design workshops, interviews, demonstrations with developers and to join MOOD’s event to test out the modules!
Are you interested in the general application of the tool?
If you would like to join the development of the generic tools, you are welcome to participate in the discussions. Click on the button below to get in touch and to receive the program.
Are you interested in diseas-specific tools?
If you are interested in one or more disease-specific application(s), contact the associated case study facilitator and join the MOOD case study. The facilitator is the reference person for each case, in charge of coordinating the work on producing tools and solving users’ problems. To learn more about each case study, just click on the buttons below!
Tu-lept Case
Chi-Den-Zika case
Latest updates on activities
Facilitators: Timothée Dub, THL, Finland & Annapaola Rizzoli, FEM, Italy.
Learn more about TBE & WNV case studies.
Updates from 23-24 June 2022 (Annual Consortium Meeting):
- Data & covariates access: Data will be made available on continental and national levels with a maximum resolution of 1 square kilometre, as well as, readily available with standardized polygons (NUTS3), but users will also have the possibility to upload their own shapefile with specific geographical units (polygons) and retrieve data prepared accordingly via an FTP link made available within a few days depending on the complexity of the request. Time series data will be updated yearly, while data reduction will be conducted every two years.
The MOOD platform will also provide guidance to end-users, with a comparison of different data sources for a similar parameter with a description of their strengths and weaknesses as well as a dashboard on which variables have been previously and most commonly used for modelling TBE and WNV. - Risk maps: at this stage, MOOD will provide static risk maps updated yearly/monthly (TBD) that should be sufficient for the needs of surveillance practitioners. Another relevant feature of WNV risk maps will be the estimation of seasonality and transmission magnitude of the disease, so that surveillance practitioners know when to enhance surveillance efforts.
Risk maps and models will be described in great detail for end-users to have a complete understanding of disease drivers. - Event-based Surveillance data (EBS): Integration with existing Epidemic Intelligence tools will be taken into account by our developers to improve uptake of the product. The possibility for a national end-user/surveillance practitioner to load his/her own data in an offline version to compare EBS and IBS data would be a relevant feature of the visualization tool to be developed. One important point to keep in mind is that one needs to proceed with caution when using un-confirmed and unstructured event-based surveillance data and that human involvement is an important step in data validation. End users willing to try using Padi-web can send a mail to padi-web@cirad.fr to get access to the platform.
Case study facilitator: Maria F. Vincenti Gonzalez, ULB, Belgium.
Learn more about the HPAI case study.
Updates from 23-24 June 2022 (Annual Consortium Meeting):
- First contact with participating potential end-users from FAO, EFSA, ESA platform from Cirad and INRAE;
- Despite moderate data availability on HPAI, public and animal health surveillance practitioners (users) expressed that further collaboration on data-sharing would be very benefitting;
- Users also found that risk mapping with different covariates, including wild bird species, is a topic of interest for HPAI;
- Two scenarios were emphasized for HPAI: risk of introduction and risk of the outbreak;
- Determining the interface between wild birds and poultry is relevant for determining the risk of introduction;
- Need to harmonize vocabulary among different platforms;
- Relevant questions:
Which is the best admin level?
How often are covariates updated?
Does the migration map from EFSA have an API that can be used?; - HPAI Study case facilitator reminded that ULB-SpELL lab can support further modeling/analytical questions about HPAI.
Case study facilitator: Chiara Poletto, INSERM, France.
Learn more about the COVID-19 case study.
Updates from 23-24 June 2022 (Annual Consortium Meeting):
- In early 2022, MOOD partners were requested to provide details on the modelling work they implemented to help support the Covid-19 pandemic response.
- A total of 60 studies from 16 partners were reported.
- Preliminary results were presented during the Covid-19 case study on methodology used by partners, data used, missing data, their interaction with decision-makers, and level of communication on the work conducted.
- After a fruitful discussion with MOOD partners and users present, further analyses of existing data and collection of more detailed data from partners was agreed on.
- Further data collection includes elements covering data access, data sustainability, data standardisation, up- and down-scaling of surveillance activities, and collaboration between disciplines and countries.
- The work is aimed for publication, hence provide guidance on epidemic intelligence needs (notably from a data science perspective) for future unknown disease treats, leveraging the multi-national character of MOOD.
Case study facilitator: Elena Arsevska, CIRAD, France.
Learn more about the Lepto case study.
Updates from 23-24 June 2022 (Annual Consortium Meeting):
- Need for better visualization of animal cases and serotypes of Leptospirosis in metropolitan France using the data from the National Reference Laboratory (NRL) at VetsupAgro. There is already a prototype of a visualization platform developed from LIRMM for the NRL and the exchange on the prototype functionalities will continue in the forthcoming period;
- Need to better understand the spatio-temporal evolution of the Leptospirosis human incidence in particular based on climate change in the french overseas territories in the Indian Ocean to support disease surveillance at the commune level. CIRAD will further exchange on data provisioning, data sharing and modeling with local authorities from SPF and ARS from the french oveseas territories in the Indian Ocean.
Case study facilitator: Renaud Lancelot, CIRAD, La Reunion
Updates from 23-24 June 2022 (Annual Consortium Meeting):
- Need to better understand the risk of introduction and circulation of different viral subtypes in the french overseas territories in the Indian Ocean and the risk of introduction of Dengue in metropolitan France using data from flight movement of passengers
- CIRAD will attempt to best support local authorities from SPF and ARS from the french oveseas territories in the Indian Ocean to address the above mentioned needs. Support from MOOD partners with expertise in modeling Dengue and human movements will be highly appreciated in the forthcoming period
The facilitators
The case study facilitator is the reference person for each case, in charge of coordinating the work on producing tools and solving users’ problems. This will involve:
- Organization of the activities related to the case, bringing together end-users and MOOD researchers to address specific questions as defined in the roadmap for each group;
- Linking interdisciplinary issues within each case, and setting up collaborations between different MOOD teams to tackle the challenges;
- Monitoring the progress for his/her group and in collaboration with the MOOD coordination team;
- In collaboration with the impact assessment managers of MOOD set the indicators to measure the change of practices among EI practitioners, assess the impact of the innovations and the innovation pathway.
Get in touch
The MOOD case studies are open to all PH/VH. If you are interested in one or more case studies , do not hesistate to contact the MOOD coordination!